Predicting and Experimentally Validating Hot-Spot Residues at Protein-Protein Interfaces
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
Cyclotides Evolve
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy 218 Cyclotides evolve Studies on their natural distribution, structural diversity, and activity SUNGKYU PARK ACTA UNIVERSITATIS UPSALIENSIS ISSN 1651-6192 ISBN 978-91-554-9604-3 UPPSALA urn:nbn:se:uu:diva-292668 2016 Dissertation presented at Uppsala University to be publicly examined in B/C4:301, BMC, Husargatan 3, Uppsala, Friday, 10 June 2016 at 09:00 for the degree of Doctor of Philosophy (Faculty of Pharmacy). The examination will be conducted in English. Faculty examiner: Professor Mohamed Marahiel (Philipps-Universität Marburg). Abstract Park, S. 2016. Cyclotides evolve. Studies on their natural distribution, structural diversity, and activity. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy 218. 71 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-9604-3. The cyclotides are a family of naturally occurring peptides characterized by cyclic cystine knot (CCK) structural motif, which comprises a cyclic head-to-tail backbone featuring six conserved cysteine residues that form three disulfide bonds. This unique structural motif makes cyclotides exceptionally resistant to chemical, thermal and enzymatic degradation. They also exhibit a wide range of biological activities including insecticidal, cytotoxic, anti-HIV and antimicrobial effects. The cyclotides found in plants exhibit considerable sequence and structural diversity, which can be linked to their evolutionary history and that of their host plants. To clarify the evolutionary link between sequence diversity and the distribution of individual cyclotides across the genus Viola, selected known cyclotides were classified using signature sequences within their precursor proteins. By mapping the classified sequences onto the phylogenetic system of Viola, we traced the flow of cyclotide genes over evolutionary history and were able to estimate the prevalence of cyclotides in this genus. -
Of Modified Peptides 660 Absorption
Index A Aequorea victoria 182, 192 post-column aerosols, danger of contamination 770 derivatization 303–305 Abbe, Ernst 181, 187, 485, 493 affinity capillary electrophoresis pre-column absolute molecule mass 4 (ACE) 285–286 derivatization 305–308 absolute quantification (AQUA) of binding constant, determined by 285 reagents used for 310 modified peptides 660 changing mobility 286 sample preparation 302 absorption complexation of monovalent acidic hydrolysis 302 bands, of most biological molecules 139 protein–ligand complexes 285 alkaline hydrolysis 303 measurement 140–142 affinity chromatography 91, 268, 650 enzymatic hydrolysis 303 of photon 135 affinity purification mass spectrometry using mass spectrometry 309 spectroscopy 131 (AP-MS) 381, 1003 L-α-amino acid residues/termini 225 acetic acid 228 agarose concentrations amino acid sequence analysis acetonitrile 227 DNA fragments, coarse separation milestones in 319 N-acetyl-α-D-glucosamine of 692 problems 322 (αGlcNAc) 579 migration distance and fragment amino acids 323–324 acetylated proteins length 692 background 324 detection of 651 agarose gels, advantages of 260 initial yield 324 separation and enrichment 649 agglutination 72 modified amino acids 324 acetylation 224, 645–647 aggregation number 288 purity of chemicals 324 sites, in proteins 656 AK2-antibodies 102 sample to be sequenced 322–323 identification of 655 alanine 562 sensitivity of HPLC system 325 N-acetyl-β-D-glucosamine alanine-scanning method 870 state of the art 325 (βGlcNAc) 579 albumin 3, 995 6-aminoquinoyl-N-hydroxysuccinimidyl -
Foldx As Protein Engineering Tool: Better Than Random Based Approaches?
Computational and Structural Biotechnology Journal 16 (2018) 25–33 Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/csbj FoldX as Protein Engineering Tool: Better Than Random Based Approaches? Oliver Buß ⁎,JensRudat,KatrinOchsenreither Institute of Process Engineering in Life Sciences, Section II: Technical Biology, Karlsruhe Institute of Technology, Karlsruhe, Germany article info abstract Article history: Improving protein stability is an important goal for basic research as well as for clinical and industrial applications Received 31 October 2017 but no commonly accepted and widely used strategy for efficient engineering is known. Beside random ap- Received in revised form 21 December 2017 proaches like error prone PCR or physical techniques to stabilize proteins, e.g. by immobilization, in silico ap- Accepted 20 January 2018 proaches are gaining more attention to apply target-oriented mutagenesis. In this review different algorithms Available online 03 February 2018 for the prediction of beneficial mutation sites to enhance protein stability are summarized and the advantages Keywords: and disadvantages of FoldX are highlighted. The question whether the prediction of mutation sites by the algo- FoldX rithm FoldX is more accurate than random based approaches is addressed. Fold-X © 2018 Buß et al. Published by Elsevier B.V. on behalf of the Research Network of Computational and Structural Thermostability Biotechnology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Protein stabilization Protein engineering Enzyme engineering 1. Introduction per unit of product [10–12][13]. For industrial enzymes improved sta- bility against heat, solvents and other relevant process parameters, Increasing protein stability is a desirable goal for different life science e.g. -
Foldx Accurate Structural Protein–DNA Binding
3852–3863 Nucleic Acids Research, 2018, Vol. 46, No. 8 Published online 28 March 2018 doi: 10.1093/nar/gky228 FoldX accurate structural protein–DNA binding prediction using PADA1 (Protein Assisted DNA Assembly 1) Downloaded from https://academic.oup.com/nar/article-abstract/46/8/3852/4955761 by Biblioteca de la Universitat Pompeu Fabra user on 25 November 2019 Javier Delgado Blanco1,†, Leandro Radusky1,†,Hector´ Climente-Gonzalez´ 1 and Luis Serrano1,2,3,* 1Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain, 2Universitat Pompeu Fabra (UPF), Barcelona, Spain and 3Institucio´ Catalana de Recerca i Estudis Avanc¸ats (ICREA), Pg. Lluis Companys 23, 08010 Barcelona, Spain Received January 18, 2018; Revised March 12, 2018; Editorial Decision March 13, 2018; Accepted March 20, 2018 ABSTRACT are involved in numerous processes including DNA repli- cation, DNA repair, gene regulation, recombination, DNA The speed at which new genomes are being se- packing, etc. Currently, although there are >120 000 struc- quenced highlights the need for genome-wide meth- tures deposited in the PDB (3), only ∼5000 of them in- ods capable of predicting protein–DNA interactions. volve DNA–protein complexes. When considering the rate Here, we present PADA1, a generic algorithm that ac- at which new genomes are being sequenced, the resolu- curately models structural complexes and predicts tion of novel DNA–protein structures is relatively scarce. the DNA-binding regions of resolved protein struc- As such, we need to develop methods not only capable of tures. PADA1 relies on a library of protein and double- predicting whether a protein can interact with DNA, but stranded DNA fragment pairs obtained from a train- also capable of determining the protein’s 3D binding re- ing set of 2103 DNA–protein complexes. -
Expanding Molecular Modeling and Design Tools to Nonnatural Sidechains
WWW.C-CHEM.ORG FULL PAPER Expanding Molecular Modeling and Design Tools to Non-Natural Sidechains David Gfeller,[a] Olivier Michielin,*[a,b,c] and Vincent Zoete*[a] Protein–protein interactions encode the wiring diagram of increase peptide ligand binding affinity. Our results obtained on cellular signaling pathways and their deregulations underlie a non-natural mutants of a BCL9 peptide targeting beta-catenin variety of diseases, such as cancer. Inhibiting protein–protein show very good correlation between predicted and interactions with peptide derivatives is a promising way to experimental binding free-energies, indicating that such develop new biological and therapeutic tools. Here, we develop predictions can be used to design new inhibitors. Data a general framework to computationally handle hundreds of generated in this work, as well as PyMOL and UCSF Chimera non-natural amino acid sidechains and predict the effect of plug-ins for user-friendly visualization of non-natural sidechains, inserting them into peptides or proteins. We first generate all are all available at http://www.swisssidechain.ch. Our results structural files (pdb and mol2), as well as parameters and enable researchers to rapidly and efficiently work with hundreds topologies for standard molecular mechanics software of non-natural sidechains. VC 2012 Wiley Periodicals, Inc. (CHARMM and Gromacs). Accurate predictions of rotamer probabilities are provided using a novel combined knowledge and physics based strategy. Non-natural sidechains are useful to DOI: 10.1002/jcc.22982 Introduction are currently expanding peptide screening technologies to include non-natural sidechains. Correct interpretation of these Protein–protein interactions are fundamental to most biologi- results at the atomic level requires structural and biochemical cal and biochemical processes. -
Understanding Protein-RNA Interactions for Alternative Splicing
Understanding Protein-RNA Interactions for Alternative Splicing During Gene Expression Using Molecular Dynamic Simulations Joseph Daou Department of Chemistry & Chemical Engineering/B.S. Chemistry Dequan Xiao Ph.D. Abstract The alternative splicing during gene expression is regulated by a type of protein called splicing factors. Recently, a splicing factor, SRSF2 protein was formed to recognize guanines and cytosines at the binding site of the RNA segment. A series of mutations were performed in experiments on SRSF2 to understand the binding interactions of the protein and RNA. However, the changes of binding interactions at the atomistic level due to the mutations have not been revealed. Here, we used molecular dynamics simulations to investigate the conformational changes and protein-RNA binding free energy changes due to a series of mutations. Through the extrapolation of intermediate states of molecular interactions during a fixed length of time throughout point mutations, we used free energy perturbation methods to compute the binding affinity between the mutated proteins and RNA segments. In addition, we also computed the binding free energy by comparing the free energy difference between the folded and unfolded states of the proteins. Our computed free energy changes due to mutations showed consistency with experimental findings. In addition, by molecular dynamic simulations for the solvated protein-RNA complexes, we revealed here the detailed interactions between the protein residues and the RNA for different mutants. Our results provide new insights on understanding the interaction between the splicing factor proteins and the RNA, which can be linked to understanding the pathological mechanisms of Leukemia and cancers. Introduction the option to solvate the RRM system for an in-vitro model Biophysical researchers have shown, comparable the environment of the protein-RNA complex. -
Nonproteinogenic Deep Mutational Scanning of Linear and Cyclic Peptides
Nonproteinogenic deep mutational scanning of linear and cyclic peptides Joseph M. Rogersa, Toby Passiouraa, and Hiroaki Sugaa,b,1 aDepartment of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan; and bCore Research for Evolutionary Science and Technology, Japan Science and Technology Agency, Saitama 332-0012, Japan Edited by David Baker, University of Washington, Seattle, WA, and approved September 18, 2018 (received for review June 10, 2018) High-resolution structure–activity analysis of polypeptides re- mutants that can be constructed (18). Moreover, it is possible to quires amino acid structures that are not present in the universal combine parallel peptide synthesis with measures of function genetic code. Examination of peptide and protein interactions (19). However, these approaches cannot construct peptide li- with this resolution has been limited by the need to individually braries with the sequence length and numbers that deep muta- synthesize and test peptides containing nonproteinogenic amino tional scanning can, which, at its core, uses high-fidelity nucleic acids. We describe a method to scan entire peptide sequences with acid-directed synthesis of polypeptides by the ribosome. multiple nonproteinogenic amino acids and, in parallel, determine Ribosomal synthesis (i.e., translation) can be manipulated to the thermodynamics of binding to a partner protein. By coupling include nonproteinogenic amino acids (20). In vitro genetic code genetic code reprogramming to deep mutational scanning, any reprogramming is particularly versatile, allowing for the in- number of amino acids can be exhaustively substituted into pep- corporation of amino acids with diverse chemical structures (21). tides, and single experiments can return all free energy changes of Flexizymes, flexible tRNA-acylation ribozymes, can load almost binding. -
Computational Prediction of Alanine Scanning and Ligand Binding Energetics in G-Protein Coupled Receptors
Computational Prediction of Alanine Scanning and Ligand Binding Energetics in G-Protein Coupled Receptors Lars Boukharta, Hugo Gutie´rrez-de-Tera´n, Johan A˚ qvist* Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden Abstract Site-directed mutagenesis combined with binding affinity measurements is widely used to probe the nature of ligand interactions with GPCRs. Such experiments, as well as structure-activity relationships for series of ligands, are usually interpreted with computationally derived models of ligand binding modes. However, systematic approaches for accurate calculations of the corresponding binding free energies are still lacking. Here, we report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 receptor and series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. Citation: Boukharta L, Gutie´rrez-de-Tera´nH,A˚qvist J (2014) Computational Prediction of Alanine Scanning and Ligand Binding Energetics in G-Protein Coupled Receptors. PLoS Comput Biol 10(4): e1003585. doi:10.1371/journal.pcbi.1003585 Editor: Alexander Donald MacKerell, University of Maryland, Baltimore, United States of America Received February 7, 2014; Accepted March 12, 2014; Published April 17, 2014 Copyright: ß 2014 Boukharta et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. -
Enabling Biomolecular Analysis and Engineering Along Structural Ensembles
bioRxiv preprint doi: https://doi.org/10.1101/2021.08.16.456210; this version posted August 17, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. pyFoldX: enabling biomolecular analysis and engineering along structural ensembles Leandro G. Radusky1 & Luis Serrano1,2,3 1 Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona 08003, Spain 2 Universitat Pompeu Fabra (UPF), Barcelona, Spain 3 ICREA, Pg. Lluis Companys 23, Barcelona 08010, Spain Abstract Recent years have seen an increase in the number of structures available, not only for new proteins but also for the same protein crystallized with different molecules and proteins. While protein design software have proven to be successful in designing and modifying proteins, they can also be overly sensitive to small conformational differences between structures of the same protein. To cope with this, we introduce here pyFoldX, a python library that allows the integrative analysis of structures of the same protein using FoldX, an established forcefield and modeling software. The library offers new functionalities for handling different structures of the same protein, an improved molecular parametrization module, and an easy integration with the data analysis ecosystem of the python programming language. Availability and implementation pyFoldX is an open-source library that uses the FoldX software for energy calculations and modelling. The latter can be downloaded upon registration in http://foldxsuite.crg.eu/ and is free of charge for academics. -
DIP/Dpr Interactions and the Evolutionary Design of Specificity In
ARTICLE https://doi.org/10.1038/s41467-020-15981-8 OPEN DIP/Dpr interactions and the evolutionary design of specificity in protein families Alina P. Sergeeva 1, Phinikoula S. Katsamba2, Filip Cosmanescu2, Joshua J. Brewer3, Goran Ahlsen2, ✉ ✉ Seetha Mannepalli2, Lawrence Shapiro2,3 & Barry Honig1,2,3,4 Differential binding affinities among closely related protein family members underlie many biological phenomena, including cell-cell recognition. Drosophila DIP and Dpr proteins med- 1234567890():,; iate neuronal targeting in the fly through highly specific protein-protein interactions. We show here that DIPs/Dprs segregate into seven specificity subgroups defined by binding preferences between their DIP and Dpr members. We then describe a sequence-, structure- and energy-based computational approach, combined with experimental binding affinity measurements, to reveal how specificity is coded on the canonical DIP/Dpr interface. We show that binding specificity of DIP/Dpr subgroups is controlled by “negative constraints”, which interfere with binding. To achieve specificity, each subgroup utilizes a different com- bination of negative constraints, which are broadly distributed and cover the majority of the protein-protein interface. We discuss the structural origins of negative constraints, and potential general implications for the evolutionary origins of binding specificity in multi- protein families. 1 Department of Systems Biology, Columbia University, New York, NY, USA. 2 Zuckerman Mind, Brain and Behavior Institute, Columbia University, New York, -
Foldx Accurate Structural Protein–DNA Binding Prediction
Nucleic Acids Research, 2018 1 doi: 10.1093/nar/gky228 FoldX accurate structural protein–DNA binding prediction using PADA1 (Protein Assisted DNA Assembly 1) Javier Delgado Blanco1,†, Leandro Radusky1,†,Hector´ Climente-Gonzalez´ 1 and Luis Serrano1,2,3,* 1Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain, 2Universitat Pompeu Fabra (UPF), Barcelona, Spain and 3Institucio´ Catalana de Recerca i Estudis Avanc¸ats (ICREA), Pg. Lluis Companys 23, 08010 Barcelona, Spain Received January 18, 2018; Revised March 12, 2018; Editorial Decision March 13, 2018; Accepted March 20, 2018 ABSTRACT are involved in numerous processes including DNA repli- cation, DNA repair, gene regulation, recombination, DNA The speed at which new genomes are being se- packing, etc. Currently, although there are >120 000 struc- quenced highlights the need for genome-wide meth- tures deposited in the PDB (3), only ∼5000 of them in- ods capable of predicting protein–DNA interactions. volve DNA–protein complexes. When considering the rate Here, we present PADA1, a generic algorithm that ac- at which new genomes are being sequenced, the resolu- curately models structural complexes and predicts tion of novel DNA–protein structures is relatively scarce. the DNA-binding regions of resolved protein struc- As such, we need to develop methods not only capable of tures. PADA1 relies on a library of protein and double- predicting whether a protein can interact with DNA, but stranded DNA fragment pairs obtained from a train- also capable of determining the protein’s 3D binding re- ing set of 2103 DNA–protein complexes. -
Exploring the Sequence Landscape of the Model Protein Rop to Gain Insights Into Sequence-Stability Relationship in Proteins
Exploring the sequence landscape of the model protein Rop to gain insights into sequence-stability relationship in proteins DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Nishanthi Panneerselvam Graduate Program in Biophysics The Ohio State University 2017 Dissertation Committee: Professor Thomas J. Magliery, Advisor Professor Charles E. Bell Professor Ralf A. Bundschuh Copyrighted by Nishanthi Panneerselvam 2017 Abstract Surface residues and surface electrostatics play an active role in maintaining protein stability. A combinatorial library randomizing five surface positions in Rop to NNK (K=G or T) codons was constructed. Interestingly, the consensus sequence had positively charged residues instead of negatively charged residues present in wild-type. Specifically, lysines were found more than arginines. To delve into this, all these five positions were individually mutated to Lys and Arg and four poly mutants were made by mutating to multiple lysines and arginines. Most of the point mutants were found to be active by Rop screen. All mutants were well folded as seen by circular dichroism studies. An important result was that most of the mutants were more thermally stable than the Cys-free wild-type scaffold AV-Rop. Thermodynamic parameters were found using Gibbs-Helmholtz analysis and the entropic change was higher for most mutants. Solubility was affected more in the poly mutants than in the point mutants. HSQC on selected variants revealed that the least stable mutant and poly mutants had more shifted peaks compared to the most stable mutant. No considerable differences were found between Lys and Arg mutants.