Posters, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #163 Probing the Interaction of Protamine with Zn-Insulin through Biophysical and Molecular Docking Studies

Presenting author: Soumya Aggarwal Jawaharlal Nehru University, School of Physical Sciences, New Delhi, India Co-author(s): Manoj Munde

Interaction of insulin with a small cationic peptide called protamine is of particular interest because of its pharmacological relevance in the case of severe diabetes. The action profile of insulin-protamine formulation is from crystallizing insulin with zinc in the presence of basic poly-arginine peptide protamine [1]. Zinc plays important role in the biosynthesis and storage of insulin as insulin structure is strongly modulated by the binding of zinc ions. Zinc ions inhibit the fibrillation of monomeric insulin at physiological pH values by forming a soluble Zn-insulin complex [2]. In spite of the long history and successful use of insulin-protamine formulation, the binding mechanism of the insulin-protamine complex is not known. In our work, we are using various biophysical techniques such as Circular Dichroism, Intrinsic fluorescence, ITC, and molecular docking studies to analyze binding protamine-insulin binding.

[1] M. Norrman, F. Hubalek & G. Schluckebier (2007). Structural characterization of insulin NPH formulations. European Journal of Pharmaceutical Sciences.30, 414-423. [2] M. F. Dunn (2005). Zinc-ligand interactions modulate assembly and stability of the insulin hexamer – a review. Biometals.18, 295-303. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #633 Fast and Accurate Constant pH Molecular Dynamics in GROMACS

Presenting author: Noora Aho University of Jyväskylä, Nanoscience Center, Department of Chemistry, Computational Biomolecular Chemistry Group, Jyväskylä, Finland Co-author(s): Pavel Buslaev, Gerrit Groenhof, Berk Hess pH is one of the key parameters affecting the function and dynamics of proteins and other biomolecules. The protonation states of titratable groups in a biomolecule can change at different pH, which alters the electrostatic interactions of the molecule. Still, being able to dynamically change the protonation states and altering the pH is not a standard option in most of the classical computer simulation software. Usually in simulations, protonation states for titratable groups are initially chosen at the given pH by selecting the statistically most probable protonation. This prevents the examination of pH-dependent phenomena, which is why an efficient constant pH molecular dynamics (MD) method in explicit solvent is highly desired. The previous version of continous λ-dynamics based constant pH MD for GROMACS was released for version 3.3.3. The dynamics of the λ-particles was calculated by linearly interpolating between the Hamiltonians of all possible protonation states [1]. In our current implementation, λ-dynamics relies on the interpolation of the charges of the atoms in titratable groups, instead of interpolating the Hamiltonians. This results in a huge improvement in speed compared to the previous version, as the charge interpolation approach only requires calculating once the electrostatic potential for the system with interpolated charges. Thus, even for N titratable sites only one PME call is needed, instead of the previously required 2N PME calls. Together with the improvement in running speed, we will present a convenient scheme to describe titratable groups with more than two protonation states, such as histidine. Currently, we are performing final tests and working on the parallelization scheme. In collaboration with the Gromacs development team, we are integrating our implementation into the main branch of the code with the aim of making it available in future GROMACS releases.

[1] S. Donnini, F. Tegeler, G. Groenhof, H. Grubmüller, Journal of Chemical Theory and Computation., 7, 1962-1978 (2011). Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #658 In silico and in vitro Analysis of a Novel Bis Coumarin Derivative Induced Anti Melanoma Effects: Suppression of the Phosphorylation of Epidermal Growth Factor Receptor (EGFR) and Proto-Oncogene Cellular Sarcoma (c-SRC) Related Downstream Pathways

Presenting author: Quratul Ain Hamdard University, Department of Pharmaceutical Chemistry, Karachi, Pakistan & Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Hamdard University & Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi & Department of Dermatology and Allergic Disease, Ulm University, Germany Co-author(s): Abhijit Basu, M. Iqbal Choudhary, Karin Scharffetter-Kochanek

Drugs with a high potency and selectivity toward multiple biological targets represent a novel and efficient drug discovery paradigm. Signal transduction in cancer cells is a sophisticated process that involves receptor tyrosine kinases (RTKs) that eventually trigger multiple cytoplasmic kinases, which are often serine/threonine kinases. In clinical trials, highly selective or specific blocking of only one of the kinases involved in these signaling pathways has been associated with limited or sporadic responses. Improved understanding of the complexity of signal transduction processes and their roles in cancer has suggested that simultaneous inhibition of several key kinases at the level of receptors and/or downstream serine/threonine kinases may help to optimize the overall therapeutic benefit associated with molecularly targeted anticancer agents. Immunotherapy with CTLA-4 and PD-1 antibodies has emerged as recent breakthrough in the therapy of metastatic melanoma. However limited response rate, severe life-threatening or fatal side effects and resistant nature of malignant melanoma further fuels the urgent quest for new strategies in the battle against metastatic melanoma. A newly emerging concept for the treatment of advanced malignant melanoma is based on developing new synthetic compounds targeting multiple signaling pathways and their corresponding genes. We have discovered a novel multi targeted molecule belonging to the class of bis-coumarin, as a potential anti-melanoma and anti-metastatic drug candidate and have suggested it for further preclinical and clinical trials based on its ability of selectively killing melanoma cells and inhibiting their migration via targeting multiple phosphokinases. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #209 The Full Model of the pMHC-TCR-CD3 Complex: A Structural and Kinetics Characterization

Presenting author: Josephine Alba University of Fribourg, Department of Biology, Molecular Biophysics of Cellular Membranes Group, Fribourg, Switzerland & University of Rome "Sapienza" – Department of Chemistry Co-author(s): Marco D'Abramo, Oreste Acuto

The machinery involved in cytotoxic T-cell activation requires three main characters such as: the major histocompatibility complex class I (MHC I) bound to the peptide (p), the T-cell receptor (TCR), and the CD3-complex which is a multidimer interfaced with the intracellular side. The pMHC:TCR interaction has been largely studied both in experimental and computational models, giving a contribution in understanding the complexity of the TCR triggering process. Nevertheless, a detailed study of the structural and dynamical characterization of the full complex (pMHC:TCR:CD3-complex) is still missing, due to insufficient data available on the CD3-chains arrangement around the TCR. The recent determination of the TCR:CD3-complex structure by means of Cryo-EM technique has given a chance to build the entire proteins system essential in the activation of T-cell, and thus in the adaptive immune response. Here, we present the first full model of the pMHC interacting with the TCR:CD3-complex, built in a lipid environment. To describe the conformational behaviour associated with the unbound and the bound states, all atoms Molecular Dynamics simulations were performed for the TCR:CD3-complex and for two pMHC:TCR:CD3-complex systems, bound to two different peptides. Our data point out that a conformational change affecting the TCR Constant β (Cβ) region occurs after the binding to the pMHC, revealing a key role of such a region in the propagation of the signal. Moreover, we found that the TCR reduces the flexibility of the MHC I binding groove, confirming our previous results. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #498 Multiscale Simulations of Radical Cation Guanine in the Nucleosomal DNA

Presenting author: Laleh Allahkaram ENS de Lyon, Chemistry Laboratory, Theoretical Chemistry Group, Lyon, France & ENS de Lyon Co-author(s): Elise Dumont, Natacha Gillet, Laleh Allahkaram

All eukaryotic cells deal with the issue of tightly packing their genomes inside a small nucleus. This physical problem has been solved by the formation the chromatin1. Eukaryotic DNA is organized into nucleosome which is the fundamental unit of chromatin and comprises 147 base pairs of DNA wrapped around an octameric core composed of four pairs of histone proteins (2 pairs of H3-H4 and two pairs of H2A, H2B)2,3. Histone protein cores have very flexible protuberant tails which play a pivotal and critical role in regulating many biological processes such as transcription, expression, and DNA repair4. The intrinsically disordered nature of histone tails creates obstacle for the structure and dynamics investigations1. Hereby, we simulate the four histone tails, isolated and with the presence of DNA using the palindromic alpha satellite sequence (from 1kx5 pdb structure). In addition to normal Molecular Dynamics simulations, we use Replica exchange with solute tempering(REST2) approach in order to increase the conformational sampling of the flexible tails. This method, which is an outstanding algorithm for sampling of molecular dynamics,5 is ideal for the sampling of aqueous protein solutions in which there are large scale solute conformational change6. Because of the intrinsically disordered character of the histone tails, we performed all simulations with two different well-established force fields for protein such as "traditional" amber force field ff14SB, and the IDP-specific force field ff14IDP7. We report there a conformational analysis of histone tails to compare of the behavior of histone tails with different force field. Furthermore, we consider different protonation states of histidine residues in the absence and presence of DNA. Further analyses consider post-translational modifications (PTMs) on the flexible N-terminal histone tails that include covalent modifications of specific amino acids, such as the methylation of lysines which plays a major role in epigenetic regulation3. Our results will help us to determine the most consistent parameters and relevant starting points to perform nucleosome simulations.

[1] Potoyan, D. A.; Papoian, G. A.Journal of the American Chemical Society2011,133,7405– 7415. [2] Biswas, M.; Voltz, K.; Smith, J. C.; Langowski, J.PLoS Comput Biol2011,7,e1002279. [3] Grauffel, C.; Stote, R. H.; Dejaegere, A.Biochimica et Biophysica Acta (BBA)- GeneralSubjects2015,1850, 1026–1040. [4] Morales, V.; Richard-Foy, H.Molecular and cellular biology2000,20, 7230–7237. [5] Jo, S.; Jiang, W.Computer Physics Communications2015,197, 304–311. [6] Wang, L.; Friesner, R. A.; Berne, B.The Journal of Physical Chemistry B2011,115,9431–9438. [7] Song, D.; Luo, R.; Chen, H.-F.Journal of chemical information and modeling2017,57, 1166– 1178 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #408 Do the Loops in the N-SH2 Binding Cleft Truly Serve as Allosteric Switch in SHP2 Activation?

Presenting author: Massimiliano Anselmi Saarland University, Department of Theoretical Physics, Computational Biophysics Group, Saarbrücken, Germany Co-author(s): Jochen Hub

The Src homology-2 domain containing phosphatase SHP2 is a critical regulator of signal transduction, being implicated in cell growth and differentiation. Activating mutations cause developmental disorders and act as oncogenic drivers in hematologic cancers. SHP2 is activated by phosphopeptide binding to the N-SH2 domain, triggering the release of N-SH2 from the catalytic PTP domain. Based on early crystallographic data, it has been widely accepted that opening of the binding cleft of N-SH2 serves as the key “allosteric switch” driving SHP2 activation. To test the putative coupling between binding cleft opening and SHP2 activation as assumed by the “allosteric switch” model, we critically reviewed structural data of SHP2 and we used extensive molecular dynamics (MD) simulation and free energy calculations of isolated N-SH2 in solution, SHP2 in solution, and SHP2 in a crystal environment. Our results demonstrate that the binding cleft in N-SH2 is constitutively flexible and open in solution, and that a closed cleft found in certain structures is a consequence of crystal contacts. The degree of opening of the binding cleft has only a negligible effect on the free energy of SHP2 activation. Instead, SHP2 activation is greatly favored by the opening of the central β-sheet of N-SH2. We conclude that opening of the N-SH2 binding cleft is not the key allosteric switch triggering SHP2 activation. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #782 Cholesterol Localization Around the Metabotropic Glutamate Receptor 2

Presenting author: Camilo Aponte-Santamaria University of Los Andes, Department of Biomedical Engineering, Max-Planck Tandem Group in Computational Biophysics, Bogotá, Colombia, Present address: Heidelberg Institute for Theoretical Studies, Heidelberg, Germany Co-author(s): Markus Kurth, Fabio Lolicato, Alexandra Teslenko, Irmgard Sinning, Rainer Beck, Britta Brügger, Angelica Sandoval-Perez, Helman Amaya-Espinosa

The metabotropic glutamate receptor (mGluR) 2 plays a key role in the central nervous system. mGluR2 has been shown to be regulated by its surrounding lipid environment, especially by cholesterol, by an unknown mechanism. Here, using molecular dynamics simulations in combination with experiments we show the interaction of cholesterol with at least two, but potentially five more, preferential sites on the mGluR2 transmembrane domain. Our simulations demonstrate that surface matching, rather than electrostatic interactions with specific amino acids, is the main factor defining cholesterol localization. Moreover, the cholesterol localization observed here is similar to the sterol-binding pattern previously described in silico for other members of the mGluR family. Our simulations revealed a significant reduction of residue–residue contacts together with an alteration in the internal mechanical stress at the cytoplasmic side of the helical bundle when cholesterol was present in the membrane. These alterations may be related to destabilization of the basal state of mGluR2. Due to the high sequence conservation of the transmembrane domains of mGluRs, we propose that the molecular interaction of cholesterol and mGluR2 described here is also likely to be relevant for other members of the mGLuR family.

More information: J. Phys. Chem. B 2020, 124, 41, 9061–9078, https://doi.org/10.1021/acs.jpcb.0c05264 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #881 Probing the Transmembrane Dimerization Interface of the TrkA and TrkB Receptors

Presenting author: Christina Athanasiou Heidelberg Institute for Theoretical Studies (HITS), Molecular and Cellular Modeling Group, Heidelberg, Germany & Faculty of Biosciences, Heidelberg University Co-author(s): Rebecca C. Wade

Neuronal survival, axonal and dendritic network maintenance, as well as synaptic plasticity are regulated by several signaling pathways that are modulated by neurotrophins (NTs) and their receptors.[1,2] NTs bind in two different types of receptors; the Trks, which are receptor tyrosine kinases and the p75 receptor, which is a death receptor. The Trks are single-span transmembrane receptors that exert their signaling through dimerization and activation of the intracellular kinase domain. However, dimerization alone is not capable to induce the activation of the receptors, and previous studies have shown that TrkA and TrkB exist as preformed, yet inactive, dimers.[3,4] This indicates that there are at least two configurations of the dimeric forms that correspond to the active and inactive states. A recently published NMR structure (PDB ID: 2N90) of the transmembrane (TM) TrkA homodimer reveals an interaction interface that is indicated by the authors as the inactive state.[5] Mutagenesis studies suggested the existence on an additional interface; possibly the active one. In the present work, we have performed atomistic and coarse-grained Molecular Dynamics simulations of the TrkA TM homodimer structure to explore the possible dimer configurations. A model of the TrkB TM dimer was also built by homology modeling using 2N90 as a template, and simulated as for TrkA. The simulations revealed several rearrangements of the dimers, showing that the interactions between the monomers are transient. This suggests that neurotrophin binding may be important for the stabilization of the TM helix interactions.

Acknowledgement: This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 765704 (www.euroneurotrophin.eu).

[1] Gomez-Palacio-Schjetnan, A. & Escobar, M. L. Neurotrophins and synaptic plasticity. Curr Top Behav Neurosci 15, 117-136, doi:10.1007/7854_2012_231 (2013). [2] Majdan, M., Walsh, G. S., Aloyz, R. & Miller, F. D. TrkA mediates developmental sympathetic neuron survival in vivo by silencing an ongoing p75NTR-mediated death signal. J Cell Biol 155, 1275-1285, doi:10.1083/jcb.200110017 (2001). [3] Shen, J. & Maruyama, I. N. Nerve growth factor receptor TrkA exists as a preformed, yet inactive, dimer in living cells. FEBS Lett 585, 295-299, doi:10.1016/j.febslet.2010.12.031 (2011). [4] Shen, J. & Maruyama, I. N. Brain-derived neurotrophic factor receptor TrkB exists as a preformed dimer in living cells. J Mol Signal 7, 2, doi:10.1186/1750-2187-7-2 (2012). [5] Franco, M. L. et al. Structural basis of the transmembrane domain dimerization and rotation in the activation mechanism of the TRKA receptor by nerve growth factor. J Biol Chem 295, 275-286, doi:10.1074/jbc.RA119.011312 (2020). Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #577 In silico Generation of Holo-Like Conformations of Multi-Pocket Highly Flexible Allosteric Proteins

Presenting author: Andrea Basciu University of Cagliari, Department of Physics, Molecular Modeling Group, Monserrato, Italy Co-author(s): Giuliano Malloci, Andrea Bosin, Paolo Ruggerone, Alexandre M.J.J. Bonvin, Attilio V. Vargiu

Quantitative understanding of molecular recognition is crucial for basic research and for structure-based drug design. Key to this goal is the knowledge of the atomic-level structures of the complexes formed by receptors and their ligands. Determining the structure of a protein by experimental techniques remains a quite demanding task in terms of both cost and duration of the experiments. Computational methods have become a valid complement to experiments, although inaccuracy increases with the extent of the conformational changes associated to protein-ligand binding. To address this limitation, we recently introduced "EDES - Ensemble Docking with Enhanced-sampling of pocket Shape", a computational method based on metadynamics simulations to generate holo-like conformations of proteins by only exploiting their apo structure. Here, we present an improved version of the original protocol enabling to handle multiple - allosteric - binding sites in extremely flexible proteins. We applied our method to a very challenging target, namely the enzyme adenylate kinase (AK), which undergoes very large conformational changes upon ligand binding. Our protocol generated a significant fraction of structures featuring a low RMSD from the experimental geometry of the complex between AK and an inhibitor. These conformations were used in ensemble docking calculations yielding to native-like poses of substrates and inhibitors of adenylate kinase among the top-ranked ones. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #618 Collective Motions of RNA Helicases Involved in RNA Translocation

Presenting author: Robert Adrian Becker Saarland University, Department of Theoretical Physics, Computational Biophysics Group, Saarbrücken, Germany Co-author(s):

In general, helicases are crucial for every living organism, because they work as motor enzymes in various types of cellular processes, such as DNA/RNA transcription, translation, DNA/RNA repair, recombination and splicing. The largest group among them is the Superfamily 2 (SF2), which includes the so called DEAD- and DEAH-box helicases as key players in the splicing pathway. Despite the wide interest in understanding the detailed mechanism of RNA translocation during splicing, the exact movements are still unknown. To observe the collective motions of single-stranded RNA translocation, we performed molecular dynamics (MD) simulations of the DEAH-box helicase Prp43. We combined two methods to overcome potential sampling problems in such a complex and dynamic system - namely simulated tempering and adaptive sampling. Thus, we could observe a full cycle of one nucleotide shift in a continuous trajectory in atomistic detail. From this trajectory, we obtained an in-depth insight into domain motions, the role of specific residues, loops, ATP etc. during the RNA translocation in Prp43 and probably other close family members of SF2. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #625 An Atomistic View of Solvent-Free Protein Liquids: The Case of Lipase A

Presenting author: Sudarshan Behera Jawaharlal Nehru Centre for Advanced Scientific Research, Chemistry and Physics of Materials Unit, Molecular Simulations Lab, Bangalore, India Co-author(s): Sudip Das, Sundaram Balasubramanian

Solvent-free enzymes hold the promise of being able to deliver higher activity at elevated temperatures by virtue of them being not limited by the boiling point of the solvent. They have been realized in the liquid phase through a polymer surfactant coating on the protein surface. However, a clear understanding of intermolecular interactions, structure, dynamics, and the behavior of the minuscule amount of water present in the solvent-free protein liquid is essential to enhance the activity of these biofluids. Using atomistic molecular dynamics simulations, we demonstrate that the scaled spatial correlations between proteins in the hybrid liquid phase of Lipase A enzyme is comparable to the inter-particle correlations in a noble gas fluid. The hydrophilic region of the surfactants forms a coronal layer around each enzyme which percolates throughout the liquid, while the hydrophobic parts are present as disjointed clusters. Inter-surfactant interactions, determined to be attractive and in the range of -200 to -300 kcal/mol, stabilizes the liquid state. While the protein retains its native state conformational dynamics in the solvent-free form, the fluxionality of its side chains is much reduced; at 333K, the latter is found to be equivalent to that of the enzyme in an aqueous solution at 249K. Despite the sluggishness of the solvent-free enzyme, some water molecules exhibit high mobility and transit between enzymes primarily via the interspersed hydrophilic regions. These microscopic insights offer ideas to improve substrate diffusion in the liquid to enable the enhancement of catalytic activity. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #402 Effects of Cryo-EM Freezing on Structural Ensembles

Presenting author: Lars Bock Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Helmut Grubmüller

The recent revolution in cryo electron microscopy (cryo-EM) allows the determination of structures of macromolecular complexes at atomic resolution. Cryo-EM also provides information on structural heterogeneity and ensembles of macromolecules. To obtain cryo- EM images of macromolecules, the samples are first rapidly cooled down to liquid nitrogen temperatures. The rapid cooling preserves some information of the room temperature ensemble. However, to what extent the structural ensemble is perturbed by the cooling is currently unknown. To quantify the effects of cooling, we first estimated the temperature decay rate by solving the heat equation which suggests that cooling takes place within microseconds. Then, we started all-atom explicit-solvent molecular dynamics (MD) simulations of the ribosome from 41 snapshots taken from a room temperature ensemble with linearly decreasing temperature at 11 different cooling rates with simulation lengths ranging from 0.1 to 128 ns. The cooling leads to a marked decrease in the structural heterogeneity of the cooled ensemble. To test if this effect depends on the cooling rate, we used Bayesian statistics to test three thermodynamic and kinetic models of the cooling process. The observation that cooling-rate dependent kinetic models do not improve the prediction of the decrease in heterogeneity compared to the cooling-rate independent thermodynamic model suggests that kinetic effects do not contribute markedly. This observation further suggests that the rapid cooling generally prevents switching of the system between conformational states and that cooling effects are dominated by equilibration into local free-energy minima. The obtained parameters for the thermodynamic model will allow one to quantify the heterogeneity of biologically relevant room-temperature ensembles from cryo-EM structures. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #339 PIP2 Induced Conformational Changes in Kir6.2 Channels – A Molecular Dynamics Study

Presenting author: Michael Bruendl University of Vienna, Department of Pharmacology and Toxicology, Vienna, Austria Co-author(s): Sarala Pellikan, Anna Stary-Weinzinger

ATP-sensitive potassium (KATP) channels consist of an inwardly rectifying K+ channel protein (Kir6.2) pore, to which four ATP sensitive sulfonylurea receptor (SUR) domains are attached, thereby coupling K+ permeation directly to the metabolic state of the cell. Dysfunction is linked to neonatal diabetes and other diseases. K+ flux through these channels is controlled by conformational changes at the helix bundle region, acting as physical barrier for K+ flux. In addition, the G-loop, located at the cytoplasmic domain and the selectivity filter might contribute to gating, as suggested by different disease-causing mutations. Gating of Kir channels is regulated by different ligands, such as Gβγ, H+, Na+, adenosine nucleotides and the signaling lipid phosphatidyl-inositol-4,5-bisphosphate (PIP2), which is an essential activator for all eukaryotic Kir family members. Although molecular determinants of PIP2 activation of KATP channels have been investigated in functional studies, structural information of the binding site is still lacking due to Kir6.2 cryo-EM structures failing to resolve PIP2. Here we use Molecular Dynamics (MD) simulations to examine the dynamics of residues associated with gating in Kir6.2. By combining this structural information with functional data, we investigate the mechanism underlying Kir6.2 channel regulation by PIP2. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #860 Magnesium Coordination of ATP: Force Field Evaluation and Structure-Driver Correction

Presenting author: Floris Buelens Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Hadas Leonov, Bert L. de Groot, Helmut Grubmüller

In the numerous molecular recognition and catalytic processes across biochemistry involving adenosine triphosphate (ATP), the common bioactive form is its magnesium chelate, ATP.Mg2+. In aqueous solution, two chelation geometries predominate, with Mg contacting either the terminal beta and gamma phosphate groups (bidentate) or all three (tridentate). These subforms are approximately isoenergetic, but separated by a high energy barrier. Force field-based atomistic simulation studies of this complex require an accurate representation of its structure and energetics. Here we focused on the energetics of ATP.Mg2+ coordination. With unbiased molecular dynamics simulation showing prohibitively slow interconversion, we devised an enhanced sampling scheme to calculate free energy differences between different Mg2+-phosphate configurations. We observed striking contradictions between Amber and CHARMM force field descriptions, most prominently in opposing predictions of the favoured coordination mode. Through further configurational free energy calculations, conducted against a diverse set of ATP.Mg2+-protein complex structures to supplement otherwise limited experimental data, we observed systematic biases for each force field. However, the force field calculations were strongly predictive of experimentally observed coordination modes, enabling linear corrections to the coordination free energy that deliver close agreement with experiment. Reassessing the applicability of the corrected force field descriptions of ATP.Mg2+ for biomolecular simulation, we observe that calculated properties broadly agree with experimental measurements of solution geometry and the distribution of ATP.Mg2+ structures found in the Protein Data Bank. However, while the corrected Amber force field appears to reproduce both bidentate and tridentate configurations, CHARMM displays an erroneous preference triphosphate overextension. This will affect the interpretation of simulations of bidentate ATP.Mg2+, which comprises the majority of PDB structures. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #757 Two-Domain Nature of Ribosomal Tunnel Proteins: Insights from Protein Data Bank Analysis

Presenting author: Michaela Černeková University of Chemistry and Technology, Department of Physical Chemistry, Prague, Czech Republic Co-author(s): Michal H. Kolář

Ribosomes are ribonucleoprotein particles responsible for protein synthesis, known as translation, during which is a sequence of messenger ribonucleic acid translated into a sequence of amino acids. Ribosomes are essential in all three domains of life - Archaea, Bacteria, and Eukarya. Across the domains, the ribosomes differ notably, although the critical parts are conserved. The main difference is the complexity as the bacterial ribosomes contain less proteins as well as mRNA in comparison with eukaryotic ribosomes. A nascent protein leaves the ribosome through an exit tunnel in the large ribosomal subunit. Numerous interactions occur between the nascent peptide and the tunnel walls, for instance with the narrowest part formed by extended loops of two ribosomal proteins named uL4 and uL22. Besides the loops, uL4 and uL22 also have globular parts at the surface of the ribosome. The globular parts may interact with other ribosomal proteins as well as with some proteins associated with the ribosomes. For example, uL22 interacts with the peptide deformylase, an enzyme removing the formyl group at nascent chain N-terminus. Furthermore, two other ribosomal proteins contribute to the exit tunnel walls - uL23 and uL24. It is unclear what roles are played by the two domains of the ribosomal proteins that contribute to the tunnel walls. We hypothesized an allosteric communication pathway from the tunnel to the ribosome surface, possibly mediated by the uL4 or uL22. To test the hypothesis, a set of about 200 structures from Protein Data Bank was analyzed. Fluctuations analysis of uL22 from the database reveals the most flexible amino acids are at the tip of the loop inside the tunnel. Principal component analysis of Cartesian coordinates suggests that some uL4 elements are structurally correlated. Sequence alignment complements the analyses as it offers an insight into conserved parts of the proteins, e.g. one of the most conserved parts of uL4 includes the loop section. Observations from these analyses can improve understanding of detailed ribosome mechanisms and can be used for preparation of enhanced molecular dynamics systems. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #912 On the Emergence of Orientational Order in Folded Proteins with Implications for Allostery

Presenting author: Debayan Chakraborty University of Texas at Austin, Department of Chemistry, Austin, United States Co-author(s): Mauro Lorenzo Mugnai, D. Thirumalai

The beautiful structures of single and multi-domain proteins are clearly ordered in some fashion but cannot be readily classified using group theory methods that are successfully used to describe periodic crystals. For this reason, protein structures are considered to be aperiodic, and may have evolved this way for functional purposes, especially in instances that require a combination of softness and rigidity within the same molecule. By analyzing the solved protein structures, we show that orientational symmetry is broken in the aperiodic arrangement of the secondary structural elements (SSEs), which we deduce by calculating the nematic order parameter, P2. We find that the folded structures are nematic droplets with a broad distribution of P2. We argue that non-zero values of P2, leads to an arrangement of the SSEs that can resist mechanical forces, which is a requirement for allosteric proteins. Such proteins, which resist mechanical forces in some regions while being flexible in others, transmit signals from one region of the protein to another (action at a distance) in response to binding of ligands (oxygen, ATP or other small molecules). Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #911 Crowding-Induced Spatial Organization of Gene Expression in Cell-Sized Vesicles

Presenting author: Gaurav Chauhan University of Tennessee, Knoxville, Department of Chemical and Biomolecular Engineering, Knoxville, United States Co-author(s): Elizabeth Norred, Michael L. Simpson, Steven M. Abel

A major limitation of cell-free expression systems is the lack of a means to spatially organize gene expression components to mimic cellular environments. We used computer simulations to guide experimental efforts to control the spatial organization of DNA and ribosomes in cell- sized vesicles using macromolecular crowding. With a coarse-grained model of DNA plasmids and crowders, we showed that plasmids were uniformly distributed at low levels of crowding but, due to depletion interactions, became strongly adsorbed to confining surfaces at high levels of crowding. We validated these results using fluorescently-labelled DNA plasmids and ribosomes in cell-sized vesicles. At large concentrations of the crowding agent Ficoll 70, DNA plasmids preferentially localized near vesicle membranes while ribosomes remained uniformly distributed. We then used kinetic Monte Carlo simulations and a coupled mRNA/protein reporter technique to understand the dynamics of transcription and translation. Crowding-induced localization of DNA to vesicle surfaces resulted in lower protein abundance and decreasing translational efficiency with increasing system size. Our approach demonstrates a cell-free platform that provides a means to better understand spatial control of gene expression. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #816 Activation of Integrin αvβ8 by Graphene-Extracted Membrane Lipids

Presenting author: Serena Chen Oak Ridge National Laboratory, Department of Computing and Computational Sciences Directorate, Oak Ridge, United States Co-author(s): Jose Manuel Perez-Aguilar, Ruhong Zhou

Owing to its unique physicochemical properties, graphene holds promise for various application in the biomedical field. However, strong van der Waals attraction between graphene and biomolecules often causes toxicity, while surface passivation of graphene may still stimulate undesired immune response. In this work, we used all-atom Molecular Dynamics simulations to unravel the underlying mechanism of graphene-induced activation of integrin αvβ8, a prominent membrane receptor expressed in immune cells. We modeled the transmembrane (TM) domains of integrin αvβ8 in a 1-palmitoyl-2-oleoyl-sn-glycero-3- phosphocholine lipid bilayer and observed the structural changes in the integrin–membrane complex when interacting with a graphene nanosheet across the membrane. We found that the β8 TM domain interacts with graphene directly or indirectly through extracted lipids, pulling the β8 subunit away from the αv subunit and thus leading to the disruption of the TM domain association by breaking the hydrophobic cluster in the cytoplasmic domains of the αv and β8 subunits. Alanine substitution of two conserved phenylalanine residues on the αv subunit at this hydrophobic cluster further reveals the importance of a stable T-shaped structure in retaining integrin in its inactive state. Our results agree with previous studies on the interactions between other integrin subtypes and their endogenous activators, suggesting an intriguing role that graphene may play in integrin-related signal transduction during its interaction with the membrane. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #826 xDeep-AcPEP: Deep Learning Method for Anticancer Peptide Activity Prediction based on Convolutional Neural Network and Multi-Task Learning

Presenting author: Jiarui Chen University of Macau, Department of Computer and Information Science, Computational Biology and Bioinformatics Lab, Macau, China Co-author(s): Hong Hin Cheong, Shirley W. I. Siu

Cancer is one of the leading causes of death worldwide. Conventional cancer treatment relies on radiotherapy and chemotherapy, but both of these methods bring heavy side effects to patients since these therapies not only attack cancer cells but also damage normal cells. Anticancer peptides (ACPs) are promising alternative as therapeutic agents that are efficient and selective toward tumor cells. Here, we propose a deep learning method based on convolutional neural networks to predict the biological activity (EC50, LC50, IC50 and LD50) toward six tumor cells, including breast, colon, cervix, lung, skin, and prostate. We show that models derived using multi-task learning achieve better performance than conventional single-task models. Being rigorously trained on the CancerPPD data sets, the best models with applicability domain define achieve average mean squared error of 0.24, Pearson’s correlation coefficient of 0.74 and Kendall’s correlation coefficient of 0.57 in repeated five-fold cross- validation. As a step toward model interpretability, we infer the contribution of each residue in the sequence to the predicted activity by means of feature importance weights derived from the convolutional layers of the model. The present method, referred to as xDeep-AcPEP, will help to identify effective ACPs in rational peptide design to achieve therapeutic purposes. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #132 Looking for Species-Specific Allosteric Inhibitors of ATP-Synthase

Presenting author: Luis Fernando Cofas-Vargas National Autonomous University of Mexico, Institute of Chemistry, Department of Chemistry of Biomacromolecules, Coyoacan, Mexico Co-author(s): Enrique García-Hernández

FOF1-ATP synthase is one of the most marvelous and interesting molecular machines. This enzyme, endowed with a sophisticated rotating mechanism, uses the transmembrane proton- motive force generated by the electron transport chain for the endergonic synthesis of ATP. ATP synthase is a multimeric protein of a complex structural organization. The architecture is highly conserved throughout evolution. Significantly, many natural peptides and small organic molecules of endogenous and exogenous origin have been isolated, which interact and inhibit the activity of this enzyme. Using phenotypic screenings, a synthetic anti-ATP synthase molecule approved to treat multidrug-resistant tuberculosis (MDR-TB) was developed. The existence of these ATP synthase binders, both natural and synthetic, can be considered as a clear sign of the druggability of this enzyme. However, the pharmacological potential of this vital enzyme for the survival of most aerobic organisms has not been systematically tested. In this study, we performed mixed-solvent molecular dynamics comparative analysis to identify species-specific binding hotspots on allosteric sites. Using these hotspots, we could perform a molecular biased docking to find a drug that only binds to the pathogen enzymes. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #565 Lipid-Protein Forces Predict Conformational Transition in a Mechanosensitive Channel

Presenting author: Csaba Daday Max Planck Institute for Biophysical Chemistry, Computational Biomolecular Dynamics Group, Göttingen, Germany Co-author(s): Bert L. de Groot

TREK-2 is one of the three potassium channels from the K2P family that is mechanosensitive, meaning that it is more conductive when it detects membrane tension. Through a combination of experimental and computational work, it was known that it adopts two conformations: “up” and “down”; out of these two, the “up” state is more likely under tension and it is also more conductive. These observations formed a near-complete picture as to what happens, but we still did not know how it happens. That is, how membrane tension causes the conformational change and what explains its higher conductivity. We therefore set out to investigate the underlying mechanisms more thoroughly. In this work, we investigate how membrane tension promotes the “up” state by simulating several down-to-up transitions under membrane tension and monitoring how protein-lipid forces change in this process. Through partial-least-squares functional mode analysis, we identify several residues that transmit force from the membrane and promote the conformational change. We also successfully prove the predictive power of the obtained model through full cross-validation across ten replicas. Our model also recovers 4 out the 5 residues that are experimentally known to contribute to stretch activation. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #626 Backbone Modification via Deamidation: An Unconventional Route to the Thermostability of Protein

Presenting author: Sudip Das Jawaharlal Nehru Centre for Advanced Scientific Research, Chemistry and Physics of Materials Unit, Molecular Simulations Lab, Bangalore, India Co-author(s): Aparna Vilas Dongre, Asutosh Bellur, Sanjeev Kumar, Anusha Chandrashekarmath, Tarak Karmakar, Padmanabhan Balaram, Sundaram Balasubramanian, Hemalatha Balaram

The formation of succinimide backbone post-translational modification (PTM) by intramolecular cyclization at Asn-Gly or Asp-Gly segments in proteins is an intermediate step in the process of deamidation, which, described as a “molecular clock” of cellular processes, generally decreases the thermostability of the protein. Surprisingly, the deamidation at Asn109-Asp110 segment of Mj glutamine amidotransferase (MjGATase) increases its thermostability through the formation of a stable succinimide (SNN109) PTM. The observations obtained from crystal structures, Hamiltonian replica exchange with solute scaling (REST2) and well-tempered metadynamics simulations of wild-type (WT) MjGATase and its SNN109S mutant explain this unexpected experimental finding. The negatively charged electrostatic shielding by the succeeding residue (Asp110), as well as the n to π* interactions from the preceding residue (Glu108), prevent the hydrolysis of succinimide, which induces the formation of a “conformational-lock”, thus reducing protein flexibility. Free energy profiles for the WT and SNN109S mutant using the radius of gyration of the succinimide containing loop as the reaction coordinate yielded a single, stable minimum at a lower value of the reaction coordinate for the former and an additional higher energy state at a higher value of the reaction coordinate for the mutant with the complete unfolding of the loop, consistent with the experimentally found reduced thermostability of the mutant lacking succinimide. Furthermore, sequence analysis on 84 archaeal GATases shows that succinimide and its neighbouring residues are highly conserved. Thus, the present study on MjGATase reveals how the introduction of a backbone modification in the protein sequence can lead to the adaptation of an apparently detrimental process to enhance thermal stability, under an evolutionary imperative. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #739 Marked Structural Dynamics of the Active Site Protein-Water Network in the Prototypical “Rigid” Enzyme Human Carbonic Anhydrase II

Presenting author: Chandan Kumar Das Ruhr University Bochum, Department of Theoretical Chemistry, Molecular Simulation Group, Bochum, Germany Co-author(s): Himanshu Singh, Rasmus Linser, Lars Schäfer

Water molecules buried in protein active sites often govern their structure and dynamics and thus play a role in ligand binding/unbinding processes and enzymatic reactions. Experimental techniques such as X-ray crystallography are widely used to locate such immobilized buried water molecules, whereas NMR relaxation and relaxation dispersion can provide insights into the dynamical picture of coupled motions of water molecule(s) and the protein matrix. However, the interpretation of such NMR dynamics data in terms of the underlying atomic motions is often challenging, and assumptions and simplified motional models have to be invoked. MD simulations can aid the interpretation of such NMR experiments at the atomic level. Recent NMRD experiments reported pronounced microsecond timescale conformational dynamics of the active site of apo human carbonic anhydrase II (hCAII) [1,2], a text-book example for a prototypical “rigid” enzyme. HCAII regulates CO2/HCO¬¬3- interconversion and is a potential pharmacological target. The NMRD particularly pointed to Thr198 located in an active site loop and, putatively, the highly conserved active site water network as showing marked conformational dynamics. Interestingly, this conformational dynamics was completely abrogated upon binding of a sulfonamide inhibitor. Our all-atom MD simulations visualize how the active site pocket is shaped by pronounced open/close conformational-exchange dynamics of the Thr198-bearing loop and associated active site water molecules, which are strongly rigidified upon inhibitor binding.

[1] H. Singh, S. K. Vasa, H. Jangra, P. Rovó, C. Päslack, C. K. Das, H. Zipse, L. V. Schäfer, R. Linser, J. Am. Chem. Soc. 2019, 141 (49), 19276. [2] H. Singh, C. K. Das, S. K. Vasa, K. Grohe, L. V. Schäfer, R. Linser, Angew. Chem. Int. Ed. 2020, 59, 22916. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #741 In silico Stretching of a Mechanosensitive Channel: Simulations of Piezo1 Opening by Increases in Membrane Tension

Presenting author: Dario De Vecchis Ruhr University Bochum, Department of Theoretical Chemistry, Molecular Simulation Group, Bochum, Germany & Leeds Institute of Cardiovascular and Metabolic Medicine. School of Medicine, University of Leeds Co-author(s): David J. Beech, Antreas C. Kalli

Cells have sophisticated molecular machines that help them to respond to external mechanical forces. The Piezo1 mechanosensitive channel is the central hub responsible for sensing shear-stress and pressure forces in cell membrane. However, how Piezo1 senses membrane forces and how these are transduced via molecular and structural changes upon gating remain elusive. Here we used coarse-grained and all-atom molecular dynamics simulations to reveal the structural rearrangements that occur when Piezo1 moves from a closed to an open state in response to increased mechanical tension applied to a model membrane. We find that Piezo1 triskelion adapts to membrane stretching by synchronous flattening of its uniquely curved membrane region and expansion of the projected area. Precise lateral and tilting motion of the pore lining helices jointly with movement of the lipids out of the pore, are associated with opening of the channel mouth via lateral fenestrations. Finally, our study suggests that the blade region of Piezo1 senses tension in the membrane because pore opening failed in the absence of the blades. Our results provide a model for how mechanical force opens the Piezo1 channel and thus how it might couple mechanical force to biological response. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #42 Aβ Peptides and β-Sheet Breakers. A Coarse Grained Molecular Dynamics Approach Using GO-Martini

Presenting author: Aishwarya Dhar University of Rome Tor Vergata, Department of Physics, Biophysics Group, Rome, Italy Co-author(s): Silvia Morante

The problem of protein misfolding is at the basis of a class of pathologies known as protein conformational disorders. All known neuro-degenerative diseases belong to this class of pathologies. These diseases are characterized by the mis-folding of proteins that accumulate in aggregates of fibrillar shape. Among them, Alzheimer Disease (AD) is one of the most studied for its high impact on the modern society. (AD) may be caused by deposition of amyloid β-peptide(Aβ) in plaques in brain tissue.[1] The process that leads to the misfolding, aggregation and amyloid plaques formation is not yet fully elucidated. It seems, however, that the “starting point” of the process is an abnormal switch of the peptide secondary structure that leads to β-sheet formation. Several factors are known to affect the Aβ aggregation process. An important role seems to be played by metal ions that have been observed to be abundant in fibril aggregates. Recently, the observation that short synthetic peptides, called β-sheet breaker (BSB's), are able to directly interact with Aβ precluding amyloid polymerisation was at the origin of a significant scientific effort aimed at trying to modulate and prevent Aβ aggregation and fibrillation processes. [2-3] In this presentation we show the role of beta-sheet breaker peptides (BSBs) on the aggregation of Aβ peptides by using coarse-grained molecular dynamics using Martini forcefield. Since the secondary structure switching is a crucial event for the aggregation process, and Standard Martini approach doesn’t allow to properly study the secondary structure evolution, in order to do that I found the recent developed GO-Martini model a promising strategy for this purpose. [4]

[1] Serpell, Biochimica et Biophysica, 2000 [2] Morante, AdvancAlzRes, 2014 [3] Minicozzi, JBC, 2014 [4] Poma, Chem Theory Comput, 2017 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #473 Intermediate Scattering Function in Multi-Channel Dynamics: From Model Systems to Particle-Tracking Data in Live Cells

Presenting author: Cai Dieball Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Mathematical bioPhysics Group, Göttingen, Germany Co-author(s): Adal Sabri, Matthias Weiss, Aljaž Godec

Several experimental techniques probe collective observables related to the intermediate scattering function, i.e. the expectation value of the Fourier-transformed displacement vectors of the system’s particles. These techniques include neutron, X-ray and dynamic light scattering, neutron spin echo and Fourier imaging correlation spectroscopy, and differential dynamic microscopy. Intermediate scattering functions provide useful, complementary information even when applied to experiments that track the motion of individual particles. In our work we analyze the intermediate scattering function in systems with "multi-channel" dynamics, i.e. dynamics stochastically switching between different modes of motion. We first inspect scattering fingerprints in simple model systems with two-channel dynamics. We then analyze trajectories from particle-tracking experiments in the cytoplasm of mammalian cells, and confirm that these display characteristics of anomalous, two-channel fractional Brownian motion. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #786 Feature Selection for Markov State Modeling of Biomolecular Systems Presenting author: Georg Diez University of Freiburg, Institute of Physics, Biomolecular Dynamics Group, Freiburg im Breisgau, Germany Co-author(s): Daniel Nagel, Gerhard Stock

Molecular dynamics simulations provide the potential to infer a fundamental understanding of biomolecular processes from first principles. In practice, however, the very complex and high-dimensional conformational dynamics of biomolecular systems often hinders a straightforward interpretation of the underlying biological mechanisms. Markov state models (MSMs) are a powerful tool to extract the interesting dynamics as they approximate the dynamics of the biomolecular system by memory-less jumps between its metastable conformations. The quality of such a MSM however depends crucially on the prior dimensionality reduction and especially on the preselection of suitable internal coordinates. Here, we present a systematic approach to identify a low-dimensional subset of coordinates which approximates the sysetms full dynamics. To this end, we employ a dissimilarity measures to first extract all coordinates which are of special interest for the allosteric transition in a PDZ domain. Since these coordinates are still highly correlated, we cluster coordinates that represent the same process and subsequently select the central coordinate of each cluster. This ensures that every important process is optimally represented in the low- dimensional subset.

2021-04-12 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #392 Conformational Dynamics of Biomolecules from the Square Root Approximation of the Fokker-Planck Equation

Presenting author: Luca Donati Free University of Berlin, Institute for Chemistry and Biochemistry, Berlin, Germany Co-author(s): Marcus Weber, Bettina G. Keller

Molecular dynamics can be modelled as a stochastic process governed by the Fokker-Planck equation, whose associated operator describes the kinetic properties of the system in terms of rates. Given a discretization of the state-space into disjoint subsets, Square Root Approximation (SqRA) discretizes the Fokker-Planck operator into a transition rate matrix, whose entries are approximated as the product of two terms: the geometric average of the Boltzmann weights of adjacent subsets, and the flux of the configurations through their intersecting surface. The first term is estimated from the potential energy function of the system, while the second term depends on the diffusion constant and the grid used to discretize the space. This method does not require to integrate the associated stochastic differential equations and it can be used to study the conformational dynamics of small molecules, reducing significantly the computational cost. SqRA can also be used, together with enhanced sampling methods, to study large molecules on a set of relevant coordinates. We present the underlaying theory of SqRA and the results obtained from the application of the method to small peptides.

[1] H. C. Lie, K. Fackeldey, and M. Weber, SIAM. J. Matrix Anal. Appl. 34 (2013) 738. [2] L. Donati, M. Heida, B. G. Keller, and M. Weber, J. Phys. Condens. Matter 30 (2018) 425201. [3] M. Heida, Math. Models Methods Appl. Sci. 28 (2018) 2599. [4] L. Donati, M. Weber, B. G. Keller, J. Phys. Condens. Matter 33 (2021) 115902. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #887 Can the Roles of Polar and Non-polar Moieties be Reversed in Non-polar Nolvents?

Presenting author: Cedrix Jurgal Dongmo Foumthuim Ca' Foscari University of Venice, Department of Molecular Sciences and Nanosystems, Theoretical Soft Matter Group, Mestre Venice, Italy Co-author(s): Manuel Carrer, Maurine Houvet, Tatjana Škrbić, Giuseppe Graziano, Achille Giacometti

Using thermodynamic integration, we study the solvation free energy of 18 amino acid side chain equivalents in solvents with different polarities, ranging from the most polar water to the most non-polar cyclohexane. The amino acid side chain equivalents are obtained from the 20 natural amino acids by replacing the backbone part with a hydrogen atom, and discarding proline and glycine that have special properties. A detailed analysis of the relative solvation free energies suggests how it is possible to achieve a robust and unambiguous hydrophobic scale for the amino acids. By discriminating the relative contributions of theentropic and enthalpic terms, we find strong negative correlations in water and ethanol, associated with the well-known entropy-enthalpy compensation, and a much reduced correlation in cyclohexane. This shows that in general the role of the polar and non-polar moieties cannot be reversed in a non-polar solvent. Our findings are compared with past experimental as well as numerical results, and may shed additional light on the unique role of water as a biological solvent. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #278 Predicting the Modulation of the Muscular Acetylcholine Receptor by Acetylcholine through Binding Affinity Calculations

Presenting author: Mina Ebrahimi CNRS, Institut de Biologie Physico-Chimique, Laboratoire de Biochimie Théorique, Paris, France Co-author(s): Jérôme Hénin

As the inhibition of the nicotinic acetylcholine receptor (nAChR) by small molecules interrupts neurotransmission as well as mutation in the nAChR, and consequently, bring about health disorders, exploring the mechanism of the nAChR activation and binding biological ligands to the binding sites has attracted the researchers’ interest. In this study, we investigate the influence of acetylcholine binding on the activation of the neuromuscular receptor in the adult mouse (AChR). Preliminarily, to study the absolute binding affinity of acetylcholine to AChR, the high and low-affinity structural models of the muscular acetylcholine binding protein in the adult mouse are constructed by homology modeling. The absolute binding affinity is estimated by the streamlined alchemical free energy perturbation method (SAFEP). In this approach, we benefit from a particular restraint so-called “distance to bound configuration” (DBC) leading to more accurate evaluations. According to this computational procedure, results are free of artificial bias, and we compare our assessments with experimental data. Moreover, the employed workflow in this work may open perspectives for binding affinity estimation in macromolecules with a more precise and cost-effective computer simulation technique. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #411 Proteome-Scale Discovery of Protein Interactions with Residue-Level Resolution using Sequence Coevolution

Presenting author: Hadeer Elhabashy Max Planck Institute for Developmental Biology, Protein Evolution Department, Biomolecular Interaction Group, Tübingen, Germany Co-author(s): Anna G. Green, Oliver Kohlbacher, Debora S. Marks

Almost all biological processes are effectively mediated by protein-protein interactions (PPIs). However, our knowledge about PPIs lags behind our need for understanding cellular pathways, providing effective therapeutic intervention, and drug discoveries. Sequence coevolution approaches have recently led to a breakthrough in predicting monomer protein structures as well as protein interactions. Here we address, with EVComplex2, the ability to assess the likelihood of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residue pairs. When assaying the E.coli cell envelope proteome, we predicted and resolved 467 PPIs including newly discovered 292 membrane protein interactions that are notoriously difficult to study experimentally. While EVComplex2 is a purely sequence-based method, it provides residue-residue restraints to construct structural models of protein-protein interactions. We provide tens of interaction models including the Flagellar Hook-Filament Junction, Tol/Pal System, and demonstrate the successful application of the method to the eukaryotic human spliceosome complex. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #777 Investigating a Key Mediator of Cross-Resistance through Docking and Molecular Dynamics

Presenting author: Paul-Enguerrand Fady King's College London, Institute of Pharmaceutical Science, London, United Kingdom & Technology Development Group, Public Health England Co-author(s): Lucy Bock, Mark Sutton, James Mason

Antimicrobial resistance (AMR) threatens humanity's continued progress in extending both lifespan and healthspan. There are almost 1,000,000 annual deaths caused by resistant infections already, with predictions of up to 10,000,000 such annual deaths by 2050—it is a crisis we cannot ignore. A pernicious yet understudied facet of AMR is "cross-resistance”. Long-term exposure & adaptation to antiseptics has been shown to lead to cross-resistance against colistin (a "last-resort" antibiotic) in 5 out of 6 Klebsiella pneumoniae strains tested, and to a range of other biocides and antiseptics in 6 out 8 Pseudomonas aeruginosa strains tested. One particular protein, smvR, was found to be mutated in a large number of these antimicrobial-adapted strains, both in K. pneumoniae and P. aeruginosa. This putative Tet- family repressor may therefore be a key player in generic mechanisms of resistance to cationic antimicrobials. Here, we describe molecular docking experiments on homology models of P. aeruginosa’s smvR, both wild-type and mutant. These were carried out in an effort to 1) determine and compare the key residues involved in WT and mutant smvR's binding to octenidine, chlorhexidine, and benzethonium and 2) compare the relative binding affinities of WT and mutant smvR to each antimicrobial. We found a reasonable amount of overlap in the residues involved in binding all 3 antiseptics, with a number of involved amino acids lying in the site of the mutation. Across homology models, the highest binding affinity was for chlorhexidine, followed by benzethonium, and finally octenidine. Furthermore, Differential Scanning Fluorimetry experiments revealed that sodium dodecylsulfate (SDS) may act to stabilise smvR in solution. Here, we describe molecular dynamics simulations carried out to validate these findings. As we ultimately seek to solve the structure of smvR by NMR, an understanding of why and how SDS might provide an appropriate buffer environment will be key for future structural studies. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #810 The Impact of Neuronal Membrane on Amyloid Beta: MD simulations Considering in vivo Conditions

Presenting author: Hebah Fatafta Forschungszentrum Jülich, Institute for Biological Information Processing - Structural Biochemistry (IBI-7), Jülich, Germany Co-author(s): Mohammed Khaled, Michael C. Owen, Abdallah Sayyed-Ahmad, Birgit Strodel

Mounting evidence suggests that the neuronal cell membrane is the main site of oligomer mediated neuronal toxicity of amyloid β-peptides in Alzheimer’s disease. To gain a detailed understanding of the mutual interference of amyloid-oligomers and the neuronal membrane, we carried out microseconds of all-atom molecular dynamics (MD) simulations on the dimerization of Aβ42 in the aqueous phase and in the presence of a lipid bilayer mimicking the in vivo composition of neuronal membranes. The dimerization in solution is characterized by a random coil to β-sheet transition that seems on-pathway to amyloid aggregation, while the interactions with the neuronal membrane decrease the order of the Aβ42 dimer by attenuating its propensity to form a β-sheet structure. The main lipid interaction partners of Aβ42 are the surface-exposed sugar groups of the gangliosides GM1. As the neurotoxic activity of amyloid oligomers increases with oligomer order, these results suggest that GM1 is neuroprotective against Aβ-mediated toxicity. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #720 Probing the Conformational Dynamics of a Conserved Epitope in the SARS- CoV-1 and -2 Spike Protein Using Gaussian Fluctuations and Collective Motions

Presenting author: Matheus Ferraz Federal University of Pernambuco, Department of Fundamental Chemistry, Recife, Brazil & Department of Virology, Aggeu Magalhães Institute Co-author(s): Christian Seitz, Roberto D. Lins

The emergence of novel SARS-CoV-2 variants urges the quest for conserved epitopes to be used as diagnostic and/or vaccinal platforms. Given that several works have reported antibody evasion against some of these variants, the efficacy of the available vaccines and diagnostic may be hampered. In this regard, a cryptic epitope is located in a hidden region of the homotrimeric spike (S) protein and it is conserved across the different betacoronaviruses. This epitope has been described as able to elicit an immune response against SARS-CoV-1, producing a potently neutralizing antibody (Ab) IC50= 5.2 μg/ml), CR3022, as isolated from a convalescent SARS patient. Even though this antibody also binds to the SARS-CoV-2 receptor binding domain (RBD), the neutralization against the full viral particle is curbed. The difference in immunogenicity between SARS-CoV-1 and 2 may be partly ascribed to the lack of an N-glycosylation site that modulates a higher affinity of CR3022 for SARS-CoV-1 RBD. Molecular modeling associated with crystallographic data suggests that the interaction between CR3022 and SARS-CoV full spike is thwarted by sterical clashes with the other domains within the S protein. Thus, since it is known that neutralization occurs, it is inferred that the only possible conformation for which the clashes would be avoided is when there exist two RBDs in the up conformation ("double-up," which has already been observed by Cryo-EM) with a slight rotation of the targeted RBD. These results suggest that Ab binding to this epitope is heavily influenced by the dynamism of the S protein, which leads to a specific conformation optimal for neutralization. Similarly, we hypothesize that the protein dynamics is of uttermost importance for Abs to bind SARS-CoV-2, therefore we set out to investigate the intrinsic fluctuations of this epitope in SARS-CoV-1 and -2 S protein to elucidate how its dynamics might impact Ab neutralization. An enhanced understanding of viral breathing can shed light on the application of this epitope as a potential antigen-based vaccine to stimulate B-cells to produce Abs agnostic to viral mutations. Thus, we have assessed functional motions of the epitope in the context of the spike homotrimer head of SARS-CoV-1 and 2 with two RBDs in the up conformation (PDB ID: 6CRX and 6X2B, respectively) using a minimalist and coarse- grained approach through the Gaussian network model. Initially, the missing loops from the cryo-EM structures were modeled using the modeller software, followed by 1,500 steps of geometry optimization. Short-scale essential dynamics simulations of the fully glycosylated S proteins heads were also employed to characterize the main motions of the epitopes and the S proteins. The CHARMM-36 atomic parameters were used with the Gromacs 2018.8 engine. Simulations were carried out in an explicitly aqueous solvated environment on the isothermal-isobaric ensemble by maintaining temperature and pressure constants at physiological conditions (310K, 1 bar) through the use of a Langevin thermostat and Parrinello-Rahman barostat, respectively. The total number of atoms in the system is ca. 0.8 mi. MD simulations acceleration were performed by the MPI library with CUDA- enabled GPU. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #809 Targeting Aquaporin-1 to Identify New Anti-Cancer Therapies

Presenting author: Sara Gabriela Ferraz Ferreira Faculty of Sciences, University of Lisbon, BioISI - Biosystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Bruno Lourenço da Silva Victor

Aquaporins (AQPs) are a family of 13 small integral membrane proteins whose primary function is to promote the passive transport of water across the cell in response to osmotic gradients generated by solutes’ active transport [1–3]. These small membrane-spanning proteins have been reported to be overexpressed in cancer cells and tumor tissues, strongly suggesting that they may be implicated in tumor formation by contributing to cell differentiation and migration [4]. Therefore, AQPs are seen as new potential diagnostic and therapeutic targets in anticancer treatment, since their inhibition in endothelial and tumor cells might limit tumor growth and spread [2,5]. Therefore, pharmacotherapy via AQPs’ modulation is seen as one of the most promising therapeutic strategies against cancer. However, traditional drug discovery crusades based on the multiple structures available, were unsuccessful. The work here presented focus on the development and application of a new computational workflow based on complementary methods that combine innovative Ligand and Structure-based approaches to identify new AQP1 modulators. By using a multiconfigurational approach based on Molecular Dynamics simulations, we were able to identify and use different representative conformations of AQP1, that strengthen a subsequent Structure-based virtual Molecular Docking screening campaign, using different available compound databases. The most promising compounds were then subjected to MM/PBSA calculations in order to narrow even more the list of AQP1 modulators. The compounds that comprise this small set are now being purchased for onward experimental validation.

[1] K. Takata, T. Matsuzaki, and Y. Tajika, “Aquaporins: Water channel proteins of the cell membrane,” Prog. Histochem. Cytochem., vol. 39, no. 1, pp. 1–83, 2004, doi: 10.1016/j.proghi.2004.03.001 [2] D. Ribatti, G. Ranieri, T. Annese, and B. Nico, “Aquaporins in cancer,” Biochim. Biophys. Acta - Gen. Subj., vol. 1840, no. 5, pp. 1550–1553, 2014, doi: 10.1016/j.bbagen.2013.09.025 [3] A. S. Verkman, “Aquaporins in clinical medicine,” Annu. Rev. Med., vol. 63, no. 1, pp. 303–316, 2012, doi: 10.1146/annurev-med-043010-193843 [4] M. C. Papadopoulos and S. Saadoun, “Key roles of aquaporins in tumor biology,” Biochim. Biophys. Acta - Biomembr., vol. 1848, no. 10, pp. 2576–2583, 2015, doi: 10.1016/j.bbamem.2014.09.001 [5] J. Wang et al., “Aquaporins as diagnostic and therapeutic targets in cancer: How far we are?,” J. Transl. Med., vol. 13, no. 1, p. 96, 2015, doi: 10.1186/s12967-015-0439-7 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #889 Optimization of Halogen Radii for (Bio)molecular PBSA Calculations

Presenting author: Andreia Fortuna Faculty of Sciences, University of Lisbon, BioISI - Biosystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Paulo J. Costa

In force field methods, to emulate the positive region of the electrostatic potential of halogens (σ-hole), an off-center point-charge, often called extra point (EP), is introduced at a given distance from the halogen. This simple strategy, which overcomes the fact that empirical force fields typically consider halogen atoms to carry a negative charge leading to unfavorable interactions with other electronegative atoms [1], has the advantage of a rather low impact on the computational cost, which is important for large-scale simulations. The estimation of protein-ligand binding energies, which is important for structure-based virtual screening and drug design programs, can be performed over molecular dynamics (MD) trajectories, combining Molecular Mechanics (MM) energies with Poisson-Boltzmann surface area (PBSA) continuum solvation methods [2]. This method depends, among other terms, on the estimation of hydration free energies (ΔGhyd) at the PBSA level. PBSA calculations, on the other hand, rely on the assignment of atomic radii (PB radii), however, standard halogen radii can be smaller than typical X···EP distances placing the EP within the solvent dielectric [3]. To overcome this issue, our previous work [3] explored the optimization of the PB radii for a particular EP implementation which uses X···EP = Rmin and RESP charges in the context of GAFF [4]. Herein, we extend the optimization to other off-center point-charge approaches in the context of the same (GAFF) and other force fields (e.g. CHARMM). For that purpose, the performance of PBSA in the calculation of ΔGhyd was evaluated for 142 halogenated compounds for which the experimental values are known. The optimization was based on the minimization of the error against experimental values, leading to sets of halogen PB radii for each methodology in study.

[1] P. J. Costa, R. Nunes, D. Vila-Viçosa, Expert Opin. Drug Discov. 2019, 14, 805-820 [2] C. Wang, P.H. Nguyen, K. Pham, D. Huynh, T.-B.N. Le, H. Wang, P. Ren, R. Luo, J. Comput. Chem. 2016, 37, 2436−2446 [3] R. Nunes, D. Vila-Viçosa, P. J. Costa, J. Chem. Theory Comput. 2019, 15, 4241−4251 [4] M. A. Ibrahim, J. Comput. Chem. 2011, 32, 2564−2574 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #800 Mutational Effects on the Structural and Dynamic Traits of Avian Cryptochromes

Presenting author: Anders Frederiksen Carl von Ossietzky University, Department of Physics, Quantum Biology and Computational Physics Group (QuantBioLab), Oldenburg, Germany Co-author(s): Maja Hanić, Ilia A. Solov’yov

For decades, physicists, as well as biologists, have tried to understand how birds use the magnetic field of the Earth to navigate. Among recent breakthroughs one can name the discovery of the magnetic compass in both eyes of migratory bird species, possibly related to the protein cryptochrome. Cryptochromes from different organisms have slightly different primary amino acid sequences, hence different structures, that would result in different functional properties. The functioning of cryptochromes could for example be influenced through spin relaxation or electron transfer rates leading to protein activation. The present investigation will consider European robin cryptochrome 4 and single amino acid mutation variants of it. The mutations are chosen specifically to explain how evolutionary hotspots have affected the functionality of the protein in different species and the overall goal is to understand why some cryptochromes may serve as a better magnetoreceptor than others. The effects of the evolutionary hotspots are investigated through molecular dynamics simulations. The investigation focuses on stability of the proteins and provides a comprehensive description of the changes in intramolecular distances, root mean square fluctuations, and energies associated with the putative magnetoreceptive functioning of the protein. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #875 A Disease Mutation in the Selectivity Filter of GIRK2 is Associated with a Loss of K+ Selectivity and Dynamics in the Gβγ Binding Site

Presenting author: Theres Friesacher University of Vienna, Division of Pharmacology and Toxicology, Vienna, Austria Co-author(s): Harald Bernsteiner, Anna Stary-Weinzinger

Inwardly rectifying potassium (Kir) channels are essential for numerous physiological processes, including neuronal and cardiac excitability. Recently, the extremely rare Keppen- Lubinsky syndrome (KPLBS), caused by de novo heterozygous mutations in the Kir3.2 (GIRK2) channel, has been described. KPLBS leads to severe developmental and intellectual disabilities, microcephaly, tightly adherent skin and severe generalized lipodystrophy. Recent breakthroughs in x-ray crystallography and cryo-electron microscopy provide insights into the structure of inward rectifier potassium channels and enable detailed characterization of the structural effects of disease-causing mutations. We performed multi-µs molecular dynamics simulations of the WT as well as mutant GIRK2, which carries a KPLBS causing point mutation the selectivity filter. Our simulations provide insights into the structural changes evoked by the KPLBS mutation, as well as the associated molecular mechanisms leading to the loss of K+ selectivity. Furthermore, a Functional Mode analysis (FMA) was performed in order to identify the collective motion of the protein backbone, which is maximally correlated with the mutation-induced dynamics. We determined a region comprising the binding site for a GIRK2 activator as maximally affected by the altered motions observed in the mutant channel. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #553 Elongation Factor G Mutations and Bacterial Resistance to Aminoglycosides

Presenting author: Sara Gabrielli Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Lars V. Bock, Helmut Grubmüller

Elongation Factor G (EF-G) is a GTPase that is involved in protein translation. After peptide bond formation, EF-G binds to the ribosome, hydrolyzes GTP and accelerates tRNA translocation. It has been observed that disease-causing bacteria containing certain mutants of EF-G display resistance towards aminoglycosides, which are a class of broad-spectrum antibiotics. Aminoglycosides induce errors in the decoding of the mRNA and, subsequently, inhibit protein synthesis. During tRNA translocation, EF-G undergoes conformational changes, e.g, a rotation of domains 4-5 relative to domains 1-3. This observation suggests that if EF-G dynamics were altered by the mutations, this effect could play a fundamental role in the resistance mechanism. Interestingly, the EF-G mutations that have been identified in different resistant bacteria are distributed over all EF-G domains in internal and in exposed regions. Specifically, the more internal locations hint that a change of the internal EF-G dynamics, independent of the interactions with the ribosome, would contribute to the resistance mechanism. Here, we use extensive all-atom MD simulations of wild-type and mutated E. Coli EF-G in solution to investigate the effect of these mutations on the internal dynamics and energetics of EF-G. Indeed, from the simulations, we observe that for certain mutations the dynamics of EF-G domains 4-5 is restricted, providing a possible explanation for their resistance mechanism in entropic terms. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #75 Coarse Grained Simulations in the Context of Neurodegenerative Disease

Presenting author: Lianne Dawn Gahan University of Sheffield, Department of Molecular Biology and Biotechnology, Sheffield, United Kingdom Co-author(s): Alexander I P Taylor, Buddhapriya Chakrabarti, Rosie Staniforth

Using an in-house coarse grained Monte Carlo simulation scheme in the NVT ensemble, we have modelled monomers of amyloidogenic protein as hard-core repulsive spherocylinders with patchy attractions in order to produce fibril structures, other oligomeric structures and to observe the dynamics of disease relevant pathologies. In doing this, we can identify potentially neurotoxic species in diseases such as Alzheimer's and consider chracteristics of potential drug targets. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #814 Accurate Absolute Free Energies for Ligand-Protein Binding Based on Non- Equilibrium Approaches

Presenting author: Vytautas Gapsys Max Planck Institute for Biophysical Chemistry, Computational Biomolecular Dynamics Group, Göttingen, Germany Co-author(s): Ahmet Yildirim, Matteo Aldeghi, Yuriy Khalak, David van der Spoel, Bert L. de Groot

The accurate calculation of the binding free energy for arbitrary ligand-protein pairs is a considerable challenge in computer-aided drug discovery. Recently, it has been demonstrated that current state-of-the-art molecular dynamics (MD) based methods are capable of making highly accurate predictions. Conventional MD-based approaches rely on the first principles of statistical mechanics and assume equilibrium sampling of the phase space. In the current work we demonstrate that accurate absolute binding free energies (ABFE) can also be obtained via theoretically rigorous non-equilibrium approaches. Our investigation of ligands binding to bromodomains and T4 lysozyme reveals that both equilibrium and non-equilibrium approaches converge to the same results. The non-equilibrium approach achieves the same level of accuracy and convergence as an equilibrium free energy perturbation (FEP) method enhanced by Hamiltonian replica exchange. We also compare uni- and bi-directional non- equilibrium approaches and demonstrate that considering the work distributions from both forward and reverse directions provides substantial accuracy gains. In summary, non- equilibrium ABFE calculations are shown to yield reliable and well-converged estimates of protein-ligand binding affinity. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #763 The Effects of Dynamic Disorder in an Engineered Assembly of Pentacene in a Metal-Organic Framework

Presenting author: Farhad Ghalami Karlsruhe Institute of Technology (KIT), Institute of Physical Chemistry, Department of Theoretical Chemical Biology, Karlsruhe, Germany Co-author(s):

The metal-organic frameworks (MOFs) materials have been found interest with regard to their application of engineering the packing of organic semiconductors (OSCs) into high ordered columns to achieve high charge mobility. Here, we study charge transport properties of a pentacene-based MOF using recently developed on-the-fly nonadiabatic quantum mechanics/ classical mechanics approach. While the pentacene-based MOF assembles into highly ordered pi stack with long-range order, the experimental charge mobility measurements demonstrate an unexpected hopping-like charge transport mechanism. Our surface hopping simulations not only show the hopping-like mechanism, but further identify the frustrated flipping of the pentacene core around center axis as the reason for the breakdown of band transport, which indicates that the dynamics disorder should also be carefully considered in crystal engineering of molecular OSCs. The present study demonstrates that the nonadiabatic QM/MM method serves as a powerful tool to unravel underling mechanisms of charge transport in OSCs. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #32 Studying and Modeling of Tumor Necrosis Factor Related Apoptosis-Inducing Ligand Superfamily Member 10C (TRAIL 10C) by Bioinformatics Software for Cancer Treatment

Presenting author: Rezvaneh Ghasemi Tabesh Alzahra University, Department of Biotechnology, Hamedan, Iran Co-author(s):

Tumor necrosis factor related apoptosis-inducing ligand belongs to family of the tumor necrosis factor (TNF) that induces apoptosis by binding to cancer cells while no toxicity in normal cells. Because this anticancer protein lacks of experimental three-dimensional structure, in this study, research has focused on the second and tertiary structures by bioinformatics software and database. Its second structure presents a 38% alpha helix, 32% beta strand and 30% coil with the lid in closed conformation. Also, this protein includes four conserved motifs. The tertiary structure was modeled by Swiss PDB Viewer based on 1za3:pdb as a pattern. Molecular dynamics suggested that the total energy of protein is -370382. Moreover, the protein maintains its structure well in organic solvents. These findings identify TRAIL10C as a good candidate due to good structure for cancer therapy. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #405 A Comparative Study of Computational and Experimental Results of Spectral Investigation of Benzo-15-Crown-5

Presenting author: Namrata Ghildiyal H. N. B. Garhwal University, Department of Chemistry, Srinagar-Garhwal, India Co-author(s):

Crown ethers form a family of versatile ligands for physologically important ions like Na+ and K+. They can be selective towards cations based on the size of their cavity and the donor atom in the macrocyclic ring. Benzo crown ethers provide an additional advantage of studying the complexation process through fluorescence studies. This property makes them good candidates for ion sensors. The possibilities and complexities of parallel mechanisms involved in either enhancement or quenching of fluorescence after complexation requires a knowledge of energies of the frontier molecular orbitals of the ligand. In our work we have attempted to verify the computational results of spectral study on benzo-15-crown-5 with experimental results. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #248 Polymer Translocation: A few Investigations from Computer Simulations

Presenting author: Bappa Ghosh IISER Thiruvananthapuram, Department of Chemistry, Thiruvananthapuram, India Co-author(s): Srabanti Chaudhury

Movement of the polymers across a membrane-pore which is termed as polymer translocation, is an ubiquitous biological process. All the biopolymers like proteins, DNA, RNA etc move across the membrane due to the potential difference in two sides. Understanding this process is utmost important in terms of biology and from applications as it is believed to be a cheap and fast sequencing method. Our work focuses on understanding the polymer translocation process through computer simulation which can be realised through sophisticated optical/magnetic tweezers or current measurement experiments on single molecules. We will discuss some of our exciting findings on the translocation process on how it is affected by the external force, mutation on pore, and branching. Our calculations on waiting time distributions, velocity propagation on the backbone of the chain guides us to a quantitative theory of polymer translocation. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #710 Studying Disulfide Shuffling with the Aid of Machine Learning

Presenting author: Claudia Leticia Gomez Flores Karlsruhe Institute of Technology (KIT), Institute of Physical Chemistry, Department of Theoretical Chemical Biology, Karlsruhe, Germany Co-author(s):

A Neural Network implementation into DFTB+ is used to predict the difference between B3LYP and DFTB on thiol-disul de systems. Metadynamics simulations show that new generated energy landscapes using the DFTB+ neural network, mimic the B3LYP functional and get rid of misleading transition states that appeared while using DFTB. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #723 AEDS for Slowly Relaxing Molecular Processes

Presenting author: Oriol Gracia i Carmona University of Natural Resources and Life Sciences, Institute of Molecular Modeling and Simulation, Department of Material Sciences and Process Engineering, Vienna, Austria Co-author(s):

One of the most challenging aspects of protein simulation is the study of slowly relaxing processes such as allostery or ligands that adopt different configurations in the binding site. The state-of-the-art methods to calculate free binding energies rely on performing several short simulations (lambda steps), in which the ligand is slowly transformed into the end-states of interest. This makes capturing the slowly relaxing processes even more difficult, as they would need to be observed in all the lambda steps. One attractive alternative is the use of a reference state capable of sampling all the end-states of interest in a single simulation. However, the energy barriers between the states can be too high to overcome, thus hindering the sampling of all the relevant conformations. To overcome this limitation, a new methodology, AEDS (Accelerated enveloping distribution sampling), has been recently developed, allowing a more efficient sampling by integrating accelerated MD techniques with the use of a reference state. The T4 L99A lysozyme, an extensively studied benchmark system, contains a hydrophobic pocket in which the conformation of a valine, Val 111, highly influences the binding efficiencies of the ligands. The incorrect sampling of the torsional dihedral angle of this valine during the simulations can lead to errors of up to 16 kJ/mol. All approaches that address this issue introduce an appropriate bias relying on previous knowledge regarding the sampling-limiting residue. In the present work we show how, with the correct reference state and the use of AEDS, is it possible to obtain binding energies with the same level of accuracy as the other methods, without the need of previous knowledge of the system. These results represent a promising first step towards the development of a method capable of studying systems that range from small binding-site rearrangements to more intricate molecular events such as allostery. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #764 The Influence of Dynamical Degrees of Freedom on Spin Relaxation in Radicalized Lipids in a Bilayer

Presenting author: Gesa Grüning Carl von Ossietzky University, Department of Physics, Quantum Biology and Computational Physics Group (QuantBioLab), Oldenburg, Germany Co-author(s): Daniel Kattnig, Ilia A. Solov'yov

The entanglement of electron spins plays an important role in many biological processes [1]. Spin relaxation describes the process of this entanglement being broken due to interactions of the involved electrons with the biological environment. In this project we present a molecular dynamics simulation of a lipid bilayer with added oxygen radicals. The oxygen radicals happen to bind to 12 out of the 255 lipids in the simulated sample, converting those lipids into radicals through the formation of a peroxid group. Several degrees of freedom that could be responsible for subsequent spin relaxation in the radicalized lipids were investigated and a comparison in dynamics between the radicalized and non-radicalized lipids was made. These degrees of freedom included, but were not limited, to dihedral angles, the depth of the peroxid group in the membrane and the tail to tail distance of each lipid. The performed analysis identified some restrictions on the dynamical degrees of freedom that permitted to conclude how efficient spin relaxation in lipids is expected. In the next step, the hyperfine coupling constants of the atoms close to the peroxid group were calculated. The hyperfine interactions were studied, dependent on degrees of freedom that modulate spin relaxation. The investigation permited drawing conclusions on the efficiency of spin relaxation in the studied lipid bilayer and to render a generalized outlook on how specific the spin relaxation processes could be expected in analogous biological environments.

[1] Solov'yov, I., Ritz, T., Schulten, K., & Hore, P. (2014). A chemical compass for bird navigation. In M. Mohseni, Y. Omar, G. Engel, & M. Plenio (Eds.), Quantum Effects in Biology (pp. 218-236). Cambridge: Cambridge University Press. doi:10.1017/CBO9780511863189.012 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #706 Structural and Dynamic Characterization of Avian Cryptochrome 4

Presenting author: Maja Hanic Carl von Ossietzky University, Department of Physics, Quantum Biology and Computational Physics Group (QuantBioLab), Oldenburg, Germany Co-author(s): Anders Frederiksen, Ilia A. Solov'yov

Migratory animals need to rely on stable cues such as celestial and/or geomagnetic information. It is remarkable that the inclination angle of the Earth’s magnetic field vector can be used by birds as a source of a geomagnetic compass. Since the geomagnetic field penetrates biological materials the sensor for the magnetic field could be located anywhere inside an animal’s body [1]. Protein that is believed to be involved in magnetic field sensing is called cryptochrome (Cry) [2]. Crys are photoreceptors that are known to regulate the entrainment of the circadian clock in plants and animals. The structure of the protein also includes a chromophore cofactor, a flavin adenine dinucleotide (FAD) that triggers its functioning [3]. There are four types of cryptochromes – Cry1a, Cry1b, Cry2 and Cry4 that have been found in the eyes of birds [4,5]. Cry4, in particular, was found in the outer segment of double cone cells and long-wavelength single cones of birds’ eye and was shown to possess unique biochemical properties, unlike other members of the cryptochrome family, making it the best candidate for a magnetic field receptor in migratory birds [5]. To understand the foundation of cryptochrome magnetic field sensing and unravel its biophysics it is imperative to have the structure of the protein. Currently, the only Cry4 crystal structure available is that of a non-migratory bird, a pigeon (Columba livia) [6]. It is fortunate that in order to elucidate the molecular sensory biology behind the magnetic field sensing in migratory birds, homology models can be used. Homology modeling is a computational process in which a 3D protein structure can be constructed by using the structure of another, similar protein, as a template [7]. In this investigation homology models of birds' Cry4 from migratory birds (European robin and Blackcap) and non-migratory bird species (Chicken and Zebra finch) have been constructed and studied. With thorough molecular dynamics simulation and structural analysis we justify the correctness of the obtained structures and preform a detailed structural comparison of Crys from different bird species. The comparison reveals structural difference of various Cry4, and we argue why some of these differences may endow cryptochromes of migration birds with a stronger magnetic sensing ability. With this investigation, we hope to get a deeper insight into the structural differences that are important for magnetic sensing in migratory birds vs. non-migratory birds.

[1] H. Mouritsen, Nature 558, 50 (2018) [2] D.R. Kattnig, J.K. Sowa, I.A. Solov'yov, and P.J. Hore, New J. Phys. 18 063007 (2016) [3] E. Sjulstok and I.A. Solov’yov, J. Phys. Chem. Lett 11, 3866 (2020). [4] R. Wiltschko, W. Wiltschko, J R Soc Interface. (2019) [5] A. Günther.et al. Current Biology 28, 211 (2018) [6] B.D. Zoltowski, et al. PNAS 116, 19449 (2019) [7] T. Schwede, J. Kopp, N. Guex, M.C. Peitsch, Nucleic Acids Research 31, 3381 (2003) Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #747 Detecting Parallel Transition Paths in Strongly Driven Networks

Presenting author: David Hartich Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Mathematical bioPhysics Group, Göttingen, Germany Co-author(s): Aljaž Godec

Stochastic network-dynamics are typically assumed to be memory-less. Involving prolonged dwells interrupted by instantaneous transitions between states such Markov networks stand as a coarse-graining paradigm for chemical reactions, gene expression, molecular machines, spreading of diseases, protein dynamics, diffusion in energy landscapes, epigenetics and many others. However, as soon as transitions cease to be negligibly short, as often observed in experiments, the dynamics develops a memory. That is, state-changes depend not only on the present state but also on the past. Here, we establish the first thermodynamically consistent mapping of continuous dynamics onto a network, which reveals ingrained dynamical symmetries and an unforeseen kinetic hysteresis [1]. These symmetries impose three independent sources of fluctuations in state-to-state kinetics that determine the ‘flavor of memory’ that in turn allows to detect parallel transition paths. Our results provide a new understanding of catch-bonds involved in cellular adhesion.

[1] DH and A. Godec, arXiv:2011.04628 (2020) Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #307 Molecular Dynamics Simulations of the SARS-CoV-2 Spike Protein

Presenting author: Jan-Mathis Hein Ruhr University Bochum, Department of Theoretical Chemistry, Molecular Simulation Group, Bochum, Germany Co-author(s): Lars Schäfer

The spike protein of SARS-CoV-2 is a major target of the immune system and of many therapeutic interventions. Understanding its molecular interactions and structural dynamics at the atomic level can contribute to devising strategies for its neutralization. Thanks to a concerted community effort and fueled by the cryo-EM resolution revolution, several structures of the spike are available in the PDB, which all have their own individual pros and cons. To construct a complete high-quality atomic model that is suitable for all-atom MD simulations, we used the cryo-EM density maps of multiple structures. Preliminary results from all-atom MD simulations of the glycosylated spike in explicit water will also be presented. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #919 Per|Mut: Spatially Resolved Hydration Entropies from Atomistic Simulations

Presenting author: Leonard Heinz Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Helmut Grubmüller

The thermodynamics of the first few surface water layers profoundly affects the overall free energy change in protein folding and unfolding, bilayer self-assembly, and ligand binding, and many other biomolecular processes. Whereas the enthalpy contribution can, in principle, be directly calculated from atomistic molecular dynamics simulations, the solvation shell entropy calculation suffers particularly from the poor sampling of the high dimensional configuration space. To furthermore understand, e.g., the effects of water molecules inside a binding pocket or the contribution of individual side chains to the hydration entropy, spatial resolution is required. To address these problems, we developed Per|Mut, a new method to calculate spatially resolved hydration entropies. In Per|Mut, we first employ a permutation reduction, which exploits the permutation symmetry of the identical water molecules to alleviate the sampling problem by the Gibbs factor N! without changing the physics. Next, we use a third- order mutual information expansion to obtain the hydration shell entropy. The spatial resolution and the decomposition into one- two- and three-body correlations of the translational and rotational entropies, as well as of the translation-rotation correlation, allows for an easy physical interpretation and characterization of the resolved entropy changes. In test-simulations, Per|Mut yielded accurate entropies for an argon gas test system and solvated alkanes. Applied to the solvation statistical mechanics of hydrated octanol and the protein Crambin, Per|Mut revealed the local effects of individual chemical groups or side chains on the solvation entropy. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #569 Mechanistic Synergism Between Bacterial Pyranose Oxidase and Peroxidase in Lignin Depolymerization

Presenting author: Enikö Hermann University of Natural Resources and Life Sciences, Institute of Molecular Modeling and Simulation, Department of Material Sciences and Process Engineering, Vienna, Austria & Institute of Molecular Modeling and Simulation / Institute of Food Technology, Co-author(s): Clemens K. Peterbauer, Chris Oostenbrink

Lignin is a highly complex aromatic heteropolymer, which comprises 10-30% of the dry weight of lignocellulose. It could provide a renewable source of aromatic chemicals, however, its depolymerization is a challenging task. Studies suggest that bacterial dye-decolorizing peroxidases (DyPs) – a recently described family of heme peroxidase enzymes – could play a key role in bacterial lignin depolymerization. DyPs also have the potential to be utilized biotechnologically for this purpose. Enzymes such as pyranose oxidase (POx) are proposed to act as redox partners for peroxidases such as DyP in the process of lignin depolymerization. The role of POx would be dual in the synergism of these enzymes. It is proposed that at the onset of lignin depolymerization POx oxidizes monosaccharides, and produces hydrogen peroxide. This hydrogen peroxide could fuel the DyP to produce aromatic radicals from lignin, and in some cases highly reactive Mn(III)-ions. Later on, the radicals or the Mn(III)-ions can be reduced by the dehydrogenase activity of the POx, preventing their repolymerization and detoxifying or recycling them. We plan to investigate this redox cycling using enzymes from the Actinobacterium Kitasatospora aureofaciens as models. A POx has already been expressed and characterized [2], and three putative genes of DyP-type peroxidases were identified in the genome. The genes were inserted into a suitable vector, and the DyPs will be expressed and characterized biochemically and biophysically. Homology models have been constructed for these putative DyPs, and molecular dynamics simulations are used to investigate their behaviour. The most recent results will be presented. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #784 Molecular Dynamics Simulations of AHA2 Reveal Preferential Interaction Sites for Anionic Phospholipids

Presenting author: Simon Holtbrügge Ruhr University Bochum, Department of Theoretical Chemistry, Molecular Simulation Group, Bochum, Germany Co-author(s): Lars Schäfer, Dario de Vecchis

AHA2 is a transmembrane plant protein from the P-type ATPase superfamily involved in the maintenance of an electrochemical gradient across the membrane by active proton transport. Membrane gradients are crucial for plant physiology and for many organisms to drive secondary transport processes such as nutrient uptake. Homologous proteins are required to establish sodium-potassium gradients in animals, support calcium homeostasis as well as stomach acidification in humans, or maintain lipid asymmetry across membrane leaflets. Evidence from other P-type ATPases suggested that direct interactions with membrane lipids play a key role in regulating the activity and stability of P-type ATPases. However, the membrane-protein interplay of P-type ATPases is a vast and complex field with many regulatory effects yet to discover. Here, we identify interaction sites of AHA2 with anionic phospholipids and propose their role in protein regulation. In this work we used coarse-grain molecular dynamics simulations employing the MARTINI coarse-grain (CG) force-field to study AHA2 within four different membrane compositions, each containing 90% neutral and 10% anionic phospholipids. Our results pinpoint four protein contact sites for anionic phospholipids and two distinct ones for neutral phospholipids in the transmembrane domain of AHA2. The protein residues involved most in the interactions with anionic lipids were identified by quantifying lipid-protein contacts. Finally, a multiple sequence alignment indicated the residues identified in the CG-MD simulations as conserved across functionally different P-type ATPases from several organisms. Although proposed consequences of the found interaction sites remain to be validated by mutational studies, our results highlight the significance of conserved lipid-protein interactions for the regulation of P-type ATPases. Future studies might investigate influences of other lipid species abundant in the natural membrane environment of P-type ATPases such as cholesterol or neutral phospholipids. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #141 Searching for a Starting Model to Simulate Spontaneous Formation of an Inverse Hexagonal Phase of Poly-Unsaturated Monogalactolipids at Atomic Resolution

Presenting author: Jakub Hryc Jagiellonian University, Department of Computational Biophysics and Bioinformatics, Kraków, Poland Co-author(s): Michał Markiewicz, Marta Pasenkiewicz-Gierula

Monogalactosyldiacylglycerol (MGDG) is the main lipid component of thylakoid membranes. The MGDG molecule consists of a polar head comprising the β-galactose moiety and the glycerol backbone, and acyl chains of different length and degree of unsaturation. The most abundant MGDG in plant thylakoids has both α-linolenoyl (di-18:3, cis) chains and as such, tends to form spontaneously an inverse hexagonal phase (HII) in water under ambient conditions. In this study four systems, each consisting of two di-18:3 MGDG bilayers separated by water layers are constructed and molecular dynamics (MD) simulated. In each system, the outer layer contains 30 water molecules per lipid (30 H2O/MGDG) whereas, the number of water molecules the inner layer varies and is 8, 12, 15 and 30 H2O/MGDG (W8, W12, W15, and W30, respectively). MD simulations have been carried out on the µs timescale at 333 K (W12, W15) and 353 K (W8, W30) in the OPLS-AA force field, using the GROMACS software package. The results obtained so far indicate that the inner hydration of 8 and 12 H2O/MGDG is too low for stalk formation whereas 30 H2O/MGDG is probably too high but MD simulations are in progress so it is too early for final conclusions. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #716 Reactive Oxygen Species Production in Metabolic Enzymes

Presenting author: Peter Husen University of Southern Denmark, Department of Physics, Chemistry and Pharmacy, Quantum Biology and Computational Physics Group (QuantBioLab), Odense, Denmark Co-author(s): Claus Nielsen, Carlos F. Martino, Ilia A. Solov'yov

Several metabolic enzymes in cells may also be sources of potentially harmful production of reactive oxygen species (ROS) such as superoxide (O2•−) as a byproduct. Among the main identified sources for superoxide production are complexes I and III of the electron transport chain, respectively the ETF enzyme and the cytochrome bc1 complex, in the inner mitochondrial membrane. The ETF enzyme facilitates electron transport as part of the fatty acid metabolism in mitochondria [1] and contains the redox active cofactor flavin adenine dinucleotide (FAD/FADH2), which could react with molecular oxygen, leading to ROS byproducts. As a first step towards modeling ROS production in the ETF enzyme, a comprehensive mapping and analysis of possible O2 binding sites in the enzyme was carried out using all-atom molecular dynamics simulations [2]. A number of O2 binding sites were identified near its FADH2 cofactor, which could act as reducing agent in superoxide formation. An extensive set of simulations was further used to characterize the binding of both O2 and superoxide in select binding sites to measure binding times and model the reactant and product states of possible electron transfer processes leading to superoxide formation. We further argue that a reduction of O2 by FADH2 may initially lead to formation of an entangled radical pair between the two, and ROS production in the ETF enzyme may therefore be controlled by the spin dynamics of this radical pair [3].

[1] J.V. Rodrigues, and C.M. Gomes, Free Radical Biol. Med. 53, 12 (2012) [2] P. Husen, C. Nielsen, C.F. Martino, and I.A. Solov‘yov, J. Chem. Inf. Model 59, 4868 (2019) [3] J.A. Imlay, Nat. Rev. Microbiol 11, 443–454 (2013) Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #759 Multiscale Simulations of Histidine Kinase Activity

Presenting author: Fathia Idiris Karlsruhe Institute of Technology (KIT), Steinbuch Centre for Computing, Multiscale Biomolecular Simulation Group, Eggenstein-Leopoldshafen, Germany Co-author(s): Alex Schug

One of the main signal transduction mechanisms in bacteria are two-component systems, which are comprised of homodimeric sensor histidine kinase (HK) and response regulator proteins. Sensor histidine kinases are multidomain, transmembrane proteins, which function through a reversible interplay of conformational transitions between states, an autophosphorylation reaction and a phosphoryl-transfer reaction with a response regulator protein. While the structural properties of HKs differ, they all have a conserved kinase core consisting of the homodimeric catalytic domain and dimerization histidine phosphotransfer domain. We explored the conformational transitions in the conserved core following signal detection using multiscale molecular dynamics simulations. A dual basin structure-based model which incorporates structural information of the active and inactive states of HK was constructed using a micro-mixing approach. After demonstrating a reversible transition between the two states, we are now investigating the influence of external forces on the sensor domain. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #857 Twist-Bending Elasticity and Energetics of the Plus-End Mirotubule Tip

Presenting author: Maxim Igaev Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Helmut Grubmüller

Microtubules (MTs), mesoscopic cellular polymers, grow by the addition of GTP-bound tubulin dimers at their dynamic flaring tips. Mechanical energy of conformational changes in tubulin upon hydrolyzing GTP to GDP is used by the MT lattice primarily to generate directed forces during catastrophic shortening. It was suggested that the mechanical stability of MTs is determined by the fine balance between lateral interactions and intrinsic lattice strain. However, due to the system complexity and the inability of modern structural methods to time-resolve the disassembly process directly and at high resolution, the fundamental physical principles behind MT instability remain elusive. Here, we used atomistic simulations to study the spontaneous relaxation of complete MT tip models from high-energy straight to relaxed splayed conformations and to comprehensively characterize the elasticity of MT tips. Starting from a blunt-end MT structure, our simulations revealed a strong dependence of the relaxation to a 'flared' MT on the nucleotide state. Further, we found an unexpected heterogeneity in protofilament splaying along the MT circumference, except at the unique seam interface, which was prone to splaying in all of our simulations. Finally, the free energy temporarily stored in the straight GDP-MT tip was released primarily along both bending and torsional degrees of freedom, as opposed to common mechanochemical models. Our data thus open a way for a minimal coarse-grained model of the MT plus-end dynamics that incorporates both the spatially heterogeneous nature of the MT shaft and important torsional degrees of freedom disregarded in previous models. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #631 Predicting Ion Channel Conductance From Dissipation-Corrected TMD and LE Simulations

Presenting author: Miriam Jäger University of Freiburg, Institute of Physics, Biomolecular Dynamics Group, Freiburg im Breisgau, Germany Co-author(s): Steffen Wolf

Ion channels control information transfer and vital functions in the human body. To gain insight into their molecular mechanisms of ion transfer and to predict conductance characteristics, we here applied dissipation-corrected targeted MD to potassium ions moving through a Gramicidin channel as test system. Performing a non equilibrium PCA on backbone dihedral angles we find coupled protein-ion dynamics occurring during ion transfer. Using free energies and friction profiles along the channel obtained from the targeted MD simulations as input for Langevin equation simulations with an external electric field, we explicitly predict I- V curves as macroscopic observables. These curves exhibit good agreement with their experimental counterparts when taking into account polarisation effects within the channel. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #773 Demonstrating the Function of the Surface-Exposed Lipoprotein BtuG in Efficient B12 Transport in Association with the Outer-Membrane BtuB Protein

Presenting author: Kalyanashis Jana Jacobs University Bremen, Department of Physics & Earth Sciences, Computational Physics and Biophysics Group, Bremen, Germany Co-author(s): Javier Abellón-Ruiz, Bert van den Berg, Ulrich Kleinekathöfer

BtuB, a TonB-dependent transporter, is an outer membrane protein in Gram-negative bacteria that enables the active transport of cyanocobalamin (vitamin B12) and essential nutrients (1). The protein consists of a channel with 22 β-strands combined with a large N-terminal domain, the luminal domain, folded back into and blocking the interior of the barrel. Substrate binding changes the conformational equilibrium in the Ton box as well as the luminal domain to favor an unfolded state that facilitates substrate translocation through BtuB (1–3). A newly determined BtuBG crystal structure purified from Bacteroides thetaiotaomicron has been considered for the present computational study. The BtuG protein is a lipoprotein strongly connected through a hinge loop to the BtuB protein and can move away from BtuB in a hinge- like fashion (4, 5). We explore the role of BtuG in the transport of the large B12 molecule transport. To this end, we have carried out unbiased molecular dynamics (MD)along with steered MD simulations to explore the B12 acquisition mechanism. The MD simulation results demonstrate that the BtuBG protein transports cyanocobalamin through a pedal-bin mechanism: the substrate first binds to the open BtuG lid before moving to the BtuB binding site.

[1] Hickman, S.J., R.E.M. Cooper, L. Bellucci, E. Paci, and D.J. Brockwell. 2017. Gating of TonB- dependent transporters by substrate-specific forced remodelling. Nat. Commun. 8: 1–12. [2] Gumbart, J., M.C. Wiener, and E. Tajkhorshid. 2007. Mechanics of force propagation in TonB-dependent outer membrane transport. Biophys. J. 93: 496–504. [3] Sarver, J.L., M. Zhang, L. Liu, D. Nyenhuis, and D.S. Cafiso. 2018. A Dynamic Protein-Protein Coupling between the TonB-Dependent Transporter FhuA and TonB. Biochemistry 57: 1045– 1053. [4] Wexler, A.G., W.B. Schofield, P.H. Degnan, E. Folta-Stogniew, N.A. Barry, and A.L. Goodman. 2018. Human gut bacteroides capture vitamin B12 via cell surface-exposed lipoproteins. Elife 7: 1–20. [5] Glenwright, A.J., K.R. Pothula, S.P. Bhamidimarri, D.S. Chorev, A. Baslé, S.J. Firbank, H. Zheng, C. V. Robinson, M. Winterhalter, U. Kleinekathöfer, D.N. Bolam, and B. Van Den Berg. 2017. Structural basis for nutrient acquisition by dominant members of the human gut microbiota. Nature 541: 407–411. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #827 Local Epigenetic Landscape Determines the Integrity of Topologically Associating Domains

Presenting author: Davin Jeong University of Texas at Austin, Department of Chemistry, Austin, United States Co-author(s): Guang Shi, D. Thirumalai

The spatial organization of chromosomes plays a crucial role in gene regulation. Many depletion studies have widely reported that CTCF and cohesin complex shape the genome architecture by mediating chromatin loop, yet an impact of chromatin loop loss on overall genome organization is not well understood. Using our chromosome copolymer model (CCM), we show that most topologically associating domains (TADs) are eliminated upon loop depletion, while checkerboard patterns are preserved and even enhanced. These findings have good agreement with experimental results after removal of cohesin, suggesting that cohesin is directly required to maintain the formation of chromatin loops. Interestingly, some TADs whose formation are driven by a segregation of active and repressive chromatin have minimal dependence on CTCF loop. The integrity of TAD after loop reduction is influenced by chromatin state of its neighboring regions. We reveal that the plaid patterns in the contact map correlate with the arrangement of epigenetic states in a chromatin. Consequently, our results suggest that the underlying epigenetic landscape is an important predictor for mammalian chromatin organization upon loop deletion. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #299 Free Energy Simulations of Guest Binding to a Photoswitchable Cage

Presenting author: Selina Juber Ruhr University Bochum, Department of Theoretical Chemistry, Molecular Simulation Group, Bochum, Germany Co-author(s): Sebastian Wingbermühle, Patrick Nuernberger, Guido H. Clever, Lars Schäfer

Photoswitchable cages that confine small guest molecules inside their cavities offer a way to control the binding/unbinding process through irradiation with light of different wavelengths. However, a detailed characterization of the structural and thermodynamic consequences of photoswitching is very challenging to obtain by experiment alone. Thus, all-atom molecular dynamics (MD) simulations were carried out to gain insight into the relationship between structure and binding affinity. Binding free energies of the B12F12 2- guest were obtained for all photochemically accessible forms of a photoswitchable dithienylethene (DTE) based coordination cage. The MD simulations show that successive photo-induced closure of the four individual DTE ligands that form the cage gradually decreases the binding affinity. Closure of the first ligand already significantly lowers the unbinding barrier and the binding free energy, and therefore favours guest unbinding both kinetically and thermodynamically. Analysis of the different enthalpy contributions to the free energy shows that binding is enthalpically unfavourable and thus an entropy-driven process, in agreement with experimental data. Dissecting the enthalpy into the contributions from electrostatic, van der Waals, and bonded interactions in the force field shows that the unfavourable binding enthalpy is due to the bonded interactions being more favourable in the dissociated state, suggesting the presence of structural strain in the bound complex. Thus, the simulations provide microscopic explanations for the experimental findings and open a possible route towards the targeted design of switchable nanocontainers with modified binding properties. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #704 Molecular Modeling of EmrE, Multidrug Transporter Protein - Studies by Molecular Dynamics Simulation

Presenting author: Jakub Jurasz Gdansk University of Technology, Facutly of Chemistry, Department of Pharmaceutical Technology and Biochemistry, Molecular Dynamics Group, Gdańsk, Poland Co-author(s): Milosz Wieczor, Jacek Czub, Maciej Baginski

EmrE is a small multidrug resistance transporter found in Escherichia coli that confers resistance to toxic polyaromatic cations by proton coupling of these substrates. One of the mechanisms by which cells neutralize the action of toxic compounds is the action of membrane transporters [1]. Secondary transporters, such as the EmrE protein, combine the outflow of drugs with the internal movement of protons across the cell membrane [2]. EmrE is a prototype member of the small multidrug resistance (SMR) transporter family and is one of the smallest known transporters in nature, consisting of only 110 amino acid residues. Studies have shown that the basic functional unit of EmrE is an oligomer, as could be expected from a small size membrane protein. It seems that the basic functional unit of EmrE is the anti- parallel homodimer, as shown by oligomerization tests, substrate binding experiments, negative domination studies and cross-linking analysis [3]. The long term aim of this work is to find basic knowledge about molecular mechanism of action of this transporter in order to design in future potential inhibitors. In particular, the aim of current part of our work is to present and verify hypothesis regarding the mechanism of transport and the mechanism of recognizing toxic compounds by the EmrE protein using molecular dynamics methods. Furthermore because only a structure consisting purely of alpha carbons with poor resolution is available, this work also focuses on creating a reliable structure needed for simulation. The obtained results present different aspects of thermodynamic and structural properties of studied transporter with regard to their mechanism of action.

[1] L.L. Grinius, E.B. Goldberg, Bacterial multidrug resistance is due to a single membrane protein which functions as a drug pump. J. Biol. Chem. (1994) 269 29998–30004. [2] H. Yerushalmi, M. Lebendiker, S. Schuldiner, EmrE an Escherichia coli 12-kDa multidrug transporter, exchanges toxic cations and H+ and is soluble in organic solvents, J. Biol. Chem. (1995) 270 6856-6863. [3] S. Schuldiner, D. Granot, S.S. Mordoch, S. Ninio, D. Rotem, M. Soskin, C.G. Tate, H. Yerushalmi, Small is mighty: EmrE, a multidrug transporter as an experimental paradigm, News Physiol. Sci. (2001) 16 130-134. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #854 Insights Into Structural Dynamic of Apo TLR3 of Cattle and Goat

Presenting author: Muniswamy Kangayan ICAR-Central Island Agricultural Research Institute, Division of Animal Science, Port Blair, India Co-author(s): Shanmugam ChandraSekar

Toll like receptors (TLR) are germ line encoded pattern recognition receptors (PRR), which is a component of innate immunity. The TLR3 is involved in sensing dsRNA of pathogens and induce immune response in host cells. The extracellular domain (ECD) of TLR3 is involved in binding of dsRNA of pathogens. This study reports structural dynamic behaviour of apo cTLR3 and gTLR3 monomeric ECD structure. The tertiary structure of apo cTLR3 and gTLR3 monomeric ECD was modelled using 2A0Z as template by Modeller. The modelled cTLR3 and gTLR3 structure was evaluated using PROCHECK, ProQ, Verif3D, QMEAN and ModFold6. The modelled cTLR3 and gTLR3 monomeric ECD structure was subjected to two independent MD simulation runs of 100ns with random initial velocities using Gromacs. The Root mean square deviation (RMSD) value of protein backbone reveals that both modelled cTLR3 and gTLR3 ECD structure showed large fluctuation and appear to converge or reach equilibration phase after 90ns. The Root mean square fluctuation (RMSF) value of protein backbone showed large fluctuations at both ends, and also at flexible loop region of LRR12 (324-356 residues) and LRR20 (532-563 residues) of both cTLR3 and gTLR3 structure. The fluctuating flexible loop region of LRR20 consists of putative ligand binding residues (His540 & Asn542) in both cTLR3 and gTLR3. The radius of gyration (Rg) plot shows gTLR3 is relative more compact than cTLR3. The variation in dynamic nature of cTLR3 and gTLR3 might be due to structural difference between these modelled structures or might be due to species variation. Further MD simulation study of ligand bound cTLR3 and gTLR3 complex is needed for better understanding of ligand interaction. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #820 Correlated Quantum MD for the Price of Semiempirical: Parameterisation of DFTB3 and Application in QMMM

Presenting author: Mayukh Kansari Karlsruhe Institute of Technology (KIT), Institute of Physical Chemistry, Department of Theoretical Chemical Biology, Karlsruhe, Germany Co-author(s): Fthia Idiris, Denis-Mario Maag, Alexander Schug, Tomáš Kubař, Marcus Elstner

Density functional tight binding(DFTB) is a semi-empirical quantum method, known for its fast and accurate calculations. Because of its fast calculation it gives us the scope to run QM/MM simulations up to nanosecond timescales, which opens the door for us to explore wide variety of bio-chemical reactions which used to be difficult due to time-scale problem in expensive QM calculations. DFTB needs suitable parameters to run as in other semi-empirical methods. In case of DFTB we use two atom centered parameters. Our latest “3OB” parameters for DFTB3 are capable enough to produce accurate results (considering B3LYP as our reference level). However reactions in biochemistry often surprise us with its uniqueness, making fail our existing parameter. We came across two such problems – a) disulfide-thiol shuffling b) autophosphorylation of histidine kinase. These two cases forced us to re-parameterise our existing 3OB parameters to fit best for capturing the reaction mechanism. So we parameterised some “special reaction parameter(SRP)” for these two cases and applied the same in protein in QMMM setup. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #615 Free Energy Simulations of Pore Formation

Presenting author: Gari Kasparyan Saarland University, Department of Theoretical Physics, Computational Biophysics Group, Saarbrücken, Germany Co-author(s): Jochen Hub, Chetan Poojari

Lipid membranes define biological cells by establishing a semi-permeable barrier. Pore formation plays a role in processes such as membrane fusion and fission, the killing of bacterial cells with antimicrobial peptides, and others. Experiments have provided first hints on metastable pores almost 40 years ago. Although pores are heavily studied with a variety of methods, the free energy landscape of the initial stages of the pore formation is still not fully understood. We use molecular dynamics simulations to study the mechanisms and energetics of pore formation. We overcome the challenge of exploring the free energy landscape using umbrella sampling along a recently developed reaction coordinate [1], as previously applied to tension-free pure-lipid membranes [2]. Here, we here study the effects (i) of electric fields on the free energies of pore formation, as applied during electroporation to allow cellular uptake of drugs or genes, and (ii) of the common small antifungal drug itraconazole[3]. Due to itraconazole low solubility in water there are several liposome-based formulations but the release mechanisms remain unclear. The potentials of mean force (PMFs) show that electric fields greatly stabilize open pores and lower the barrier for pore formation. Interestingly, whereas itraconazole has only a small effect on the structure of planar, intact membranes, it strongly stabilized open pores[3]. In near future, we will use these simulation to study pore formation by membrane-active peptides.

[1] J. Hub and N. Awasthi, J. Chem. Theory Comput. 2017, 13, 2352-2366 [2] C. Ting, N. Awasthi, M. Müller, and J. Hub, Phys. Rev. Lett., 120:128103, Mar 2018 [3] G. Kasparyan, C. Poojari, T. Róg, J. Hub, J. Phys. Chem. B, 124, 40, 8811–8821, Sept 2020 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #920 GPU-Accelerated Fast Multipole Method for GROMACS: Performance and Accuracy

Presenting author: Bartosz Kohnke Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Carsten Kutzner, Helmut Grubmüller

The evaluation of Coulomb forces in molecular dynamics (MD) simulations is the computationally most expensive task as it scales with O(N2); hence the calculation of the electrostatic interactions described by Coulomb's law has to be approximated even for moderate numbers of particles. Most MD simulation codes evaluate forces and potentials with the Particle Mesh Ewald (PME) method, which scales with O(N log N). This method is extremely fast on a single node but suffers from a communication bottleneck when parallelized on a large number of compute nodes. The fast multipole method (FMM) is an attractive alternative to PME because, by construction, it requires less communication. The method approximates long-range interactions with multipoles, which are computed from clustered particles. The clustering is described by an underlying octree structure in a way that further separated particles require fewer interaction calculations, hence less communication. As a first step towards massive parallel molecular simulations, we implemented a full CUDA GPU version of the FMM and optimized it for MD simulations. Subsequently, we assessed the performance of our FMM implementation and evaluated its accuracy in comparison to GROMACS' PME. For a valid comparison of the performance, we first evaluated parameters that yield similar forces and potentials as a typical mixed-precision simulation using PME. We found out that FMM tree depth 3 and a multipole order of 8 yield an accuracy that is at the PME level with a similar energy drift. With this parameter setup, we compared FMM to PME performance for various simulation systems of up to 268 M charges. For a benchmark system with 50k atoms, FMM reaches a third of the PME performance. In contrast, for a large box filled with water droplets, FMM/GROMACS is twice as fast as PME already on a single GPU. With this highly optimized CUDA FMM, we anticipate to outperform PME on multi-GPU, multi- node clusters. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #377 Current Regulation in Potassium Channels

Presenting author: Wojciech Kopec Max Planck Institute for Biophysical Chemistry, Computational Biomolecular Dynamics Group, Göttingen, Germany Co-author(s): Andrei Mironenko, Ben Goold, Bert L. de Groot

Potassium channels are important proteins playing key roles in several physiological functions. Despite decades of electrophysiological, structural and computational studies, several principles of ion conduction through potassium channels are still not fully understood. The main structural element of all potassium channels is the conserved selectivity filter (SF), a narrow functional core lined with carbonyl oxygens, that provides a permeation pathway for potassium ions, whereas rejecting sodium ions. Recent combined experimental and computational studies suggest that potassium ions permeate through the channel via the so- called ‘direct knock-on’ mechanism, by forming close ion-ion contacts, without any water co- permeation. It therefore provides a convenient framework to study ion conduction and its regulatory mechanisms in greater detail. Here, we will show results of our Molecular Dynamics-based in silico electrophysiology simulations of several potassium channels (KcsA, MthK, NaK2K, K2P) and their mutants, to uncover mechanisms regulating ionic currents in these channels. We show that a dual conformation of a single hydrophobic residue strategically placed below the SF is able to completely shut ion permeation. Moreover, slight widening of the SF greatly modulates the current, by changing the instantaneous occupancies in the SF, providing an appealing explanation how channels with identical SF exhibit currents varied by an order of magnitude. Finally, we show why potassium ion surrogates (e.g. ammonium) permeate potassium channels at reduced rates, in an excellent agreement with electrophysiological observations. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #918 Towards Protein Function Prediction Based on Molecular Dynamics Simulations

Presenting author: Nicolai Kozlowski Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Malte Schaeffner, Andreas Volkhardt, Helmut Grubmüller

Proteins are essential building blocks of life, conducting most important functions in all living organisms. Although determined by their amino acid sequence and tertiary structure, the particular function of most proteins is unknown. Because many protein functions are realised by protein motions, an even more direct link is expected between protein dynamics and protein function. Here we explore to what extent this link can serve to predict protein function from its dynamics. To this aim, we have performed 3x1 μs molecular dynamics simulations each for a large set of 200 proteins. We then constructed Markov state models from these simulations, which turned out to capture a sufficient amount of protein dynamics to serve as a 'dynamics fingerprint' of the studied proteins. We suggest these dynamics fingerprints as a new tool for protein function prediction. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #545 Proton Transfer Through the Tetrameric Charge Zipper of Assembly Protein

Presenting author: Deepak Kumar Karlsruhe Institute of Technology (KIT), Institute of Physical Chemistry, Department of Theoretical Chemical Biology, Karlsruhe, Germany Co-author(s): Marcus Elstner, Tomas Kubar

The formation of persister cells are among the most important strategies employed by the bacterial population to get rid of antibiotic treatment and external stress. E. coli overproduces amphiphilic α-helical peptide TisB(toxic protein) in harmful conditions, which is localised into the inner membrane. Whenever bacteria are under stress, the persister cells help to equilibrate PH gradient, thereby Proton Motive Force(PMF) is eliminated across the membrane. This phenomenon leads to the depletion of ATP level in the membrane, which results in the formation of biofilm and induces the state of temporary dormancy. Our studies have found TisB to be inserted upright between the membrane as an antiparallel tetrameric bundle and tetramer is stabilized by an extensive pattern of the salt bridge and H-bond in a charge-zipper fashion. In this work, we want to study the detailed molecular mechanism and energetics of the transport of protein and depletion of a proton gradient, involving the breakdown of pH gradient through the insertion of TisB into the membrane using enhanced sampling molecular dynamics. We also want to study the energetics of the passage of water through the peptide assembly using enhanced sampling methods. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #808 Structural Modulation in Smoothened (Smo) in Ciliary Membrane and its Interaction with Membrane Lipids

Presenting author: Shweta Kumari International Institute of Information Technology (IIIT), Center for Computational Natural Sciences and Bioinformatics (CCNSB), Hyderabad, India Co-author(s): Abhijit Mitra, Gopalakrishnan Bulusu

The Smoothened receptor (SMO, a 7 pass transmembrane domain, Class F GPCR family protein) plays a crucial role in the Hedgehog (Hh) signalling pathway, involved in embryonic development, and is implicated in various types of cancer throughout the animal kingdom. SMO is inhibited by Patched (Ptc1; a 12 pass transmembrane domain protein) via small molecules by an unknown mechanism. The structures of SMO typically show bound cholesterol molecules in the extracellular cysteine-rich domain (CRD) and the transmembrane domain (TMD) of the receptor. Here, we carry out coarse-grained molecular dynamics simulations of the SMO receptor in POPC and in ciliary membrane models, respectively, to analyse its structure, interaction, and dynamics involving membrane cholesterol and other molecules in the ciliary membrane models. We are able to identify the interaction of membrane cholesterols with preferential sites in both TMD and CRD, respectively. We also show that, in the presence of cholesterol molecules in the membrane, there is a build up in the concentration of cholesterol molecules near the cholesterol-binding motif of SMO TMD, which helps to maintain the volume of the TM bundle. In addition, our analysis of the correlated motion of SMO domains shows a significant change in the CRD. Further detailed analysis of the dynamics of the TMD, triggered by interactions involving the extracellular domain (ECD) and extracellular loops ( ECLs), reveals a significant movement of TM6 and smaller movements of TM5 and TM7, linked with the helix H8, thus shaping the conformational disposition of the intracellular domain (ICD). Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #589 Running GROMACS in the Cloud

Presenting author: Carsten Kutzner Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Vytautas Gapsys, Christian Kniep, Helmut Grubmüller

We are presenting our experiences with migrating from traditional HPC to cloud-native HPC using a compute-heavy scientific workflow that is usually carried out on supercomputing centers. Our scientific application are atomistic biomolecular simulations using the GROMACS molecular dynamics simulation toolkit. Molecular dynamics simulations are computationally challenging in two respects: First, individual simulations usually need to be parallelized over as many resources (cores, GPUs, nodes) as practicable, to reduce the time to solution from months down to weeks or possibly less. Second, as scientists we are not so much interested in individual simulations, but rather in average properties of the simulated systems. Average properties are however addressed with ensemble runs of many (typically hundreds) slightly different replicas of the system, thus requiring an enormous amount of compute time. Cloud- based HPC can address both challenges: The cloud offers as much compute time as desired, plus the possibility to efficiently scale individual simulations over multiple instances connected by a high-performance interconnect. We build a cloud-based HPC cluster in a straightforward and reproducible way by simplifying software management with SPACK and cluster life cycle management with AWS ParallelCluster. With the SPACK package manager, diverse hardware is easily incorporated into a single cluster, e.g. instances with AMD, ARM, and Intel processors, instances with (multiple) GPUs and instances with high-performance interconnect. On the cluster, we used several representative biomolecular systems to benchmark the GROMACS performance on various hardware that is available in the cloud, both on individual instances as well as across multiple instances. This way we uncover which instances deliver the highest performance or the best performance-to-price ratio for GROMACS simulations. As a next step, we are preparing to run a large ensemble consisting of about twenty thousand individual simulations in the cloud using all resources that are globally available to reduce the time to solution as much as possible. In principle, such an ensemble simulation - which would occupy a medium-sized compute cluster for weeks or even months - could then finish within a day. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #663 Links between Selectivity Filter Conformations and Ion Permeation through Potassium Channels

Presenting author: Chun Kei Lam Max Planck Institute for Biophysical Chemistry, Computational Biomolecular Dynamics Group, Göttingen, Germany Co-author(s): Bert L. de Groot

Many potassium channels are proposed to regulate potassium ion flux across them via gating at their selectivity filter, which is the narrowest part of the channels. However, molecular details of the regulation of ion current by such a selectivity filter gate remain elusive. Based on molecular dynamics simulations of potassium channels, we employ principal component analysis (PCA) and variational approach for Markov processes (VAMP) to determine conformational changes of the selectivity filter. Markov State modeling, together with analysis on timescales of subprocesses in ion permeation, reveals the dependence of ion conductance on the identified conformations of the selectivity filter. This work provides valuable insights into molecular mechanisms of selectivity filter gating and barriers that constitute the nanosecond timescale for ion permeation in multiple potassium channels. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #320 DNA Opening During the Initiation of the Transcription by RNAPII

Presenting author: Jeremy Lapierre Saarland University, Department of Theoretical Physics, Computational Biophysics Group, Saarbrücken, Germany Co-author(s): Jochen Hub

The RNA polymerase II (RNAPII) is a macro-molecular complex which synthesizes RNA by reading a DNA code, this process is called transcription. During the first step of the transcription called "initiation", the RNAPII needs to open the double stranded DNA in order to read the DNA code. This DNA opening is poorly understood, therefore we seek to give atomic details of this crucial step of the transcription with the help of molecular dynamics (MD) simulations. The main pitfall in this study is the long timescale needed for this process to occur regarding the timescale achievable by MD simulations with such a big system. Thanks to recent GROMACS code improvements and the use of hydrogen mass repartitioning we already gained some important speedup with which we've combined some enhanced sampling methods making the DNA opening timescale reachable by our MD simulations. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #386 A Toolbox for Quantifying Memory in Dynamics Along Reaction Coordinates

Presenting author: Alessio Lapolla Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Mathematical bioPhysics Group, Göttingen, Germany Co-author(s): Aljaž Godec

Memory effects in time-series of experimental observables are ubiquitous, have important consequences for the interpretation of kinetic data, and may even affect the function of biomolecular nanomachines such as enzymes. Here we propose a set of complementary methods for quantifying conclusively the magnitude and duration of memory in a time series of a reaction coordinate. The toolbox is general, robust, easy to use, and does not rely on any underlying microscopic model. As a proof of concept we apply it to the analysis of memory in the dynamics of the end-to-end distance of the analytically solvable Rouse-polymer model and an experimental time-series of extensions of a single DNA hairpin measured in an optical tweezers experiment. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #225 What Molecular Dynamics Teach us about Drug Resistance

Presenting author: Florian Leidner Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics & University of Massachusetts Medical School, United States Co-author(s): Nese Kurt Yilmaz, Celia Schiffer

In rapidly evolving pathogens, the emergence of drug resistance is a critical impediment to drug treatment. Mutations in the drug target are a common cause of resistance. Such mutations alter protein-inhibitor interactions through subtle changes in the structure and dynamics of the target protein. The molecular mechanisms by which combinations of mutations, alter drug binding to confer resistance are poorly understood and thus remain difficult to counteract. This problem is especially pertinent for mutations remote from the active site, that do not interfere directly with drug binding. Molecular dynamics simulations are an invaluable tool to quantify molecular interactions and correlate them with changes in protein function. However, identifying functionally relevant interactions remains a key challenge. To address this key issue, I have developed a machine learning strategy that utilizes molecular dynamics simulations and experimental binding affinities to identify conserved mechanisms underlying resistance. This strategy was first evaluated on a panel of HIV-1 protease variants bound to the protease inhibitor darunavir. The protease variants contained a broad range of mutations with darunavir binding potencies ranging from picomolar to micromolar. Feature reduction resulted in a model with 4 specific features that predicts the inhibitor binding free energy within 1 kcal/mol of the experimental values. These predictive features are physically interpretable, as they vary specifically with affinity. They identify changes in the hydrophobic core of the enzyme and hydrogen bonding between protein and inhibitor as the key drivers of resistance. In a follow up study, this strategy was employed to identify trimethoprim-resistant variants of P. Jirovecii dihydrofolate reductase. This system was chosen to specifically evaluate the efficacy of this strategy in a system with sparse experimental data. The model was able to distinguish resistant and susceptible variants with a high degree of accuracy. Changes in the alpha helices adjacent to the drug binding site, but distal from the cofactor binding site were identified to be most closely correlated with resistance. Overall, this physics-based approach of parallel molecular dynamics and machine learning captures mechanisms by which complex combinations of mutations confer resistance and identifies critical interactions that serve as bellwethers of affinity, which will be critical for future drug design. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #418 Cancelled Development of a Hybrid Neural Network/Molecular Mechanics Approach for Metalloprotein Simulations

Presenting author: Bettina Lier University of Natural Resources and Life Sciences, Institute of Molecular Modeling and Simulation, Department of Material Sciences and Process Engineering, Vienna, Austria Co-author(s): Peter Poliak, Julia Westermayr, Philipp Marquetand, Chris Oostenbrink

Metals play a central role in the function of many proteins. The theoretical description of predominantly transition metals in their biological environments is intrinsically complex. Classical molecular mechanics (MM) force fields remain insufficient to accurately account for metal-ligand interactions in molecular dynamics (MD) simulations. Hybrid quantum classical (QM/MM) methodologies provide both a dynamical view on large biological systems as well as precise energetics for the quantum region, usually based on density functional theory (DFT). However, QM/MM approaches are computationally very expensive. Here we introduce a neural network (NN) based hybrid approach as an efficient alternative. Instead of costly QM calculations during MD simulations, atomistic NNs learn the relationship between molecular conformations and corresponding energies based on DFT reference data. The NN evaluation can be performed at a fraction of the computational time but with comparable accuracies. In particular, the NNs are trained on the interaction energies of the metal, the difference in QM energy with and without the metal present. The resulting energies are representative of the metal-ligand interactions, as well as the influence of the metal on the ligand-ligand interactions. The remaining interactions of the system as well as long-range metal interactions are treated classically. We implemented this mixed NN/MM approach using existing QM/MM features in the GROMOS software for biomolecular simulations. Besides, we started to train NNs on small coordination complexes and performed NN/MM-MD simulations for proof of concept of our implementation. Preliminary results of our approach will be presented.

2021-04-19 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #531 Interpretation of Solution Scattering Data in Light and Heavy Water

Presenting author: Johanna-Barbara Linse Saarland University, Department of Theoretical Physics, Computational Biophysics Group, Saarbrücken, Germany Co-author(s): Jakub Macošek, Bernd Simon, Frank Gabel, Janosch Hennig, Jochen Hub

Atomistic ensembles are important in many areas of biology but are difficult to determine if the ensembles are disordered. By combining small-angle scattering (SAS) and molecular dynamics (MD) we are now able to determine such atomistic ensembles. SAS may investigate biomolecules in a near-native environment, providing scattering curves I(q), but it is not appropriate to explain the scattering curve with only one structural model, obtained with experimental methods like NMR and X-ray crystallography, because proteins are highly dynamic in solutions. This is especially true for is flexible proteins. In such cases computational methods are needed, such as MD simulations. In various biophysical experiments, for example small-angle neutron scattering (SANS), heavy water or deuterium oxide can be used as a solvent. In order to model such experiments with MD simulations, pair potentials for heavy water are required that reproduce the known physicochemical differences relative to light water. We present an atomistic ensemble of a disordered Protein-RNA complex from SAXS and MD and three effective pair potentials for heavy water (SPC/E-HW, TIP3P-HW, and TIP4P/2005-HW). Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #642 The Dynamics and Membrane Interactions of Murine Guanylate Binding Proteins

Presenting author: Jennifer Loschwitz Heinrich Heine University Düsseldorf, Department of Theoretical Chemistry and Computer Chemistry, Düsseldorf, Germany & Institute of Biological Information Processing: Structural Biochemistry, Forschungszentrum Jülich, Germany Co-author(s): Wibke Schumann, Birgit Strodel

Upon the infection by pathogens, the host immune reaction activates interferons, which in turn regulate the expression of many other proteins, such as the guanylate binding proteins (GBPs, ~65 kDa). Some of the murine GBPs (mGBPs), which belong to the superfamily of dynamin-related large GTPases, are highly upregulated after Toxoplasma gondii infection. It was demonstrated that the mGBPs can form hetero- and homo-multimers, which destabilize the membrane of the parasitophorous vacuole membrane (PVM). To understand the physical basis of how the mGBPs bind to and destroy the PVM, we performed a multitude of ordinary and enhanced molecular dynamics (MD) simulations on the μs timescale. We focus our studies on mGBP2 and mGBP7 as they are in parallel investigated by our CRC-1208 coll-aboration partners (Prof. Klaus Pfeffer and co-workers) using experiments. A key difference between these two proteins is that mGBP2 undergoes post-translational modification resulting in a geranylgeranyl (GG) lipid anchor, whereas mGBP7 exhibits 49 additional C- terminal residues (CT tail) with a certain propensity for a transmembrane helix [1]. Hamiltonian replica exchange MD simulations of the mGBPs in different states revealed that in solution the middle and effector domain undergo large-scale motions of up to 70 Å, which are not hugely affected by GTP binding and the GG anchor [2]. This characteristic hinge motion was also observed for human GBP1, which is a homologue of mGBP2 [3]. Also upon homo-dimerization, the dynamics of mGBP2 is largely unchanged apart from an overall reduction of the protein flexibility. In order to unravel the lipid- membrane binding of mGBP2/7, we switched to the coarse-grained (CG) level. We elucidated the membrane-binding process of both proteins using a membrane composition that was experimentally determined to be needed for mGBP2/7 to associate with membranes. Our major observations are that i) mGBP2 has a higher membrane affinity than mGBP7; ii) mGBP2 always inserts into the membrane via its GG anchor, while mGBP7 predominately employs its CT tail for this purpose. Despite mGBP2/7 being rather flexible in their membrane-bound states, the proteins have only minor effects on the membrane properties, suggesting that mGBP2/7 multimers are required for causing damage to the PVM as observed in experiments. Therefore, the next step will be to simulate the membrane binding of mGBP2 and mGBP7 dimers.

[1] L. Legewie, J. Loschwitz, N. Steffens, M. Prescher, X. Wang, S.H.J. Smits, L. Schmitt, B. Strodel, D. Degrandi, K. Pfeffer, Biochemical and structural characterization of murine GBP7, a guanylate binding protein with an elongated C-terminal tail, Biochem. J. 476, 3161-3182 (2019) [2] J. Loschwitz, X. Wang, B. Strodel, Conformational dynamic and membrane interactions of murine guanylate binding protein 2: A large-scale molecular dynamics simulation study, Frontiers Mol. BioSci., in preparation (2021) [3] B. Barz, J. Loschwitz, B. Strodel, Large-scale, dynamin-like motions of the human guanylate binding protein 1 revealed by multi-resolution simulations, PLOS Comp. Biol., 15, e1007193 (2019) Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #100 Probing the Transition Dipole Moment of Proteins in Amide I and II Regions by FTIR and MD Simulations

Presenting author: Nicole Luchetti University of Rome Tor Vergata, Department of Physics, Biophysics Group, Rome, Italy Co-author(s): Alessandro Nucara, Velia Minicozzi, Alessandra Filabozzi, Almerinda Di Venere, Marina Carbonaro

Linear Fourier Transform Infra-Red spectroscopy (FTIR) is a widely accepted method for protein investigation, being highly sensitive to the secondary and tertiary structures of complex polypeptides. Likewise, Molecular Dynamics (MD) simulations may be really helpful in the interpretation of experimental data, as they provide microscopic information on what it is observed at the macroscopic level. FTIR spectra of eight selected proteins in H2O solution were collected and analyzed to measure the molar extinction coefficient of the amide I and amide II absorption bands. The Transition Dipole Moment (TDM) strength was also measured by FTIR spectra and values obtained in alpha-helix rich proteins are compared with those observed in beta-sheet rich proteins. We found that TDM strength of the amide I vibration depends on the protein folding, unlike that of the amide II mode. MD simulations of the eight proteins were performed in the NPT ensemble and the trajectories were used both to evaluate protein secondary structures and to calculate vibrational spectra from normal mode analysis. Experimental and computational data are in very good agreement and suggest that the C=O bond vibration strength of proteins with a majority of beta-secondary structures is increased by a factor almost 3 compared to that in alpha-helices rich proteins. We’re also trying to study vibrational spectrum between 1000-1800 cm-1 of four small peptides using AIMD and DFT. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #599 QM/MM Metadynamics Uncovers the Mechanism of Long-Range Proton Transer in a Bacterial Proton Pump

Presenting author: Denis Maag Karlsruhe Institute of Technology (KIT), Institute of Physical Chemistry, Department of Theoretical Chemical Biology, Karlsruhe, Germany Co-author(s): Thilo Mast, Marcus Elstner, Qiang Cui, Tomáš Kubař

Extensive classical and QM/MM molecular dynamics simulations are used to establish the structural features of the O state in bacteriorhodopsin and its conversion back to the bR ground state. The computed free energy surface is consistent with available experimental data for the kinetics and thermodynamics of the O to bR transition. The simulation results highlight the importance of the proton release group (PRG, consisting of Glu194/204) and the conserved arginine 82 in modulating the hydration level of the protein cavity. In particular, in the O state, deprotonation of the PRG and downward rotation of Arg82 lead to elevated hydration level and a continuous water network that connects the PRG to the protonated Asp85. Proton exchange through this water network is shown by ~0.1 µs semiempirical QM/MM free energy simulations to occur through the generation and propagation of a proton hole, which is relayed by Asp212 and stabilized by Arg82. This mechanism provides an explanation for the observation that the D85S mutant of bacteriorhodopsin pumps chloride ions. The electrostatics-hydration coupling mechanism and the involvement of all titration states of water are likely applicable to many biomolecules involved in bioenergetic transduction. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #417 Molecular Docking, Molecular Dynamics, and Free Energy Calculations for Identification of New Drugs Against Biofilm Formation in P. aeruginosa

Presenting author: Rita Magalhães Faculty of Medicine, University of Porto, Department of Chemistry and Biochemistry, Porto, Portugal & BioSIM@UCIBIO/REQUIMTE Co-author(s): Tatiana F. Vieira, André Melo, Sérgio F. Sousa

Biofilms are highly organized communities of bacteria attached that show differences in gene expression when compared with similar free-flowing cells. Furthermore, they are highly resistant to antibiotics and host immune response and affect both human tissues and medical devices. P.aeruginosa is a highly pathogenic biofilm forming gram negative bacteria. The development of potent inhibitors against its mechanisms of biofilm formation is a promising therapeutic strategy to combat P.a related infection. Quorum-sensing, the intercellular communication in bacteria, is one of the main mechanisms leading to biofilm formation. In P.aeruginosa, the LasI/LasR system involves the binding of molecule to the receptor LasR, resulting in changes in gene expression that lead to biofilm development. The identification of potent LasR inhibitors that disrupt the QS pathway and largely decrease biofilm formation is urgent. This work reports on the optimization of a molecular docking and virtual screening protocol for the identification of inhibitors against LasR. Autodock4, Vina, LeDock and all four GOLD scoring functions were used in re and cross-docking studies. Large scale virtual screening on several databases (Chemoteca, TimTec, Chimioteca, FDA-Approved Drugs) was performed. The results were treated and filtered with datawarrior. The most promising molecules were subjected to Molecular Dynamics experiments with AMBER software to confirm their binding mode and estimate their affinity towards LasR through MM/GBSA calculations. The identified molecules can now be tested experimentally for their inhibition against LasR. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #779 Development of a Novel Computational Protocol for the Identification of Membrane PAINS

Presenting author: Pedro Rafael Magalhães Biosystems and Integrative Sciences Institute, FCUL, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Pedro Reis, Diogo Vila Viçosa, Miguel Machuqueiro, Bruno L. Victor

Pan-assay interference compounds (PAINS) are promiscuous molecules with apparent bioactivity that can interfere with the result of biological assays. These compounds are often mistakenly flagged as positive hits [1], acting as burden agents in drug screening processes. There are several categories of PAINS, but an especially problematic and underestimated category are the so-called membrane PAINS [2]. These compounds interact directly and nonspecifically with lipid membranes, promoting changes in their biophysical properties and ultimately affecting the function of mechanosensitive membrane proteins. Despite developed efforts, the identification of these compounds in initial compound screening phases of drug discovery is still very imprecise. We will describe a new computational protocol to identify and characterize membrane PAINS. This protocol is based on an already validated method [2], featuring atomic detail potential of mean force (PMF) calculations using umbrella sampling (US) techniques. These calculations allow the estimation of the perturbing effect of these compounds on membrane permeability and stability. Our validation set comprises molecules with reported minor, mild and major membrane PAINS activity [2,3]. Since one of the main concerns limiting the accuracy of these calculations is related with long equilibration times and insufficient sampling in each US window, we will also show new advances to the initial protocol based on longer simulation times and the use of enhanced sampling methods.

[1] Baell, J.B. et al. (2010) JMC 53(7):2719 doi.org/10.1021/jm901137j [2] Ingólfsson, H.I. et al. (2014) ACSCB 9(8):1788 doi.org/10.1021/cb500086e [3] Jesus, A.R. et al. (2017) JMC 60(2), 568-579 doi.org/10.1021/acs.jmedchem.6b01134 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #176 The Effect of Radius on the Nanoparticle-Protein Corona

Presenting author: Piercarlo Magliano University of Turin, Department of Chemistry, Turin, Italy Co-author(s):

Placing a nanoparticle (NP) in a biological fluid, causes the adsorption of biomolecules to the surface of the NP, called “protein corona”. The proteins are adsorbed fast by the NP via a mechanism of competitive adsorption between biomolecules. To study the complex dynamics of the corona formation we resort to GPUs simulations of a coarse-grained model that can account for the large number of particles that surround the NP. It has been shown that the model, once calibrated with experimental data, is able to reproduce and predict the corona long time composition. Furthermore, thanks to three-body interactions the model reproduces the multilayer formation of the corona. Here we consider the model in the case of a model solution made of three proteins, Human Serum Albumin (HSA), Transferrin (Tf) and Fibrinogen (Fibr), competing to adsorb onto a silica NP and focus on how the corona composition depends on the NP’s radius, ranging from 10 to 50 nm. We find the radius of the NP has a substantial effect on its surface coverage and the corona composition. These results are relevant for possible applications of nanoparticles in nanomedicine and theranostic. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #628 Let's Build a Software Ecosystem for Molecular Dynamics

Presenting author: Dibyajyoti Maity Indian Institute of Science, Bengaluru, Department of Computational and Data Sciences, Biomolecular Computation Lab, Bengaluru, India & Indian Institute of Science, Bengaluru, IISc Mathematics Initiative Co-author(s):

Development in molecular dynamics (MD) is directed towards improving the performance, simulating increasingly larger macromolecular assemblies, or incorporating machine learning into MD simulations. While these are essential, little effort has been put into improving the user experience and making MD accessible to researchers not directly involved in macromolecular simulations. Many issues are faced when performing MD simulations, which can be solved by better design choices for MD packages. For example, using PDB files to provide macromolecular coordinates is limited to 26 chains (A-Z for chain labels), easily solved by accepting input structure in PDBx/mmCIF, the official format of the Protein Data Bank (PDB). Another issue is the incompatibility of forcefield between various MD programs; A force field created for one MD program is challenging to incorporate into another. Moreover, each MD program uses its unique output format, which increases the difficulty of creating analysis tools for MD trajectories. Due to independent development, a desirable feature in one program is unavailable in another and vice versa. For example, VMD is excellent for visualizing MD trajectories but does not have the intuitive sequence viewer that PyMOL has. To make a presentation, 95% of people use Microsoft PowerPoint; it is so good that PowerPoint has become synonymous with the word 'presentation'. It would be wonderful if the development community could collaborate to build a software ecosystem for MD simulations—The PowerPoint of MD simulations. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #834 Structure-based Multiscale Modeling of Photosynthetic Antenna Complexes

Presenting author: Sayan Maity Jacobs University Bremen, Department of Physics & Earth Sciences, Computational Physics and Biophysics Group, Bremen, Germany Co-author(s): Ulrich Kleinekathöfer

As the first step of photosynthesis takes place in light-harvesting antenna complexes, these pigment-protein complexes have raised considerable interest in the last decades. Recently the pH-dependent photoprotective mechanism in the antenna complexes of higher plants have been in the focus of several studies. In order to model the excitation energy transfer in light-harvesting complexes of bacteria and plants, the so-called “spectral density” is the key input parameter. However, spectral densities determined from multiscale methods based on classical molecular dynamics simulation followed by excitation energy calculations often suffer from the so-called “geometry-mismatch” problem combined with a poor description of the vibrational dynamics. To alleviate these problems, we have recently established a scheme in which the self-consistent-charge Density-Functional based Tight-Binding method is applied in in a QM/MM framework in order to perform the ground state Born-Oppenheimer molecular dynamics simulations of the (bacterio)chlorophyll molecules. Subsequently, long-range corrected time-dependent Density-Functional based Tight-Binding calculations have been employed also in a QM/MM setting to determine the fluctuations of the excitation energy along those QM/MM MD trajectories. This technique eliminates the geometry mismatch problem, and the obtained spectral densities show a remarkable agreement with the experimental counterparts. The accuracy, robustness and reliability of our multiscale method has been validated for various antenna complexes of bacteria and plants. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #817 Role of Water in Catalytic Mechanism of ATP Synthase

Presenting author: Antoni Marciniak Gdansk University of Technology, Facutly of Chemistry, Department of Physical Chemistry, Computational Molecular Biophysics Group, Gdansk, Poland Co-author(s): Jacek Czub

ATP synthase is a transmembrane enzyme, embedded in the inner mitochondrial membrane. Because it uses the proton gradient created by the electron transport chain - complexes I to IV - it is sometimes called "complex V". It is composed of two subcomplexes: hydrophilic part F1, and hydrophobic Fo. F1 is directly responsible for the ATP synthesis, whereas Fo converts the energy accumulated in the proton gradient to the rotation of its centerpiece called the c- ring. The rotation empowers the F1 conformational changes, but the details about F1-Fo coupling are not clear. C-ring is a circular oligomer made up of c subunits, each presenting acidic aminoacid outside. It has been long known that these amino acids serve as proton carriers which protons reach by the separated entrance and exit. Protons reach the entrance from the perimitochondrial space, protonate acidic carrier, rotate almost 360 degrees on the c-ring to leave for the mitochondrial matrix through the exit. Most of the details about the exit and entrance remain unknown, although recent Cryo-EM structures shed some light on its nature. It has been proposed that there are distinct water half-channels through which protons can reach the c-ring. In this work, we use molecular dynamics to confirm the existence of these half-channels. We examine how mutations of conserved amino acids affect their water densities and ability to form Grotthus proton wires. Finally, we compute the water flow between both of them to verify their separation. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #767 Screening of Aquaporin-5 Modulators with Anticancer Properties

Presenting author: Jéssica Marques Faculty of Sciences, University of Lisbon, BioISI - Biosystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Bruno L. Victor, Graça Soveral

Aquaporins (AQPs) are membrane channels which facilitate the flow of water and other molecules (glycerol) across biological membranes. They play a crucial role in cell homeostasis and volume regulation, being widely distributed along the organisms. In mammals, there are 3 subsets of AQPs that are divided according to their permeability profiles and sequence homology. Due to its biological importance, deregulations of AQPs activity and/or expression can induce changes in the cell homeostasis, causing health problems and diseases, such as carcinogenesis. The relationship between AQPs and cancer has been thoroughly studied and, as a result, it was concluded that AQPs are overexpressed in a wide variety of tumor cell types. Moreover, the discovery of efficient and selective human AQPs (hAQPs) modulators has been seen as a potential future cancer treatment/therapy. To date, the inhibitors reported are non- selective and mostly toxic, which make them impossible to be applied in in vivo studies and clinical trials.. Therefore, the main goal of this project is the development and application of a new workflow, combining different computational approaches to identify new and innovative hAQP5 modulators. The most promising compounds identified with this approach will be purchased and experimentally validated using stopped-flow technology. In this poster presentation, we will show the preliminary results we have already gathered.

[1] Madeira, A., & Brito, M. A. (2016). Aquaporin-5 : from structure to function and dysfunction in cancer. 1623–1640. https://doi.org/10.1007/s00018-016-2142-0 [2] Huber, V. J., Tsujita, M., & Nakada, T. (2012). Molecular Aspects of Medicine Aquaporins in drug discovery and pharmacotherapy. Molecular Aspects of Medicine, 33(5–6), 691–703. https://doi.org/10.1016/j.mam.2012.01.002 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #868 Develop a Simple and Fast MM-PBSA Method Based on Delphi to Study Protein/Protein and Protein/Membrane Binding Affinities

Presenting author: João Nuno Marques Vitorino Faculty of Sciences, University of Lisbon, BioISI - Biosystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Pedro Reis, Miguel Machuqueiro

Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) has become one of the most widely used methods for estimating interaction free energies of biomolecular interactions, (such as in protein-ligand complexes), for its good compromise of computational cost, speed and precision. Combined with molecular dynamics (MD) simulations, this method constitutes an extremely useful tool to understand biomolecular associations in detail, and decompose the total binding energy in a series of components. Here, we present a new implementation of this method, designed to be fully compatible with the GROMOS54a7 force field (and potentially others), to study protein-protein interactions, as well as, in a near future, handle pKa/protonation changes, and protein-membrane interactions. Following a similar rationale from the previously developed tool for for GROMACS, g_mmpbsa [1], our method is able to correctly reproduce the molecular mechanics energy component in vacuum and the nonpolar solvation energy with a solvent accessible surface area (SASA-Only) model, for the β2 Microglobulin (B2M) dimer, which was used as a test system. To calculate the polar solvation energy component of the binding energy, our method uses DelPhi4Py, a DelPhi wrapper, as a PB solver, which has previously been validated using GROMOS force fields [2], in contrast to APBS, which is used in the g_mmpbsa implementation. Currently, a validation study is underway for which we will show our preliminary results.

[1] Kumari R, Kumar R, Open Source Drug Discovery Consortium, Lynn A. g_mmpbsa--a GROMACS tool for high-throughput MM-PBSA calculations. J Chem Inf Model. 2014;54: 1951–1962. [2] Reis PBPS, Vila-Viçosa D, Rocchia W, Machuqueiro M. PypKa: A flexible Python module for Poisson-Boltzmann-based pKa calculations. J Chem Inf Model. 2020;60: 4442–4448. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #888 Mechanotransduction in the Focal Adhesion Pseudokinase ILK

Presenting author: Isabel Martin Heidelberg Institute for Theoretical Studies (HITS), Molecular Biomechanics, Heidelberg, Germany Co-author(s): Michele Nava, Sara Wickström, Frauke Gräter

Cell migration is vital for organism maintenance and is regulated by an interplay of mechanical forces and biochemical signaling. The major integration platform are the focal adhesions, the constituent proteins of which are directly subjected to mechanical force. The intracellular adaptor integrin-linked kinase (ILK) in complex with α-parvin provides a docking scaffold of focal adhesions coordinating the integrin-actin linkage. Although long debated about, ILK is now classified as a pseudokinase which retained its ability to bind ATP. A mechanosensing function of ILK and a potential role of ATP therein remain elusive. Here, we report extensive molecular dynamics simulations of ILK in conjunction with cellular experiments. ATP mechanically stabilizes the pseudokinase which proposes a role for ATP as an obligatory binding partner for structural and mechanical integrity. The transmission of internal forces from ATP proceeds towards α-parvin over two previously unrecognized saltbridges. Mutations of the saltbridge forming residues lead to loss of α-parvin binding, increase in focal adhesion disassembly rate and a lower force generation of the cell on the matrix in vivo. This proposes an unprecedented role of ATP as an allosteric regulator and mechanical stabilizer of the ILK: α-parvin interaction. Our results suggest ILK as a kinase in which ATP lost its biochemical function but instead acquired a mechanical role within the mechanotransduction of the focal adhesions. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #175 Kinetics of Interaction between Nanoparticle and Protein Corona

Presenting author: Albert Martínez Serra University of Barcelona, Department of Statistical Physics of Complex Matter, Barcelona, Spain & Institut de Nanociència i Nanotecnología de la Universitat de Barcelona Co-author(s): Piercarlo Magliano

When we settle a nanoparticle in a biological fuid, the existing biomolecules adsorp to its surface forming the known protein-corona. Proteins adsorb fast to the nanoparticle through competitive adsorption between them. To study the dynamics of the corona formation we perform GPUs simulations of a coarse-grained model which works with CUDA which considers the large number of particles that surround the nanoparticle. It has been shown that the model is able to reproduce and predict the corona composition. Even more, due to three-body interactions the model reproduces the multilayer formation of the corona. In basic models we consider the three main proteins of plasma, i.e. Human Serum Albumin (HSA), Transferrin (Tf) and Fibrinogen (Fibr), which compete in order to adsorb onto a silica nanoparticle. It can be found that a set of parameters such as the radius of the nanoparticle have a substantial effect on its surface coverage and the corona composition. These results are relevant for possible applications of nanoparticles in nanomedicine and theranostics. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #811 Full-Atom Model of the Activated Toll-Like Receptor 4 Dimer in a Membrane Environment

Presenting author: Alejandra Matamoros Recio Center for Biological Research Margarita Salas, CSIC, Department of Structural and Chemical Biology, Computational Chemical Biology, Madrid, Spain Co-author(s): Juan Felipe Franco-Gonzalez, Sonsoles Martin-Santamaria

Toll-like receptors (TLRs) are pattern recognition receptors involved in innate immunity. In particular, TLR4 binds to lipopolysaccharides (LPS), a membrane constituent of Gram-negative bacteria, and together with MD-2 protein, forms a heterodimeric complex which leads to the activation of the innate immune system response. TLR4 activation has been associated with certain autoimmune diseases, noninfectious inflammatory disorders, and neuropathic pain. Therefore, TLR4 has risen as a promising therapeutic target, and design of TLR4 modulating drugs constitutes a highly relevant and active research area. Specific molecular features of extracellular, transmembrane, and cytoplasmic domains of TLR4 are crucial for coordinating the complex innate immune signaling pathway. Although X-ray, NMR, and biological structural data are currently available for the independent TLR4 domains, the structure fragments only provide a partial view, because full-length proteins are flexible entities and dynamics play a key role in their functionality. Therefore, many structural and dynamical features of the TLR4 mode of action remain largely unknown. Computational studies of the different independent domains composing the TLR4 were undertaken, using ab-initio calculations, homology modeling, protein-protein docking, all-atom molecular dynamics simulations, and thermodynamics calculations, to understand the differential domain organization of TLR4 in a wide range of membrane-aqueous environments, including liquid-disorder and liquid-order membrane models, to account for the TLR4 recruitment in lipid-rafts after activation. From the information gathered from our independent TLR4 domains studies, we finally modeled, by all-atom MD simulations, the structural assembly of plausible full-length TLR4 models embedded into a realistic plasma membrane, accounting for the active (agonist) state of the TLR4. These observations unveil relevant molecular aspects involved in the mechanism of receptor activation, and adaptor recruitment in the innate immune pathways, and will promote the discovery of new TLR4 modulators and probes. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #572 Systematic in silico Investigation of Amyloid-Beta Oligomer Models Highlight the Role of Lipid-Stabilized Pores in Membrane Permeabilization

Presenting author: Dirk Matthes Max Planck Institute for Biophysical Chemistry, Computational Biomolecular Dynamics Group, Göttingen, Germany Co-author(s): Bert L. de Groot

Oligomeric aggregates of the Amyloid-beta (Ab) peptide are regarded as pivotal agents and primary cause of cytotoxicity related to membrane damage in Alzheimer's disease. However, the broad and heterogeneous ensemble of non-fibrillar and pore-forming oligomers has not been amenable to direct structural characterization. NMR and MS derived structural data of Ab(1-42) tetramers and octamers in membrane mimicking environment were recently made available for the first time by Ciudad et al. Membrane inserted Abeta oligomers were reported to permeabilize lipid bilayers by a mechanism termed edge conductivity, where pores would form along exposed, hydrophilic edge strands of the beta-sheet core of the aggregates.Yet, there are remaining questions on the prerequisites and details of the pore formation process in the presence of membrane inserted beta-sheet oligomers. The novel structures allow us to probe specific hypotheses regarding the principal relationship between the oligomer structure and membrane permeabiliziation. Here we used Ab(1-42) oligomers as a putative model system to study lipid-stabilized pores with fully atomistic MD simulations in POPC bilayers.Based on the same template, we investigated various aggregate structures and sizes. We found that the formation of edge conductivity pores is strongly dependent on the insertion depth of hydrophilic residues H13 to K16 and thus on subtle differences in the overall stability, orientation and conformation of the exposed transmembrane beta-strand domain. Most notably, only beta-sandwich structures with parallel sheet pairs and exposed, hydrophilic strands are able to maintain continuous, lipid-stabilized pores and facilitate ion permeation. Backbone carbonyl oxygen and polar side chain atoms from these edge strands were found to contribute directly to the coordination sphere of the permeating ions in the center most part of the bilayer. Simulations of oligomers with point mutations either destabilizing or altering the hydrophilic character of the beta-sandwich edge structure, furthermore highlight its role as key structural element that defines the properties of edge conductivity pores. Interestingly, oligomeric aggregates which were only composed of transmembrane beta-strands from the C-terminal part of Ab and therefore lacked hydrophilic edge strands, were found to relax towards stable, barrel-like states with a significantly reduced ability to permeabilize the lipid bilayer. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #643 Conductance Mechanism in a K+ Channel with a Mutant Selectivity Filter

Presenting author: Andrei Mironenko Max Planck Institute for Biophysical chemistry, Computational Biomolecular Dynamics Group, Göttingen, Germany Co-author(s): Wojciech Kopec, Bert L. de Groot

K+ channels play a crucial role in the life of cells: ionic currents through K+ channels establish the membrane voltage in all cells and terminate action potentials in excitable cells. K+ channels have a conserved functional core - selectivity filter (SF) - that consists of successive K+ binding sites lined with carbonyl groups and serves as a primary regulator of K+ channels activity. K+ channels are characterized by high conductivity coupled with high selectivity. Despite decades of research, the exact microscopic events leading to such highly efficient ion permeation are still not known. Based on molecular dynamics simulations of various potassium channels (such as KcsA, MthK, and others), we have proposed a ‘direct knock-on’ ion permeation mechanism, where water-free permeation and formation of direct ion-ion contacts in the SF provide high K+ conductance, while being intrinsically ion selective. This direct knock-on mechanism was confirmed by several experimental observations. Recently, the ‘direct knock-on’ model has been challenged by new experimental data on SF mutants of the KcsA K+ channel that suggested co-permeation of water, while the high ion selectivity was conserved. Here, we use molecular dynamics simulations to study the permeation mechanism of these SF mutants. We show that the SF mutants undergo conformational changes that are incompatible with the permeation mechanism of wild-type channels. Our results are in good agreement with experimental data, thus rendering it non-contradictory with the ‘direct knock- on’ model. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #902 The Anti-HCV, Sofosbuvir, Versus the Anti-EBOV Remdesivir Against SARS- CoV-2 RNA Dependent RNA Polymerase in silico

Presenting author: Eman Bellah Mohamed Azzam Helwan, Department of Biomedical Physics, Giza, Egypt Co-author(s): Eman B. Azzam, Medhat W. Shafaa

Coronavirus diseases 2019 (COVID-19) are seriously affecting human health all over the world. Nucleotide inhibitors have promising results in terms of its efficacy against different viral polymerases. In this study, detailed molecular docking and dynamics simulations are used to evaluate the binding affinity of a clinically approved drug, sofosbuvir, with the solved structure of the viral protein RNA-dependent RNA polymerase (RdRp) and compare it to the clinically approved drug, Remdesivir. These drugs are docked onto the three-dimensional structure of the nsp12 protein of SARS-CoV-2, which controls the polymerization process. Hence, it is considered one of the primary therapeutic targets for coronaviruses. Sofosbuvir is a drug that is currently used for HCV treatment; therefore, HCV RdRp is used as a positive control protein target. The protein dynamics are simulated for 100 ns, while the binding is tested during different dynamics states of the SARS-CoV-2 RdRp. Additionally, the drug-protein complexes are further simulated for 20 ns to explore the binding mechanism. The interaction of SARS- CoV-2 RdRp as a target with the active form of sofosbuvir as a ligand demonstrates binding effectiveness. One of the FDA-approved antiviral drugs, such as sofosbuvir, can help us in this mission, aiming to limit the danger of COVID-19. Sofosbuvir was found to bind nsp12 with comparable binding energies to that of Remdesivir, which has been reported for its potential against COVID-19 RdRp and is currently approved by the FDA. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #624 Analysis of Secondary Structure Stability of Designed Peptides with Molecular Simulations

Presenting author: Korana Mudrovcic Heinrich Heine University Düsseldorf, Institute for Pharmaceutical and Medicinal Chemistry, Düsseldorf, Germany Co-author(s): Neha Verma, Annabelle Friedrich, Björn Stork, Holger Gohlke

Autophagy is a cell’s mechanism to eliminate damaged or long-lived proteins and organelles and is currently being explored for treating cancer, with clinical trials of autophagy inhibitors showing encouraging results.[1,2,3,4] A central protein complex involved in autophagy initiation is a tetrameric ULK1 protein complex consisting of ULK1, ATG101, ATG13, and RB1CC1 subunits. Wallot-Hieke et al. showed that by inhibiting the interaction between ATG13 and ATG101, the entire process of autophagy can be inhibited.[5] To probe whether the inhibition of the ATG13-ATG101 interaction could eventually be accomplished with small molecules, three α-helical peptides of 13-18 residues length were excised from the region of ATG13 protein where the most important interaction hotspots were predicted to be. However, since α-helical structure in peptides of this length may be hard to preserve, we decided to test the secondary structure stability with molecular simulations prior to in vitro experiments.[6] Since the 14SB AMBER force field in explicit solvent has been suggested to reproduce the thermodynamics of helix formation well, this force field was chosen to produce 10 replicas of 5 μs long molecular dynamics simulations in explicit solvent for the three excised peptides.[7] We additionally designed another two peptides similar to the originally excised ones, but including a “staple” consisting of two 2-(4'-pentenyl)alanine residues making a covalent bond to each other, to keep the α-helical structure stable. These “stapled” peptides were simulated with the same protocol to see whether the secondary structure stability is improved by the addition of the staple. Since the parameters for this non-standard residue were not available a priori, partial charges for the 2-(4'-pentenyl)alanine residue were derived with the RESP procedure, and the force field parameters were taken over from GAFF small molecule force field. The results showed that while excised peptides did show helicality, the helical content and the stability of the α-helix was greatly improved in the stapled peptides.

[1] White, Eileen et al. Clinical Cancer Research, vol 21, no. 22, 2015, pp. 5037-5046 [2] Amaravadi, Ravi et al. Genes & Development, vol 30, no. 17, 2016, pp. 1913-1930 [3] Santana-Codina, Naiara et al. Annual Review Of Cancer Biology, vol 1, no. 1, 2017, pp. 19- 39 [4] Mulcahy Levy, Jean M., and Andrew Thorburn. Cell Death & Differentiation, vol 27, no. 3, 2019, pp. 843-857 [5] Wallot-Hieke, Nora et al. Autophagy, vol 14, no. 5, 2018, pp. 743-763 [6] Scholtz JM, Baldwin RL (1992) Annu Rev Biophys Biomol Struct 21:95–118. [7] Sun, Zhaoxi, and Xiaohui Wang. Journal Of Theoretical And Computational Chemistry, vol 18, no. 03, 2019, p. 1950015. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #821 How are Electrons Transferred from Cytochrome P450 Reductase to Cytochrome P450 Enzymes? Towards a Structural and Dynamic Understanding

Presenting author: Goutam Mukherjee Heidelberg University and Heidelberg Institute for Theoretical Studies HITS gGmbH, Zentrum für Molekulare Biologie der Universität Heidelberg (ZMBH), Heidelberg, Germany Co-author(s): Prajwal P. Nandekar, Ghulam Mustafa, Rebecca C. Wade

Cytochrome P450 (CYP) is the cardinal xenobiotic-metabolizing superfamily of enzymes. CYPs require two electrons for their catalytic cycle. For microsomal CYPs, these electrons are transferred by their redox partner, NADPH-cytochrome P450 oxidoreductase (CPR) to the CYP active site heme cofactor. CYP and CPR are membrane-anchored proteins and the association of the two proteins to form a complex, CYP-CPR, is driven by electrostatic interactions. However, so far, no crystal structure has been solved of their full length complex. Here, we have developed a transferable multiresolution computational approach to build and simulate a full length CYP-CPR-membrane complex using Brownian dynamics and all-atom molecular dynamics simulations.1-2 Application of this approach yielded multiple arrangements of CPR around CYP1A1 that are electron transfer (ET) competent. The present study also provides atomic detail into ET routes and the determinants of ET rates, which agree well with available experimental data.2-3

[1] Mukherjee, G.; Nandekar, P. P.; Wade, R. C. An electron transfer competent structural ensemble of membrane-bound cytochrome P450 1A1 and cytochrome P450 oxidoreductase. Communications Biology, 2021, 4, 1-13. [2] Kenaan, C.; Zhang, H.; Shea, E. V; Hollenberg, P. F. Uncovering the Role of Hydrophobic Residues in Cytochrome P450- Cytochrome P450 Reductase Interactions. Biochemistry 2011, 50 (19), 3957– 3967. [3] Duggal, R.; Denisov, I. G.; Sligar, S. G. Cytochrome B5 Enhances Androgen Synthesis by Rapidly Reducing the CYP 17A1 Oxy-Complex in the Lyase Step. FEBS Lett. 2018, 592 (13), 2282–2288. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #855 MSMPathfinder: Finding Pathways of Markov State Models

Presenting author: Daniel Nagel University of Freiburg, Institute of Physics, Biomolecular Dynamics Group, Freiburg im Breisgau, Germany Co-author(s): Anna Weber, Georg Diez, Gerhard Stock

In numerous fields of research, the population dynamics of states is described in terms of a master equation or a Markov state model (MSM). Given Markovian dynamics, we can define a transition matrix Tij for a certain lagtime taulagwhich determines completely the time evolution of the system. Often we are interested in the pathways of the MSM, that lead from an initial to a final state. E.g., in protein folding these paths account for the mechanism the molecular reaction evolves. These paths naturally arise in a Markov chain Monte Carlo simulation, where we draw random numbers which determine the next step depending on the transition matrix Tij. The catch is the slow convergence. As a remedy, Vanden Eijnden and co-workers have proposed transition path theory. However, this method is designed to only give the most important pathways correctly. In systems of biological interest, e.g. protein folding, allostery, etc., many pathways may arise, and may also be important to understand the underlying mechanism. To cope with these problems, we suggest a new method–MSMPathfinder–which directly considers the path probabilities. In contrast to Markov chain Monte Carlo, it samples the path space more efficiently and gives a well-defined error. We demonstrate the performance and discuss the insights revealed by adopting the folding of villin headpiece. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #630 Vibrio Export Monitoring Peptide Structure Within and Outside of the Ribosome

Presenting author: Gabor Nagy Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Michal H. Kolář, John Kunkel, Sara M. Vaiana, Lars V. Bock, Helmut Grubmüller

The Vibrio export monitoring polypeptide (VemP) is mechano-sensitive peptide that allows Vibrio bacteria to switch between sodium and proton driven protein export and to survive in both in fresh- and seawater. VemP controls export channel gene expression through stalling the ribosome in the absence of forces exerted by active protein export channels. Cryo-electron microscopy (CryoEM) showed that the stalling mechanism involves a helix-loop-helix conformation that VemP adopts within the ribosomal exit tunnel. We investigated the secondary structure preferences of several VemP constructs to better understand the VemP stalling mechanism. Circular Dichroism spectroscopy showed that VemP in water is disordered, but adopts partially helical structures in more hydrophobic environments. Molecular dynamics (MD) simulations started from the CryoEM structure also highlight key interactions that stabilize the helical VemP stalling conformation in the ribosomal exit tunnel. These interactions involve ribonucleic acids in the vicinity of the peptidyl transferase center (PTC) as well as ribosomal proteins uL4 and uL22. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #261 Molecular Docking Study and Multivariate Statistical Approach of Natural Compounds Inhibition Effects on the SARS-CoV2 Spike Protein

Presenting author: Miroslava Nedyalkova University of Fribourg, Department of Chemistry, Fribourg, Switzerland Co-author(s):

Angiotensin-converting enzyme 2 (ACE2) (EC:3.4.17.23) is a transmembrane protein that is considered as a receptor for spike protein binding of novel coronavirus (SARS-CoV2). Since no specific medication is available to treat COVID-19, designing a new drug is important and essential. In this regard, in silico method plays an important role, as it is rapid and cost- effective compared to the trial and error methods using experimental studies. Natural products are available to combat coronavirus affected patients, in the present alarming situation. The study is based on 40 phytochemicals, which have been selected as small molecules in the molecular docking study of the spike protein of SARS-CoV2 (RBD) with its human receptor ACE2 molecule. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #882 Conformational Characterization of the NES-Binding Groove in CRM1

Presenting author: João Gonçalo Nunes Sequeira Faculty of Sciences, University of Lisbon, BioISI - Biosystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Miguel Machuqueiro

Proteins function depends greatly on its subcellular localization, since it determines the proteins access to binding partners and enzymes that catalyze post-translational modifications. The movement of molecules between the nucleoplasm and the cytoplasm is controlled by nuclear pore complexes, with the best studied export protein being the Chromosome Region Maintenance 1 (CRM1) that mediates nucleocytoplasmic transport of macromolecules, such as proteins and RNA [1]. CRM1-cargo binding commonly depends on a 10-15 residue-long, leucine rich, nuclear export signal, or NES, which binds to a hydrophobic cleft on the outer convex surface of CRM1 - the NES-binding groove. Tumor cells use this nuclear-cytoplasm transport system to evade anti-neoplastic mechanisms [2]. Several tumor suppressor proteins have been shown to be excluded from the cell nucleus and the overexpression of CRM1 is known to be oncogenic. There are a few CRM1 inhibitors known but their therapeutic value has been hindered by high toxicities due to a direct covalent bond to the target. Non-covalent and reversible inhibitors would be ideal chemotherapeutics, but none have been proposed yet. In this work, we aim at designing new non-covalent inhibitions of CRM1. These new compounds will target the NES-binding groove, preventing the association of CRM1 with its normal cargo. Since this NES pocket is relatively shallow, we propose that the X-ray structures available may not be representative of the conformations in solution. Therefore, it is important to study the conformational space of the NES binding groove at the molecular level, in order to help identify representative CRM1 conformations to be used in virtual screening campaigns. We performed several long MD simulations from a crystallographic structure of CRM1 (6TVO [3]) and did a complete structural characterization of the NES-binding groove to identify the larger conformational clusters and provide a reliable depiction of the protein structure in solution.

[1] Cautain B, Hill R, de Pedro N, Link W. Components and regulation of nuclear transport processes. FEBS J. 2015;282: 445–462 [2] Hill R, Cautain B, de Pedro N, Link W. Targeting nucleocytoplasmic transport in cancer therapy. Oncotarget. 2014;5: 11–28 [3] Shaikhqasem A, Dickmanns A, Neumann P, Ficner R. Characterization of Inhibition Reveals Distinctive Properties for Human and Saccharomyces cerevisiae CRM1. J Med Chem. 2020;63: 7545–7558 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #866 The Role of Electrostatics in the Mechanism of ATP/ADP Carrier Function: An in silico Study

Presenting author: Nuno Oliveira Faculty of Sciences, University of Lisbon, BioISI - Biosystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Miguel Machuqueiro

Electrostatic interactions are key participants in biomolecular processes, being the main driving force of molecular interactions [1]. However, accurately describing these forces is extremely challenging in both experimental and computational methods. We propose a computational protocol that couples Umbrella Sampling with Constant-pH Molecular Dynamics [2] in order to overcome the time-scale limitations of regular MD simulations and to allow protonation changes to all molecules in our simulations. This protocol was used to study the energetics and electrostatic interactions involved in the ATP/ADP carrier (AAC) transport mechanism. Here, the AAC binds and transports two highly negative charged molecules, hinting at the important role of electrostatics in this membrane transport process. Several computational studies have already identified the importance of electrostatics in this protein system [3], however, none have tackled the entirety of the transport processes and all lack the correct description of pH. In this work, we used US-CpHMD simulations at pH 7 for the import and export processes (from the mitochondria) of both substrates (ADP and ATP). The final results showed that these processes were energetically favourable, greatly influenced by the positive electrostatic funnel present on the AAC cavity. Furthermore, a clear selectivity for the import of ADP over ATP was verified, which can easily be correlated with a biological necessity, which resulted in evolutionary pressure. On the other hand, in the export process, no selectivity was observed, probably due to the lack of such evolutionary pressure.

[1] Zhang Z, Witham S, Alexov E. On the role of electrostatics in protein–protein interactions. Phys Biol. 2011;8: 035001. [2] Santos HAF, Vila-Viçosa D, Teixeira VH, Baptista AM, Machuqueiro M. Constant-pH MD Simulations of DMPA/DMPC Lipid Bilayers. J Chem Theory Comput. 2015;11: 5973–5979. [3] Bidon-Chanal A, Krammer E-M, Blot D, Pebay-Peyroula E, Chipot C, Ravaud S, et al. How Do Membrane Transporters Sense pH? The Case of the Mitochondrial ADP–ATP Carrier. J Phys Chem Lett. 2013;4: 3787–3791. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #904 AQP0-Cholesterol Interaction from Molecular Dynamics Simulations

Presenting author: Juan David Orjuela University of Los Andes, Department of Biomedical Engineering, Max-Planck Tandem Group in Computational Biophysics, Bogotá, Colombia Co-author(s): Po-Lin Chiu, Thomas Walz, Bert L. de Groot, Camilo Aponte-Santamaría

Studying lipid-protein interactions is fundamental to understand the complex behavior of biological membranes. In these systems, membrane proteins affect the organization of lipid bilayers and thus their mechanical properties, and vice-versa the local lipid environment alters membrane-protein function. Growing evidence supports the idea that lipid-protein interactions may modify not only the structure but also the dynamics of integral membrane proteins. The most abundant membrane protein in the eye lens is aquaporin-0 (AQP0), with reported roles in water conduction, cell-cell adhesion, and cell organization. Electron crystallography (EC) and molecular dynamics (MD) simulations have contributed to our understanding of lipid-protein interactions by providing high-resolution three-dimensional structural and dynamical data for diverse lipidic environments in a systematic manner. Recent EC experiments by Chiu et al. provided detailed structures for AQP0 tetramers in membrane mixtures of sphingolipid and cholesterol, which resemble more closely the natural environment of AQP0. With these structures, we performed MD simulations to monitor the positioning of cholesterol around AQP0 in a sphingolipid membrane and examined the effect cholesterol concentration has on the localization of this sterol molecule. Additional pulling simulations indicate a clear effect of cholesterol on stability and organization for groups of tetramers. We thereby expand our previous studies focused on phospholipids by also considering cholesterol, which potentially plays a key role in the higher-order organization of AQP0 tetramers in the lens membrane. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #746 Role of Tyr-39 for the Structural Features of α-Synuclein and for the Interaction with a Strong Modulator of Its Amyloid Assembly

Presenting author: Oscar Palomino Hernandez Forschungszentrum Jülich, Department of Computational Biomedicine (IAS-5/INM-9), Jülich, Germany & Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen, Co-author(s): Fiamma A. Buratti, Pamela S. Sacco, Giulia Rossetti, Paolo Carloni, Claudio O. Fernandez

Recent studies suggest that Tyr-39 might play a critical role for both the normal function and the pathological dysfunction of α-synuclein (αS), an intrinsically disordered protein involved in Parkinson’s disease. We perform here a comparative analysis between the structural features of human αS and its Y39A, Y39F, and Y39L variants. By the combined application of site-directed mutagenesis, biophysical techniques, and enhanced sampling molecular simulations, we show that removing aromatic functionality at position 39 of monomeric αS leads to protein variants populating more compact conformations, conserving its disordered nature and secondary structure propensities. Contrasting with the subtle changes induced by mutations on the protein structure, removing aromaticity at position 39 impacts strongly on the interaction of αS with the potent amyloid inhibitor phthalocyanine tetrasulfonate (PcTS). Our findings further support the role of Tyr-39 in forming essential inter and intramolecular contacts that might have important repercussions for the function and the dysfunction of αS. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #753 Molecular Dynamics Simulations of Glucose Binding Protein-Based Fluorescence Probe

Presenting author: Ziwei Pang Karlsruhe Institute of Technology (KIT), Institute of Physical Chemistry, Department of Theoretical Chemical Biology, Karlsruhe, Germany Co-author(s):

Fluorophores linked to the Glucose Galactose Binding protein (GGBP) are a promising class of glucose sensors for application in medical devices needed from diabetes patients. A lot of fluorophores at different positions in the protein were studied experimentally. In this work, we present the theoretical investigation of the wild-type protein as well as a triple mutant linked with the dye Badan. Stable molecular structures and the free energy of these conformations are studied by free molecular dynamics simulations as well as metadynamics simulations. We point out that consideration of the polarization of the glucose in the binding pocket is essential. The final free energies for the wild-type (9 kcal/mol) and the mutant (1 kcal/mol) are in agreement with the experiment. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #302 Study of the Molecular Aggregation of Muricatacin in Water by Means of Molecular Dynamics Simulations

Presenting author: José G. Parra Universidad de Carabobo, Department of Chemistry, Valencia, Venezuela & Universidad de Carabobo. Dpto. De Química. Lab. Simolquimex Co-author(s): Peter Iza, Mariangeles Salas

Muricatacin is a acetogenin derivative that is present in the seeds of Annona muricata. This molecule have presented an important antiproliferative activity towards several human tumour cell lines. Also, this specie has been used for the preparation of other natural product with biological activity. In addition, this molecule has amphiliphilic characteristics which can allow the distribution of the Muricatacin between aqueuos medium and the air/water interface. In function of this, we evaluated the molecular aggregation of Muricatacin in water by means of Molecular Dynamics (MD) simulations to explore the nature of the molecular interactions that drive the molecular aggregation of this molecule in aqueuos solution. In this investigation, MD simulations of the systems were performed with the GROMACS-2019.1 software. The Muricatacin and water molecules were described using the CHARMM and TIP3P force field, respectively. The shape of the micelle was evaluated as function of the Muricatacin concentration in aqueous medium. This molecule present amphiphilic properties with a high level of hydrophobic characteristics in water that produce in short time the molecular aggregation in aqueous solution.

Keywords: MD simulations, Muricatacin, Micelles, molecular aggregation. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #865 Computational Analysis of the Interactions Between the S100B Extracellular Chaperone and the Aβ Peptide

Presenting author: Filipe Eduardo Pequito Rodrigues Faculty of Sciences, University of Lisbon, BioISI - Biosystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Cláudio M. Gomes, Miguel Machuqueiro

Amyloid β peptides (Aβ) are associated with several neurodegenerative diseases, notoriously with Alzheimer’s disease (AD). In the AD brain, Aβ peptides are produced as a result of misprocessing of APP which leads to the production of variants with multiple lengths, including the highly amyloidogenic Aβ42 [1]. The latter aggregates extracellularly, forming the so-called amyloid plaques, which constitute one of AD’s landmarks. The formation of these aggregates, which are neurotoxic, leads to an inflammatory response releasing several inflammatory cytokines, among which is S100B [2]. S100B is a small homodimeric protein from the S100 protein family that binds four Ca2+ per dimer in EF-hands motifs and which also comprises two interfacial metal binding sites for Cu2+ and Zn2+ [2]. It was described to act as an extracellular chaperone counteracting Aβ42 aggregation in a Ca2+ dependent manner [2]. Binding of Ca2+ to S100B induces conformational changes which result in the exposure of a binding cleft within the dimer interface that is able to mediate protein:protein interactions. Experimental data from structural NMR experiments revealed that Aβ42 interacts with S100B through this region, involving Lys28 and Ile31 [2]. However, the atomic details of this interaction are not well known. The main goal of this work is to use computational techniques (molecular docking and MD simulations), guided by experimental evidence, to help elucidate the atomic details of the Aβ:S100B complex formation. Since the peptide is only partially folded in solution, it creates a significant challenge to capture its conformational space. However, with the help of all experimental evidence available, we were able to devise a protocol to direct both the conformational space of the peptide and the geometry of the final complex configurations. In this work, we also explored the hotspot interactions between Lys28 and several S100B residues, which were pivotal in stabilizing the complex. The results of several structural properties will also be presented.

[1] Coronel R, Bernabeu-Zornoza A, Palmer C, Muñiz-Moreno M, Zambrano A, Cano E, et al. Role of Amyloid Precursor Protein (APP) and Its Derivatives in the Biology and Cell Fate Specification of Neural Stem Cells. Mol Neurobiol. 2018;55: 7107–7117 [2] Cristóvão JS, Morris VK, Cardoso I, Leal SS, Martínez J, Botelho HM, et al. The neuronal S100B protein is a calcium-tuned suppressor of amyloid-β aggregation. Sci Adv. 2018;4: eaaq1702 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #596 mdciao: Analysis of Molecular Dynamics Simulations Using Residue Neighborhoods

Presenting author: Guillermo Pérez-Hernández Charité - Universitätsmedizin Berlin, Instiute for Medical Physics and Biophysics, Berlin, Germany Co-author(s): Peter W. Hildebrand

We present mdciao, an open-source command line tool and Python Application- Programmers-Interface (API) for easy, one-shot analysis of molecular simulation data. It uses a distance-cutoff to compute frequent neighbors, tracking the underlying interactions between residues. The added value to this simple computation comes from wrapping it in a user-friendly command-line-interface (CLI) which simultaneously simplifies most decisions for non-expert users while keeping customizability for expert ones. It produces paper-ready figures and tables that can be automatically annotated with consensus nomenclature like the Ballesteros-Weinstein or Common-G-protein-Nomenclature. The readout of the so-called neighborhoods and contact frequencies are presented in a number familiar graph types like contact matrices, flareplots, histograms and beta-colored 3D molecular structures. mdciao also ships with an API for Python users to have programmatic access to many core- and/or helper- functions beyond those of the pre-packaged command-line-tools. mdciao is fully documented, unit-tested and developed under continuous integration. The package is published under the GNU Lesser General Public License v3.0 or later, and is readily available for download under https://github.com/gph82/mdciao. A manuscript is in preparation. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #497 Free Energy along Transition Pathways from Structure Refinement Simulations

Presenting author: Emmi Pohjolainen Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Helmut Grubmüller, Andrea Vaiana, Maxim Igaev

Modern cryo-EM provides high-resolution structures of multiple conformational states of biomolecules and biomolecular complexes from heterogeneous samples, yielding spectacular insights into their conformational heterogeneity and functional mechanisms. This approach is limited, however, to highly populated states and lacks a detailed description of the dynamics and energetics of the transitions between these states. Here we show that molecular dynamics (MD) -based structure refinement methods can be used not only to obtain such information, but also to provide time resolved pathways for each atom of the system. As a proof of concept, we use the correlation driven MD (CDMD) structure refinement method to investigate the conformational transition between open and closed states of a ligand free Adenylate-kinase (AKE) protein in solution. In CDMD the simulated system is driven from its initial state to the target state by introducing, in addition to the MD forcefield, a controlled biasing potential. This potential tends to maximize the real space correlation coefficient (CC) between the density of the simulated system and of the target state. The value of this correlation coefficient CC(X) specified for any given configuration X along the simulation trajectory can be used as a coordinate to describe the transition towards the target state. This results in different coordinates describing the forward and reverse transitions. We overcome this problem by optimizing the difference between the correlations to the start and end states, respectively. Using this reaction coordinate allows to compute the free energy profile by umbrella sampling simulations. Compared to reference free energies derived from 1 millisecond of unbiased MD simulations, our method yields similar transition pathways, thus underscoring that indeed low energy paths are identified. Our method should also be useful for larger systems for which unbiased sampling is impossible. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #294 Optimisation of the Mechanical Stability of Anticalin:CTLA-4 Protein Complex via GoMARTINI Simulations

Presenting author: Adolfo Poma Institute of Fundamental Technological Research Polish Academy of Sciences, Department of Biosystems and Soft Matter, Warsaw, Poland Co-author(s): Adolfo B. Poma, Rodrigo A. Moreira, Zhaowei Liu, Michael A. Nash

A variety of non-immunoglobulin protein scaffolds with potential as alternatives to monoclonal antibodies for nanoparticle-based drug delivery are of high interest for targeting T-cells displaying cytotoxic T-lymphocyte antigen 4 (CTLA-4), a limiting factor is the resistance of the anticalin:CTLA-4 complex to mechanical forces exerted by local shear stress. Here, we used a multi scale approach based on Go-MARTINI approach and single-molecule AFM force spectroscopy (AFM-SMFS) to screen residues along the anticalin backbone and determine the optimal anchor point that maximizes binding strength of the anticalin:CTLA-4 complex. We parametrize the Go-MARTINI approach based on the AFM_SMFS data and the molecular dynamics (MD) simulations using parametrized approach help to explain the mechanisms underlying the geometric dependency of mechanostability in the complex. This process can be related to an unzipping-shear mechanism which is commonly seen in nucleic acids strands. These results suggest that optimization of attachment residue position for therapeutic and diagnostic cargo can provide large improvements without requiring genetic mutation of binding interface residues. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #587 Lipid Specificity of Viral Proteins

Presenting author: Chetan Poojari Saarland University, Department of Theoretical Physics, Computational Biophysics Group, Saarbrücken, Germany & Theoretical Physics and Center for Biophysics, Saarland University, Saarbrücken, Germany Co-author(s): Jochen Hub

Viral fusion proteins drive fusion of viral and host cell membranes in a series of complex structural transition events. Although the structure of several fusion proteins have been solved, the characterization of viral protein-membrane interactions at atomistic resolution is still missing. Membrane interactions of fusion proteins are conserved and occur via fusion peptides (FPs) in class I and fusion loops (FLs) in class II/III proteins. Previously, we had characterized the glycerophospholipid binding in class II fusion protein glycoprotein C (gC) of Rift Valley fever virus (RVFV) [2] and the studies revealed specific binding pockets for PC lipids. Now we aim to understand if specific lipid binding site also exists in class I and III viral proteins and any preference for lipid type. Molecular dynamics (MD) simulations is an excellent technique to understand how proteins associates with lipid membrane at atomistic resolution and here we make use of MD simulations to gain structural insights into lipid contact sites and membrane insertion of FP / FL residues.

[1] M. Vallbracht et al., J Virol 92: e01203-17, (2018) [2] P. Guardado-Calvo et al., Science 358, 663-667, (2017) Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #781 Memory Kernel Estimation from Constrained MD Simulations

Presenting author: Matthias Post University of Freiburg, Institute of Physics, Biomolecular Dynamics Group, Freiburg im Breisgau, Germany Co-author(s): Steffen Wolf, Gerhard Stock

Usually, the modelling of biophysical systems necessitate very long molecular dynamics simulations to sample all important configurations and transitions, with biologically relevant timescales ranging from few femtoseconds to multiple seconds. The complexity is then reduced by some form of dimensionality reduction, resulting in a description of the system by a set of a few collective coordinates. Then, the essential dynamics can be described by the (generalized) Langevin equation. If the aforementioned sampling problem is circumvented by an enhanced sampling method, can this Langevin dynamics still be recovered? We study the special case of constraining one reaction coordinate to enforce slow transitions. First, the Free energy can be recovered by use of Jarzynskis equality; not only along this reaction coordinate, but also in general for a set of collective variables. The position dependent memory kernel or friction can be recovered through the constraint force auto-correlation. We study the influence of the constraint and the pulling rate on the friction estimate. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #769 All-Atom MD Simulations of High-Concentration Protein Solutions

Presenting author: Tobias Marcel Prass Ruhr University Bochum, Department of Theoretical Chemistry, Molecular Simulation Group, Bochum, Germany Co-author(s): Lars Schäfer

Many biological cells constitute highly crowded environments, which can influence the structure and/or the dynamics of biomolecules. Likewise, many biopharmaceuticals are also administered at high concentrations, for example monoclonal antibody formulations. In principle, MD simulations provide the means to study the dynamics and interactions in such complex systems. However, computing properties such as the shear viscosity requires careful consideration of the size of the simulation system (copy number of proteins in the box), simulation time, and protein and water force field. Here, we investigate the influence of finite size effects in MD simulations of high-concentration solutions (ca. 200 mg/ml) of the monoclonal antibody (mAb) trastuzumab. We present data from simulations of 4 and 8 mAbs in the simulation box with varying amounts and nature of mobile ions. We focus on the shear viscosity of the concentrated solution and discuss aspects related to its computation from the (very large) fluctuations of the pressure tensor. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #576 pyPolyBuilder: An Automated Software for Building Molecular Topologies and Initial Configurations for Arbitrary Molecules for Molecular Dynamics Simulation

Presenting author: Mayk Caldas Ramos Federal University of Rio de Janeiro, Chemistry Institute, Rio de Janeiro, Brazil Co-author(s): Patrick K. Quoika, Vitor A. C. Horta, Jorge L. M. do Amaral, Klaus R. Liedl, Bruno A. C. Horta

Nowadays, new molecular systems are being synthesized daily for attending to the technological demand of numerous areas of nanotechnology. Theoretical and computational studies of those new systems are of crucial importance for understanding them as well as the suggestion of new improvements. In order to study such systems, making computational models that represent them is the first step to be done. Generating molecular topology files (MTF) and initial structure as input for a classical molecular dynamics (MD) simulation is a needed step in any MD study. However, depending on the size of the molecules, making such files may be a challenging task, especially for supramolecular systems. There are many tools for building MTFs for proteins, small molecules, and even some tools specialized for dendrimers. Here, we present a generalized tool for building MTFs and initial structures for an arbitrary supramolecule such as linear and hyper-branched polymers (as dendrimers, for instance). PyPolyBuilder is a standalone command-line tool developed in python3. For that reason, it may be compatible with most computer architectures and operating systems. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #715 Hybrid Simulations of Collagen as Mechanical and Chemical Buffer

Presenting author: Benedikt Rennekamp Heidelberg Institute for Theoretical Studies (HITS), Department of Molecular Biomechanics, Heidelberg, Germany & Interdisciplinary Center for Scientific Computing, Heidelberg University Co-author(s): Frauke Gräter

Proteins in their natural environment are exposed to various mechanical loads that can lead to covalent bond scissions. Knowledge of these molecular breakages is important to understand mechanical properties and, potentially, the failure mechanism of the protein. However, in regular Molecular Dynamics (MD) simulations, covalent bonds are predefined and reactions cannot occur. Furthermore, such events would rarely take place on MD time scales. We previously developed a hybrid Kinetic Monte Carlo / Molecular Dynamics (KIMMDY) scheme that overcomes these limitations. Here, bond rupture rates are calculated in the spirit of a transition state model based on the interatomic distances in the MD simulation and then serve as an input for a Kinetic Monte Carlo step determining the reactive event. Using this new technique, we investigated bond ruptures in a multimillion atom system of tensed collagen, a structural protein found in skin, bones and tendons. Our simulations show a clear concentration of homolytic bond scissions near chemical crosslinks in collagen. Having a higher rupture propensity on this molecule side, crosslinks located there can act as a mechanical buffer by releasing additional length of the stressed strands - a property that is conserved among collagen models from various species. Additionally, these breakage sites are in vicinity of redox-active amino acids, thereby also acting as a chemical buffer for the arising oxidative stress and overall suggesting a stress buffering role of collagen. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #802 Investigating the Structure-Dynamics-Function Relationship in Antibodies

Presenting author: Marta Rigoli University of Trento, Department of Physics, Statistical and Biological Physics Group, Trento, Italy Co-author(s): Thomas Tarenzi, Raffaello Potestio

The paradigm that connects sequence, structure and function in proteins has been revisited in recent years, opening new perspectives on the importance of dynamics [1]. In this work we tackle this issue for a full-length IgG4 antibody, through the analysis of all-atom molecular dynamics (MD) simulations, with the final objective of correlating motions and structural features. We first characterize the dynamics of the antibody pembrolizumab [2], through 2 μs of all-atom MD simulations, to investigate the correlation between structural properties and the flexibility of the molecule. Subsequently we perform 2 μs of all-atom MD simulations of the same antibody bound to its antigen, to investigate the changes in dynamics. We analyzed the simulations through several techniques among which we highlight the effectiveness of those based on the calculation of the information transfer between different amino acids [3]. These types of measurements, combined with the analysis of the interaction between the antibody and its antigen, allow us to identify significant correlations between the antibody binding site and the overall structure, providing clues on the effect of the binding event. The investigations carried out in this work also serve as a guide in the identification of those structural patterns whose preservation is necessary in the construction of coarse-grained models. Overall this study is meant as a starting point for the application of a multi-scale method to large-size macromolecules.

[1] Hensen, U. et al. (2012). Exploring protein dynamics space: the dynasome as the missing link between protein structure and function. PloS one, 7(5). [2] Scapin, G. et al. (2015). Structure of full-length human anti-PD1 therapeutic IgG4 antibody pembrolizumab. Nat Struct Mol Biol, 22(12):953-8. [3] Bowerman, S., and J. Wereszczynski. (2016) Detecting Allosteric Networks Using Molecular Dynamics Simulation. Methods in enzymology. 578. 429-47. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #639 Cardiolipin’s Role in Preventing Pore Formation in Staphylococcus aureus Membrane Models

Presenting author: Cristian Camilo Rocha University of Antioquia, Faculty of Exact and Natural Sciences, Max Planck Tandem Group - Biophysics of Tropical Diseases, Medellín, Colombia Co-author(s): Camilo Aponte-Santamaría, Pilar Cossio Tejada

S. aureus is a Gram positive bacteria, listed as one of the main causes of nosocomial bacteremia in North America, Latin America and Europe. Due to the excessive use of antibiotics, it has acquired drug-resistance to conventional drugs such as Methicillin and Daptomycin. An adaptation mechanism of S. aureus is the modification of the lipid composition of its membrane. Recent experiments show that an increase in the concentration of the phospholipid cardiolipin (CL) enables it to resist various stress environments. Atomic details of the CL role in preserving the structure of S. aureus membrane in stressful environments have not yet been elucidated. In this work, we use molecular dynamics and umbrella sampling simulations to quantify the implications of increase in CL concentration over the pore formation process in S. aureus membrane models. We found that increasing the CL concentration leads to an increase in the free energy barrier for the formation of a transmembrane pore, going from ΔG of ~25 kBT for a pure POPG membrane to ~32kBT for a membrane with 30:70 CL:POPG. This increase in the free energy barrier can be associated with changes in the biophysical properties of the membrane, such as an increase in the bilayer thickness and an increase in the packing of the lipids that make the membrane more stable. Our results suggest that by just increasing CL membrane concentration S. aureus is less susceptible to pore-formation processes. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #879 Conformational Landscape of AmyloidB1-42: The Impact of Metals

Presenting author: Lorena Roldán Autonomous University of Barcelona, Department of Chemistry, InSiliChem Group, Cerdanyola del Vallès, Barcelona, Spain Co-author(s): Francesca Pecatti, Giuseppe Sciortino, Mariona Sodupe, Jean-Didier Maréchal

Alzheimer’s Disease (AD), the most common form of dementia, is an important threat to health nowadays. Its main cause is the formation of amyloid plaques, with β-amyloid peptides (Aβ) as its principal constituent, though their aggregation mechanism is still a mystery. Among other theories, the metal ions hypothesis states that metals could influence on the aggregation propensity. In the present study, the conformational landscape of Aβ42 in presence of Al(III) and Cu(II) has been explored with the enhanced simulation system Gaussian accelerated Molecular Dynamics, allowing a more exhaustive exploration. In general, metal binding reduced the flexibility of the peptide, which reorganizes both secondary and tertiary structures, frequently leading to U-shape structures. Nonetheless, the stabilization degree is remarkably different between the metal ions tested. Cu(II) usually provokes stable U-shape structures, with two antiparallel α-helixes. On the contrary, Al(III) presents less stable secondary and tertiary structural patterns, with a smaller helical content and less propensity to adopt U-shape forms, thus, favoring residues exposition to the solvent. Further studies are being performed to clarify the implication of those trends on the aggregation process. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #597 Behavior of Lipid Tails of Palmitoylated Transmembrane Peptides in Phospholipid Membranes: A Molecular Dynamics Study

Presenting author: Maria Chiara Saija J. Heyrovsky Institute of Physical Chemistry, Department of Computational Chemistry, Prague, Czech Republic Co-author(s):

Palmitoylation is one of the post-translational lipid modifications of proteins in which the cysteine’s -SH group was esterified. Protein palmitoylation was proven as essential for many aspects of the cell organization, such as the trafficking of proteins from the intracellular organelles toward the cell membrane and the localization into it. Phosphoprotein associated with glycosphingolipid micro-domains (PAG) is a transmembrane protein for which palmitoylation was demonstrated to be crucial for its trafficking toward phospholipid membranes and its accumulation into the ordered regions of the cell membrane. What is not well explored is how palmitoyl lipid tails behave in the cell membrane and whether or not these tails are responsible for the stability of the protein into the bilayers. Furthermore, the palmitoylated protein’s propensity in different membrane phases, named liquid-ordered (Lo) and liquid disordered (Ld), hasn't been fully explored yet. In this work, we employ atomistic molecular dynamics simulation to assess the behavior of the palmitoylated PAG transmembrane domain into several model membranes mimicking Lo and Ld phases and Lo/Ld interface. We focus on molecular-level aspects of palmitoyl accumulation at the water- membrane interface and in the well-hydrated headgroup region. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #350 Replica-Exchange Molecular Dynamics of Protein Disulfide Isomerase-Assisted Folding of a Conotoxin

Presenting author: Windol Santos University of the Philippines Baguio, Department of Physical Sciences, Baguit City, Philippines & Institute of Chemistry, College of Science, University of the Philippines Diliman Co-author(s): Ricky B. Nellas

The unaided oxidative folding pathway of a contoxin falls somewhere between the well- defined folding pathway of bovine protease trypsin inhibitor, and the rapid, hydrophobic- driven collapse of hirudin. This means that conotoxins are likely to form alternate disulfide linkages, and so will take on a myriad of structures. The reordering of disulfide linkages is relatively slow, and this makes the oxidative folding of conotoxins relatively slow. However, the presence of protein disulfide isomerase (PDI) is known to increase the folding rate of the conotoxin. The hydrophobic regions present in the bʹ-domain are thought to facilitate the folding of the conotoxin via hydrophobic interactions. In this study, replica-exchange molecular dynamics in UNRES was used to generate conformations of conotoxins with varying disulfide connectivities. The conformations of the conotoxins were docked with PDI using the HADDOCK program to obtain probable complexes. Selected conotoxin-PDI complexes were coarse-grained using the Martini forcefield and simulated using the GROMACS package. Using biophysical analyses such as principal component analysis, sulfur-sulfur distances, hydrophobic contacts, among others, we find that in the presence of the hydrophobic bʹ- domain, the “collapse” of the conotoxin is guided towards the native state, in a way that conformations favoring native disulfide linkages are followed. It was also found in this study that the spread of distances between free cysteine pairs of the conotoxin is not significantly decreased in the presence of other disulfide linkages. From these findings, it was concluded that hydrophobic contacts and the relative orientations of the aʹ and bʹ-domain play a role in stabilizing the cysteine pair distances of the conotoxins. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #478 Origin of Slow Solvation Dynamics in DNA: DAPI in Dickerson-DNA

Presenting author: Deepika Sardana Jawaharlal Nehru University, School of Physical Sciences, New Delhi, India Co-author(s):

Time-resolved fluorescence Stokes shift (TRFSS) experiments measure dynamics of complex biomolecules and their surrounding environment from femtoseconds to nanoseconds. These experiments unravel anomalously slow solvation dynamics in DNA beyond ~100 ps, whose origin remains incomprehensible. We compare results of TRFSS experiments to MD simulations of minor groove-bound DAPI in Dickerson-DNA over five decades of time from 100 fs to 10 ns. We show the solvation time-correlation function (TCF) calculated from (200 ns) simulation trajectory captures most features of slow dynamics, as measured in experiment. Decomposition of TCF into components resolves that slow dynamics originate from dynamically coupled DNA-water motion. This dynamically coupled DNA-water motion dominate in the slow solvation relaxation when probed by minor groove- bound DAPI in Dickerson-DNA, although the effect of water-Na+ coupled motion on slow dynamics cannot be overlooked. We find that freezing DNA fluctuations in simulation eliminates slower dynamics beyond ~100 ps, where water and Na+ dynamics become faster, although signature of strong anti- correlation is captured. Results show that primary origin of slow dynamics lies within slow fluctuations of DNA-parts which perturb nearby water and ions to govern the slow concerted solvation dynamics in Dickerson-DNA. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #915 About the Impact on MSMs of Protein MD Simulations by the Resemblance Between tICA Projections and Cosines

Presenting author: Malte Schäffner Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Steffen Schultze, Nicolai Kozlowski, Andreas Volkhardt, Helmut Grubmüller

Markov State Models (MSMs) are widely used to extract kinetic properties from molecular dynamic (MD) simulations of proteins. These models discretize the conformational space to describe the MD trajectory via a set of metastable states and transition rates. Conventional MSM constructions typically rest on projections of the atomic coordinates onto a suitably chosen subspace of the full configuration space. An widely used projection, considered the gold standard by many, employs the time-lagged independent correlation analysis (TICA). TICA aims at identifying slow processes by maximizing the autocorrelation along its components with respect to a previously defined lag time. We asked whether analysis of the TICA projections alone suffices to judge the quality of the resulting MSM. As a starting point to answer this question, we carried out TICAs of 2000 unbiased 1μs MD trajectories—10 trajectories each for 200 globular proteins with sequence lengths from 35 to 399 amino acids. For strikingly many trajectories the TICA projections along the slowest two components resemble cosines with half and full period and do not show pronounced metastable states. We used the cosine content—originally defined as the inner product between the projection on a PCA component with a cosine [Berk Hess, 2002]—to quantify the resemblance and analyze the relation between cosine content and protein properties. We found that, on average, the cosine content increases with protein size indicating that the cosine content can be used to detect undersampling and, hence, overfitted MSM models. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #750 Effect of Transmembrane Domains on Free Energy of Stalk Formation

Presenting author: Katharina Scherer Saarland University, Department of Theoretical Physics, Computational Biophysics Group, Saarbrücken, Germany Co-author(s):

The formation of the stalk is known as the first step in membrane fusion. Using a novel reaction coordinate the free energy of stalk formation can efficiently be computed based on MARTINI CG force field and potential of mean force (PMF) calculations. The effect of transmenbrane domains (TMD) of the SNARE complex as well as of viral fusion protein on the free energies have been analyzed and reveal a decrease in both the free energy barrier of stalk formation and the free energy of the stalk itself. The effects observed seem smaller than previous suggested and dependent on the lipid composition. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #752 Introducing the Scandinavian Online Kit forNanoscale Modeling (VIKING)

Presenting author: Fabian Schuhmann Carl von Ossietzky University, Department of Physics, Quantum Biology and Computational Physics Group (QuantBioLab), Oldenburg, Germany Co-author(s): Vasili Korol, Ilia. A. Solov'yov

The field of computational biology is expanding at a rapid pace aided by the ever-growing capacity of supercomputers and the development of more and more specialized software. The amount of expertise required for every simulation can be overwhelming, especially for scientists who did not use computational methods daily or are joining the hunt for solving biological mysteries from a different area. On the other end, seasoned computational scientists might enjoy doing their simulations with ease. The only needed service to bring computational biophysics to any level scientist is VIKING (Scandinavian OnlineKit for Nanoscale Modeling) available at viking-suite.com and free-to-use within academia. VIKING is an online platform designed to provide an intuitive user-friendly experience to simulate and analyze biophysical processes [1]. It guides a user to set up molecular dynamics simulations from start to finish employing NAMD [2] and VMD [3], allows quantum chemistry calculations with different kinds of spectroscopy, includes a subset of Molspin [4] to calculate spin specific properties, and allows the randomized construction of polypeptide chains with Pep McConst [5]. VIKING supports direct links to supercomputers, taking care of submitting and monitoring tasks and retrieving simulation data back to the VIKING interface, ready to analyze and/or download. In this presentation, we will give a brief overview of VIKING and its options by demonstrating some examples of possible computational tasks. We will append a structure using Pep McConst which is then to be simulated and briefly analyzed.

[1] V. Korol, P. Husen, E. Sjulstok, C. Nielsen, I. Friis, A. Frederiksen, A. B. Salo, and I. A. Solov’yov. Introducing VIKING:A Novel Online Platform for Multiscale Modeling.ACS Omega, 5(2):1254–1260, 2020. [2] J. C. Phillips, R. Braun, W. Wang, J. Gumbart,E. Tajkhorshid, E. Villa, C. Chipot, R. D. Skeel, La. Kalé, and K. Schulten. Scalable Molecular Dynamics with NAMD. J. Comput. Chem., 26(16):1781–1802, 2005. [3] W. Humphrey, A. Dalke, and K. Schulten. VMD: VisualMolecular Dynamics. J. Mol. Graph., 14(1):33–38, 1996. [4] C. Nielsen and I. A. Solov’yov. MolSpin - Flexible and Extensible General Spin Dynamics Software. J. Chem. Phys., 151(19), 2019. [5] F. Schuhmann, V. Korol, and I. A. Solov’yov. Introducing PepMcConst — A user-friendly peptide modeler for biophysical applications. J.Comput. Chem., 42:572–580,2021 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #846 A Bayesian Approach to Structure Determination from Ultrafast Single Molecule X-Ray Diffraction

Presenting author: Steffen Schultze Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s):

Single molecule X-Ray diffraction experiments are a promising new method for the structure determination of biomolecules. In the experiments, a stream of single molecules enters a femtosecond high-intensity X-Ray free electron laser beam, and for each molecule the scattered photons are recorded as an image. The reconstruction of the structure from this data is quite challenging: The orientations of the molecules during the scattering events are unknown, the signal to noise ratio is very low, and the recorded images are sparse, with typically less than 10-50 photons per image. Previously available analysis methods require at least 100 photons per image, or a very large number (e.g. 10⁹) of images. We present a novel bayesian approach that requires fewer photons per image and, at the same time, a comparatively small number of images. It can be applied using many different representations of the electron density, both in Fourier space and directly in real space. We demonstrate it using synthetic data, reconstructing the structure of Crambin at a resolution of 6-7 Angstromg using 106 images with on average 15 photons per image. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #858 Investigation of Ddifferent Protonation States on ADGRL1 Flap Dynamics

Presenting author: Florian Seufert Leipzig University, Institute for Medical Physics and Biophysics, Proteinformatics Group, Leipzig, Germany Co-author(s):

Adhesion G-Protein Coupled Receptors (aGPCR) are a family of 33 receptors exhibiting large and variable N-terminal extracellular regions. The defining feature of aGPCRs is the conserved GPCR-autoproteolysis inducing domain (GAIN domain), mediating autoproteolytic cleavage at the GPCR proteolytic site (GPS).1,2 A tethered agonist (TA) between the GPS and the seven- transmembrane region activates aGPCR, however the mechanism of TA exposure to the seven-transmembrane region remains elusive.3–6 In a recent study, GAIN domains were investigated using molecular dynamics (MD) simulations of GAIN domain crystal structures and homology models combined with in vitro labeling experiments. It was shown that the GPS region is constitutively solvent-accessible, mediated by two surrounding flexible protein regions termed flaps.7 Our studies proposed two glutamate residues being part of solvent- exposure mediating flaps in ADGRL1, exhibiting high flexibility in MD simulations. With the change in position, changes in residue pKa are expected in closed and open flap states. However, such changes cannot be easily simulated by classical MD based on non-polarizable force fields and unbreakable bonds. Therefore, protonation states of residues must be determined before running the simulation. We show that by changing the initial protonation state pattern of GLU774 and GLU808 in ADGRL1, GAIN domain dynamics are affected and state-dependent differences in pKa of the acidic side chains can be observed, indicating that protonation state determination of flexible residues needs to be treated in detail to promote reliability of dynamics observed in MD simulations.

[1] Prömel, S. et al. The GPS Motif Is a Molecular Switch for Bimodal Activities of Adhesion Class G Protein-Coupled Receptors. Cell Rep. 2, 321–331 (2012) [2] Araç, D. et al. A novel evolutionarily conserved domain of cell-adhesion GPCRs mediates autoproteolysis. EMBO J. 31, 1364–1378 (2012) [3] Araç, D., Sträter, N. & Seiradake, E. Understanding the Structural Basis of Adhesion GPCR Functions. in Handbook of Experimental Pharmacology vol. 234 67–82 (Springer New York LLC, 2016) [4] Zhu, B. et al. GAIN domain–mediated cleavage is required for activation of G protein– coupled receptor 56 (GPR56) by its natural ligands and a small-molecule agonist. J. Biol. Chem. 294, 19246–19254 (2019) [5] Wilde, C. et al. The constitutive activity of the adhesion GPCR GPR114/ADGRG5 is mediated by its tethered agonist. FASEB J. 30, 666–673 (2016) [6] Demberg, L. M. et al. Activation of adhesion G protein-coupled receptors: Agonist specificity of Stachel sequence-derived peptides. J. Biol. Chem. 292, 4383–4394 (2017) [7] Beliu, G. et al. Tethered agonist exposure in intact adhesion/class B2 GPCRs through intrinsic structural flexibility of the GAIN domain. Mol. Cell, (2021) Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #352 Stimulating Life Essential Prebiotic Chemistry Through Automated Reaction Networks

Presenting author: Siddhant Sharma University of Delhi, Department of Biochemistry, Surat, India & Blue Marble Space Institute of Science, Seattle, Washington, United States Co-author(s): Aayush Arya, Jessica Ray, Eduardo Loranzo Garcia, Romulo Cruz, Jakob Andersen, Henderson Jim Cleaves

Complex chemical reaction networks can grow exponentially in terms of the chemical diversity they can generate. It is unknown whether such networks easily discover or shuttle fluxes through autocatalytic sub-networks. Such sub-networks may be common or rare or anywhere in between in organic chemistry in general. We aim to provide a map for experimental chemists studying complex organic reactions. We used an automated rule-based reaction generation to simulate the reaction network generated during the alkaline hydrolysis of glucose, which is a well studied reaction providing ample data for ground-truthing. We applied graph transformation rules based on well-documented reaction mechanisms and restricted by applying various constraints to the outputs, such as disallowed output structural motifs. We used isomorphism tests to match the output molecular structures to experimentally reported structures as a test of the completeness of our methods. The monoisotopic exact masses of the molecules in the computed reaction network product set were calculated and used to match peaks identified in high resolution FT-ICR-MS data of the same reaction. The reaction network was further assessed for the existence of potentially autocatalytic loops. This was done by loading the network topology (nodes being compounds and edges being reactions) into a graph database where pattern matching queries could be executed to search for patterns of interest. This work demonstrates some efficient methods for finding reaction pathways and autocatalysis in silico modeled reaction networks. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #878 Computational Methods to Tackle the pH Effects on Membrane-Inserting Peptides

Presenting author: Tomás Silva Faculty of Sciences, University of Lisbon, BioISI - Biosystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Diogo Vila Viçosa, Miguel Machuqueiro

Membrane-interacting peptides and proteins play an important role in biological pathways by inducing changes in the biophysical properties of either cell or organelle membranes. These effects are exerted by interface interactions ranging from simple surface adsorption to full membrane bilayer crossing. These are very relevant due to their therapeutic potential as antimicrobial agents or as drug-delivery systems in more target-specific therapies (i.e. tumors). These types of model peptides and membranes are widely used as test cases for novel computational methodologies, like the implementation of enhanced sampling techniques and the inclusion of relevant chemical-physical properties, such as pH. pHLIP is a membrane-insertion peptide, whose insertion process is triggered by the acidity-induced protonation of a key residue (Asp14). The intricate play of electrostatic interactions at the peptide/membrane interface constitutes a challenge, in which state-of-the-art methods, like the constant-pH molecular dynamics, are unable to adequately sample the configurational and protonation space. In this work, we apply our newly-developed pH-replica exchange (pHRE) method [1] to overcome the well-known sampling limitations and provide enhanced sampling at the electrostatic environments that dictate the equilibrium between Asp14 and the lipid bilayer. By performing pHRE simulations of wt-pHLIP in different POPC membrane sizes, we identified that most pKa variability, observed between the insertion-dependent pKa profiles of all systems, derived from conformational heterogeneity as a result of strong and persistent interactions between Asp14 and the lipid phosphate groups. Despite these issues, our method still predicted pKa values (6.0~6.2), at deeper membrane regions, which are in agreement with the experimental pK of insertion (6.0) [2]. These results support our approach as a valuable tool for pKa prediction in membrane environments and to capture the underlying electrostatic effects occurring at the peptide-membrane interface, thus opening a pathway for future applications in similarly challenging systems.

[1] Vila-Viçosa D, Reis PBPS, Baptista AM, Oostenbrink C, Machuqueiro M. A pH replica exchange scheme in the stochastic titration constant-pH MD method. J Chem Theory Comput. 2019;15: 3108–3116 [2] Vila-Viçosa D, Silva TFD, Slaybaugh G, Reshetnyak YK, Andreev OA, Machuqueiro M. Membrane-Induced \pKa Shifts in wt-pHLIP and Its L16H Variant. J Chem Theory Comput. 2018;14: 3289–3297 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #727 Mechanism of Inhibition of ATP Synthase

Presenting author: Joanna Słabońska Gdansk University of Technology, Facutly of Chemistry, Department of Physical Chemistry, Computational Molecular Biophysics Group, Gdańsk, Poland Co-author(s): Antoni Marciniak, Jacek Czub

The FoF1 ATP synthase is a membrane-embedded enzyme present in all living organisms, including the mitochondria of yeast and mammals, as well as plant thylakoids and bacterial cells. It synthesizes over 90% of cellular ATP using the proton motive force (pmf). The pmf, composed of a proton gradient (ΔpH) and a membrane electrostatic potential (Δψ), energizes the rotation of c-ring, a Fo subcomplex, thus converting electrochemical into mechanical rotational energy. The mechanism of proton transport by Fo is central to research aimed at using Fo as a molecular therapeutic target, such as derivatives of the two known Fo inhibitors - bedaquiline and oligomycin. Previous genetic studies have identified an inhibitor binding site among all organisms, thereby creating a common 'drug binding site'. Thus, this drug binding site can serve as an effective target for the design of new antibiotics developed through rational design. Here, our enforced rotation molecular dynamics simulations of the yeast and mycobacterial Fo complex allow us to investigate the effect of protonation states and inhibitor binding on c-ring rotation and proton transfer. To clarify the structural basis of specific recognition of the c- ring by inhibitors, we correlate contact patterns between target-bound bedaquiline and oligomycin. Our research will allow us to trace the pathway of proton translocation through the membrane and examine the mechanistic details of this process, including possible structural changes associated with its inhibition. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #666 Benchmark of Analytical TD-LC-DFTB Gradients in DFTB+ and Application in Excited State QM/MM Simulations

Presenting author: Monja Sokolov Karlsruhe Institute of Technology (KIT), Institute of Physical Chemistry, Department of Theoretical Chemical Biology, Karlsruhe, Germany Co-author(s): Beatrix M. Bold, Julian J. Kranz, Sebastian Höfener, Thomas A. Niehaus, Marcus Elstner

The study of fluorescence requires an accurate description of excited states. If the dynamics of a fluorophore needs to be considered, sampling of the excited state phase space becomes necessary. However, ab initio methods and TD-DFT are computationally too expensive to be used in simulations of a significant length. With the implementation of analytical gradients for the time-dependent density functional tight-binding (TD-LC-DFTB) method in DFTB+, optimizations and simulations of excited states can now be performed at a reasonable computational cost. Further, it is possible to account for environmental effects on fluorescence in QM/MM simulations. This poster shows an extensive benchmark of the TD-LC-DFTB method with respect to geometries and transition energies. It includes adiabatic excitation energies, reorganization energies and vibronic spectra. Furthermore, the results of QM/MM simulations with Gromacs/DFTB+ of solvated fluorophores in excited state are presented. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #536 Molecular Dynamics Simulations Of Hydrophobin Bilayers

Presenting author: Leonhard Starke Saarland University, Department of Theoretical Physics, Computational Biophysics Group, Saarbrücken, Germany Co-author(s): Tobias Fischbach, Jochen Hub

Hydrophobins are a family of proteins that are characterized by a large exposed hydrophobic region, which makes them strongly amphiphilic. Class II Hydrophobins self-assemble into membranes on a water-air or water-oil interface, revealing long- range ordered hexagonal structures[1]. This allows manufacturing of pure-protein bilayers and vesicles [2]. Recent experiments show that the protein bilayer has an almost zero water permeability. We are conducting atomistic and coarse grained MD simulations of HFBI bilayers to investigate the molecular origins of this unusual behaviour. The initially proposed structure, which consists of an overlay of 2 crystal lattices was found to be unstable and therefore could not explain the experimentally observed behaviour. This leads to the assumption that the bilayer undergoes a rearrangement of the proteins, forming a dense structure. However, obtaining such a stable structure, that reproduces the experimentally observed properties, remains challenging.

[1] Lindner,M.B. Curr. Opinion in Colloid & Interface Science 14,356-363 (2009) [2] Hähl et.al. Advanced Materials, 29, 1602888 (2017) Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #870 In silico Study of Acid-Induced Anti-Tumor Drug Resistance

Presenting author: Pedro Suzano Faculty of Sciences, University of Lisbon, BioISI - Biosystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Lisbon, Portugal Co-author(s): Miguel Machuqueiro, Tomás Silva

Targeted cancer therapeutics remains a central goal of cancer research. The tumor microenvironment (TME) is an important component of tumor development that influences several key processes, such as tumor cell phenotype, proliferation, immune evasion, and drug resistance [1]. One important feature of the TME is the increased acidity of the extracellular milieu (pH 6.0-6.8) relative to the cytosolic pH (pH 7.2-7.4). This pH gradient between the extracellular and intracellular environments can potentially create an energy barrier, thus impairing the hydrophobic Lewis base drugs membrane crossing. The high pKa values (7.5-9) of these compounds, such as sunitinib and nintedanib, which are known tyrosine kinase inhibitors, require them to first undergo deprotonation before passively diffusing through the plasma membrane into the cells [2], which becomes more difficult in more acidic microenvironments like the TME. Our main objective is to calculate the different membrane permeability values at different pH environments: in normal cells (~7.5), the TME (~6.0) and in the liposomes (~4.5). We used umbrella sampling coupled with constant-pH molecular dynamics (US-CpHMD) simulations at four different pH values (pH 4.5, 6.0, 7.5, and 9.0) to obtain the desired PMFs, from which the membrane permeabilities can be estimated [3]. The preliminary results indicate higher permeability rates for healthy cell environments (pH 7.5), while more acidic environments suffer from slower membrane diffusion rates. Moreover, the PMF calculations show higher energy barriers at the membrane center, for the acidic pH values, whereas pH 7.5 was associated with a much smaller energy barrier when reaching the same membrane center. Overall, these results indicate that these Lewis base-containing drugs have a serious specificity problem, where the healthy cells are being targeted more than tumors.

[1] Assaraf YG, Brozovic A, Gonçalves AC, Jurkovicova D, Linē A, Machuqueiro M, et al. The multi-factorial nature of clinical multidrug resistance in cancer. Drug Resist Updat. 2019;46: 100645 [2] Stark M, Silva TFD, Levin G, Machuqueiro M, Assaraf YG. The Lysosomotropic Activity of Hydrophobic Weak Base Drugs is Mediated via Their Intercalation into the Lysosomal Membrane. Cells. 2020;9. doi:10.3390/cells9051082 [3] Dickson CJ, Hornak V, Pearlstein RA, Duca JS. Structure-Kinetic Relationships of Passive Membrane Permeation from Multiscale Modeling. J Am Chem Soc. 2017;139: 442–452 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #86 Counterion and Solvation Impacts on Nucleic Acid Conformations

Presenting author: Clark Templeton University of Texas at Austin, Department of Chemistry, Austin, United States Co-author(s):

An analytical model for the free energy change during collapse of an RNA molecule from an extended to a compact conformation is proposed. It considers explicit binding of water and ion molecules to the RNA and the exchange of these molecules with the aqueous solution. Microscopic states of the system are captured on a two-dimensional square lattice and evaluated using contact energies. We compute the free energy as a function of a collapse variable and the number of ions bound to the RNA. The major driving force to the collapse of the RNA chain is the gain in water entropy once expelled from the surface of the RNA molecule illustrated by decomposing the free energy into species contributions and their energy and entropy components. The sensitivity of the conclusions of the model to variations in parameters is computed and appears to be weak. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #839 A Coarse-Grained Molecular Dynamics Approach to Aqueous Polypeptide Coacervates

Presenting author: Maria Tsanai University of Groningen, Department of Biophysical Chemistry, Molecular Dynamics Group, Groningen, The Netherlands Co-author(s): Pim W. J. M. Frederix, Carsten F. E. Schroer, Paulo C. T. Souza, Alex de Vries, Siewert J. Marrink

Coacervation is a unique type of electrostatically-driven liquid-liquid phase separation, resulting from association of oppositely charged macro-ions typically in aqueous solution with a high salt concentration (0.1–4 M) [1]. Complex coacervates are widely studied for their functional properties as well as their potential involvement in cellular compartmentalization as biomolecular condensates. In this project, we present an explicit-solvent, molecular dynamics coarse-grain model of complex coacervates based on Martini 3.0 force field [2], which we use in order to produce the salt dependent coacervation of poly-lysine and poly- glutamate systems, and to simulate the partitioning of ions and small nucleotides between the condensate and surrounding solvent phase. [3] Our results show that the recently parametrized Martini 3.0 model can capture coacervate formation of biopolymers, opening the way to gain physical insight on the mechanisms that drive the formation and structuring of membraneless organelles within cells.

[1] C. E. Sing, Development of the modern theory of polymeric complex coacervation, Adv. Colloid Interface Sci. 2017, 239, 2-16. [2] S.J. Marrink, H.J. Risselada, S. Yefimov, D.P Tieleman, A.H. de Vries, The MARTINI forcefield: coarse grained model for biomolecular simulations, J. Phys. Chem. B, 2007, 111 (27), 7812- 7824. [3] D. Priftis M. Tirrell, Phase behaviour and complex coacervations of aqueous polypeptide solutions, Soft Matter, 2012, 8, 9396-9405. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #895 Molecular Dynamics Simulations of the p75 Neurotrophin Receptor Transmembrane Domain

Presenting author: Alexandros Tsengenes Heidelberg Institute for Theoretical Studies (HITS), Molecular and Cellular Modeling Group, Heidelberg, Germany & Faculty of Biosciences, Heidelberg University, Co-author(s): Rebecca C. Wade

Neurotrophins (NTs) are key regulators of the development and function of the nervous system. They interact with two different receptors: the p75 NT receptor (p75), which belongs to the tumor necrosis factor receptor (TNFR) family, and the Trk receptors, which are receptor tyrosine kinases. The main biological function of p75 is the induction of cell death, but it triggers other signaling pathways as well, such as survival and axonal growth. Cross-linking experiments have shown that NTs dimerize the extracellular domain of p75 upon binding, while other data indicate the presence of pre-formed p75 dimers [1]. However, the dimeric form of the receptor in its active and inactive states remains unknown. NMR structures of the wild-type (WT) and a C257A mutant of the rat p75 transmembrane (TM) domain dimer have been published [2], that show different interfaces between the TM helices. C257, which forms a disulfide bond between the monomers in the WT structure, has been shown to be important for signaling triggered by NGF binding. To examine the dynamic behavior of the p75 TM domain dimer, we performed atomistic and coarse-grained molecular dynamics simulations. Multiple simulations of the WT and mutant dimer were performed to achieve extensive sampling of the different dimer configurations. The results showed different configurations, suggesting that the interactions might be transient. These data will aid in the understanding of the function of p75.

Acknowledgement: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 765704 (www.euroneurotrophin.eu).

[1] Vilar, M. et al. Activation of the p75 neurotrophin receptor through conformational rearrangement of disulphide-linked receptor dimers. Neuron 62, 72-83, doi: 10.1016/j.neuron.2009.02.020 (2009). [2] Nadezhdin, K. D. et al. Structural Basis of p75 Transmembrane Domain Dimerization. J Biol Chem 291, 12346-12357, doi: 10.1074/jbc.M116.723585 (2016). Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #859 Non-local Interactions within the Disordered C-Terminal Domain of the Measles Virus Nucleoprotein

Presenting author: Andrea Vaiana Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): John Kunkel, Gerdenis Kodis, Sara M. Vaiana, Gabor Nagy, Helmut Grubmüller

The nucelocapsid (N) protein of the Measles virus consists mainly of two domains; Ncore, the N-terminal globular domain which encapsulates the viral RNA, and the disordered Ntail domain that, along with the Measles Phospho (P) protein, recruits the viral polymerase for replication. Binding studies show that this function of Ntail is related to a partially alpha-helical molecular recognition region (α-More). This region undergoes coupled folding and binding with the X domain of the phospoprotein (PXD). Here, we investigate the conformational dynamics of Ntail and its potential impact on PXD binding using photoinduced electron transfer (PET) experiments and molecular dynamics (MD) simulations of several Ntail mutants. The PET fluorescence decay between cystein-tryptophan pairs, introduced at different points within the Ntail sequence, suggests complex structural dynamics around the α-More region that cannot be explained through simple polymer models or coarse grained simulations. To further elucidate the internal Ntail dynamics, we performed full-atom MD simulations. The results indicate strong interactions between the α-More flaking regions and the N-terminal part of the peptide. The full atom simulations were also validated by comparison to independent experimental measurements including small angle X-ray scattering, Circular Dichroism and NMR spectroscopy. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #623 Determination of the Excess Chemical Potential of Dibenzothiophene in Imidazolium Ionic Liquids, Using Molecular Simulations

Presenting author: Marco Vinicio Velarde SAlcedo Universidad Autónoma del Estado de México, Facultad de Ciencias, Toluca, Mexico Co-author(s): Joel Sánchez-Badillo, Marco Gallo, Jorge López-Lemus

Aromatic sulfur compounds of the Thiophene family are amongst the most difficult pollutants to remove from fuels [1]; Failure to remove sulfur during this process results in the formation of sulfur oxides, an important source of air pollution emanating from automotive vehicle emissions [2,3]. Hydrodesulfurization (HDS) is a catalytic process performed at high pressure and temperature that removes most sulfur compounds [4], even though is the most effective process to remove sulfur from oil, is not suitable for the removal of aromatic sulfur compounds [1]. The liquid extraction of sulfur compounds at ambient pressure and temperatures, at lower energy costs has been considered as an alternative to replace or complement HDS processes. Ionic liquids (IL) are a promising class of solvents with a wide-ranging ability to interact with polar and non-polar compounds that present unique physicochemical properties such as low vapor pressure [5,6] and are considered as solvents in a variety of extraction processes [7]. The degree of solvation of dibenzothiophene (DBT) in imidazolium based ionic liquids (IL) [C4mim][Cl], [C4mim][Br], [C4mim][BF4], and [C4mim][CH3COO] was analyzed by means of molecular dynamics simulations. Particularly, the DBT excess chemical potential was calculated within imidazolium IL; Also, in order to elucidate the solvation mechanism at the atomic level of the DBT molecule within the ILs, intermolecular energetic interactions, radial and combined distribution functions, the monitoring of hydrogen-bonds, and average non-covalent interaction analysis, were calculated. The ionic liquids were modeled using the revisited OPLS-2009-IL all-atom FF [8,9] and the all-atom Virtual Site OPLS FF for Imidazolium-Based Ionic Liquids [10]; For the DBT classical non-polarizable force fields based on TRAPPE [11] and AMBER [12] were evaluated to correctly reproduce the experimental enthalpy of vaporization, dipole moment and various density values along the vapor-liquid equilibrium curve.

[1] Babich, I. V.; Moulijn, J. A. Fuel 2003, 82, 607-631 [2] Li, H.; He, L.; Lu, J.; Zhu, W.; Jiang, X.; Wang, Y.; Yan, Y. Energy Fuels 2009, 23, 1354-1357 [3] Thurston G. D., in International Encyclopedia of Public Health, edited by S. R. Quah (Academic Press, Oxford, UK, 2017), 367-377 [4] Cai, H.; Liu, Y.; Gong, J.; E, J.; Geng, Y.; Yu, L. J. Cent. South Univ. 2014, 21, 4091-4096 [5] Maginn, E. J. J. Phys.: Condens. Matter 2009, 21, 373101 [6] Zhang, S.; Lu, X.; Zhou, Q.; Li, X.; Zhang, X.; Li, S. Ionic Liquids. Physicochemical Properties (Elsevier Science, Oxford, UK, 2009) [7] Lei, Z.; Dai, C.; Chen, B. Chem. Rev. 2014, 114, 1289-1326 [8] Sambasivarao, S. V.; Acevedo, O. J. Chem. Theory Comput. 2009, 5, 1038–1050 [9] Doherty, B.; Zhong, X.; Gathiaka, S.; Li, B.;Acevedo, O. J. Chem. Theory Comput. 2017, 13, 6131 [10] Doherty, B.; Zhong, X.; Acevedo, O. J. Phys. Chem. B 2018, 122, 2962−2974 [11] Rai, N.; Siepmann, J. I. J. Phys. Chem. B 2007, 111, 10790-10799 [12] Liu, X.; Zhou, G.; Zhang, X.; Zhang, S. AIChE J. 2010, 56, 2983-2996 Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #799 Structural Basis of the Transmembrane Domain of the Yeast Mitofusin Fzo1

Presenting author: Raphaëlle Versini CNRS, Institut de Biologie Physico-Chimique-Fondation Edmond de Rothschild, PSL Research University, Paris, France & Sorbonne Université, Ecole Normale Supérieure, PSL Research University, CNRS, Laboratoire des Biomolécules (LBM), Paris (France) Co-author(s): Antoine Taly, Patrick Fuchs

Outer mitochondrial membrane (OMM) fusion is an important process for the cell and organism survival, as its dysfonction is often linked to neurodegenerative diseases. The OMM fusion is mediated by proteins named mitofusins, which are members of the dynamin-related protein (DRP) family. Fzo1 is the only mitofusin homologue of the yeast Saccharomyces cerevisiae. This protein is embedded in the OMM, and was modeled in literature by homology with the mitofusin related bacterial dynamin-like protein (BDLP) as template. However BDLP does not possess any transmembrane part. Thus, the structure of the Fzo1 transmembrane domain had to be determined using ab initio methods. This domain is made of two putative helices TM1 and TM2 that are likely packed against each other. One study in literature predicted the structure of Fzo1 transmembrane domain using the webserver PREDIMMER. In this this work, we wanted to complement this study by using a multiscale molecular modeling approach. We first used massive conformational sampling of the possible TM1/TM2 associations using coarse-grained molecular dynamics (MD). The first three most probable models obtained were then backmapped to an all-atom (AA) representation and 3 replicas per model were simulated using AA MD. Our AA trajectories suggest two models that are good candidates for the structure of Fzo1 transmembrane domain. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #830 Activation Pathway of Acetylated Cyclin Dependent Kinase 1

Presenting author: Krishna Vishwakarma Tifr Mumbai, Department of Chemistry, Mumbai, India & DBS TIFR Mumbai Co-author(s):

The main regulators of the cell cycle are the cyclin-dependent kinases (CDKs) which phosphorylate their target substrate and drive the cell cycle. These kinases are inactive in isolation and require binding with Cyclin proteins for their activation. The activity CDK-Cyclin complexes are being regulated by activatory and inhibitory phosphorylation and also by inhibitory protein binding, which have been quite well understood. Besides this, it has been found that CDKs undergo acetylation and inhibit the kinase activity whose study is quite obscure from the mechanistic point of view. Here using molecular dynamics (MD) simulation we have studied the activation pathway of acetylated CDK1 and the molecular mechanism by which it inhibits the kinase activity. Our result suggests that acetylated CDK1 may not favor cyclin-B binding and its activation involves first the deacetylation and then Cyclin-B/ATP binding for its activation. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #917 Improving Reproducibility of Automatically Generated Markov Models From Molecular Dynamics Trajectories

Presenting author: Andreas Volkhardt Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Göttingen, Germany Co-author(s): Nicolai Kozlowski, Malte Schäffner, Helmut Grubmüller

Generating Markov models is a broadly used method to capture dominant processes in protein dynamics from molecular dynamics(MD) trajectories. In such models, dynamics are represented as a graph of transition rates (edges) between essential states (nodes) such that transitions are independent of previously visited states. Generating Markov models from MD trajectories is a challenging task: It not only requires a large amount of sampling but often special knowledge about the analyzed system to handpick suitable reaction coordinates. However, if many different systems need to be analyzed or suitable reaction coordinates are not at hand, an automated approach for Markov model generation is required. Against that background, here we asked to which extent the construction of Markov models from MD trajectories is reproducible, and -- related -- how much of the protein dynamics these models actually capture. We used standard protocols (e.g. tICA, k-Means clustering, maximum likelihood transition matrix estimation) and neural network approaches (e.g. VAMPnet) to analyze three independent 1μs MD trajectories of 200 small globular proteins, selected to cover known folds and functions, and compared the resulting timescales. Their reproducibility depends on the method used to generate Markov models. Neural network approaches yield better reproducibility compared to standard protocols. We identified the high dimensionality of configuration space as a major factor that limits reproducibility. To address the well-known curse of dimensionality, we use a minimally-coupled subspace approach (MCSA) that decomposes configuration space into lower-dimensional independent subspaces. In summary, our results demonstrate that the reproducibility of Markov models generated using currently available methods in an automated way can be improved significantly. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #807 Nonlinear Allosteric Effect in Elastic Network Models of Proteins

Presenting author: Maximilian Vossel Max Planck Institute for Biophysical Chemistry, Department of Theoretical and Computational Biophysics, Mathematical bioPhysics Group, Göttingen, Germany Co-author(s): Aljaž Godec

Allostery is a ubiquitous phenomenon in proteins, where the binding of a ligand at one site induces perturbations at another, often spatially distant site. The large scale dynamics of biomolecules is often effectively described by coarse-grained elastic network models that encode the collective motion of proteins around their equilibrium structure. However, despite their conceptual simplicity the manner in which these network models respond to local structural perturbations, such as the binding of a ligand molecule, is highly non-trivial and in the context of allostery remains an unsolved problem. We develop a simple and efficient algorithm for determining the full, nonlinear response of such networks to arbitrary structural perturbations that mimic the binding of a ligand molecule in the limit of high stiffness (or low temperature). Applying the algorithm we find that the response often displays pronounced nonlinearities. This suggests that recent attempts to explain allostery in proteins based on linear response theory are not necessarily accurate and may not always be meaningful. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #791 Fluoro Substituents in a Protein Environment: Tightly Bound Water Extends Fluorinated Side-Chain

Presenting author: Leon Wehrhan Free University of Berlin, Institute for Chemistry and Biochemistry, Berlin, Germany Co-author(s): Leon Wehrhan, Bettina Keller

The introduction of fluorine to an organic molecule like an aminoacid can lead to strong effects on its physicochemical properties. The C-F bond introduces unique properties with its high polarity and low polarizability. So has fluorination of aminoacids shown significant changes to their hydrophobicity due to changes in their dipole moments, SASA and hydrogen bonding to water. Due to these effects on interaction patterns of aminoacids, the presence of fluorine has the ability to impact protein-protein interactions. This becomes clear in the case of BPTI mutants binding to Trypsin. Fluorination can fully restore the inhibitor activity of BPTI mutants with hydrocarbons at the key P1 site against Trypsin. Crystal structures suggest that fluorine enables an interaction of the BPTI variant to water molecules present in the Trypsin S1 pocket. We study the mechanism of binding by these fluorinated aminoacids in the S1 pocket of Trypsin with molecular dynamics simulations. We find that fluorination has an impact on the mobility of water molecules of the S1 pocket. Also, we find that the H-bond network in the S1 pocket is altered by the presence of fluorine. While classical hydrogen bonds involving the C- F bond likely do not play a role, other ways of interactions such as dipole-dipole are possible and further investigation is needed. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #796 Free Energy Calculations for Epigenetics and DNA Lesions: Applications to Nucleosome Positioning and Transcription Factor Binding

Presenting author: Miłosz Wieczór IRB Barcelona, Department of Mechanisms of Disease, Barcelona, Spain Co-author(s): Modesto Orozco

The increasingly important role of epigenetics and DNA damage in biomedical research, combined with the wealth of structural and genomic data, makes the atomistic studies of DNA modifications more relevant than ever. At the same time, thanks to software, hardware and theoretical improvements, the field of free energy calculations has matured to a point where robust predictions can be made cheaply and at scale. Here I use PMX-based tools to introduce a new parametrization of 16 modified DNA residues for alchemical simulations, ranging from abasic sites to single-strand breaks or base modifications to pyrimidine dimers. I then show how workflows building upon this modification library can be used for massive free energy- based screening of biologically relevant effects, using the example of (1) nucleosome positioning affected by lesions or epigenetic marks and (2) changes in the affinity of selected transcription factors to oxidation-prone target sites containing 8-oxoguanine. Poster, Online Workshop, April 23-24, 2021 “COMPUTER SIMULATION AND THEORY OF MACROMOLECULES”

Poster – #906 Sequence and Chemical Environment Determine the Global Dimension of Intrinsically Disordered Protein Ensembles

Presenting author: Feng Yu University of California, Merced, Department of Quantitative and Systems Biology, Merced, United States Co-author(s): David Moses, Alex Holehouse, Shahar Sukenik

Intrinsically disordered proteins (IDPs) play essential roles in the cell, but do not have a stable native structure. Lacking intramolecular bonds, IDPs exist in a rapidly changing conformational ensemble. These ensembles have a high degree of surface area exposure, making them sensitive to the physical-chemical composition of the cellular environment. The sensitivity of IDPs to their environment can lead to a solution-induced change in both global ensemble dimensions (such as radius of gyration) and local residual structure between residues, which may alter IDP function. To reveal the link between the IDP sequence and the sensitivity of its ensemble to physical-chemical changes in its environment we use implicit-solvent Monte Carlo simulations of IDP ensembles in a range of solution conditions using a method we call Solution Space Scanning. We use Solution Space Scanning to compile a dataset containing over 100 naturally occurring IDPs in different solution conditions. Our dataset reveals a staggering range of IDP sensitivities, which shows a weak correlation with sequence length and chain- average molecular features such as hydrophobicity or net charge. Instead, we find a strong correlation between IDP solution sensitivity and the global dimension of the chain in aqueous buffers. We corroborate our findings with high-throughput experiments and a polymer physics model to establish how sensitivity to solution conditions emerges in intrinsically disordered proteins.