Molmod: an Open Access Database of Force Fields for Molecular
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Secondary Structure Propensities in Peptide Folding Simulations: a Systematic Comparison of Molecular Mechanics Interaction Schemes
Biophysical Journal Volume 97 July 2009 599–608 599 Secondary Structure Propensities in Peptide Folding Simulations: A Systematic Comparison of Molecular Mechanics Interaction Schemes Dirk Matthes and Bert L. de Groot* Department of Theoretical and Computational Biophysics, Computational Biomolecular Dynamics Group, Max-Planck-Institute for Biophysical Chemistry, Go¨ttingen, Germany ABSTRACT We present a systematic study directed toward the secondary structure propensity and sampling behavior in peptide folding simulations with eight different molecular dynamics force-field variants in explicit solvent. We report on the combi- national result of force field, water model, and electrostatic interaction schemes and compare to available experimental charac- terization of five studied model peptides in terms of reproduced structure and dynamics. The total simulation time exceeded 18 ms and included simulations that started from both folded and extended conformations. Despite remaining sampling issues, a number of distinct trends in the folding behavior of the peptides emerged. Pronounced differences in the propensity of finding prominent secondary structure motifs in the different applied force fields suggest that problems point in particular to the balance of the relative stabilities of helical and extended conformations. INTRODUCTION Molecular dynamics (MD) simulations are routinely utilized to that study, simulations of relatively short lengths were per- study the folding dynamics of peptides and small proteins as formed and the natively folded state was used as starting well as biomolecular aggregation. The critical constituents of point, possibly biasing the results (13). such molecular mechanics studies are the validity of the under- For folding simulations, such a systematic test has not lyingphysical models together with theassumptionsofclassical been carried out so far, although with growing computer dynamics and a sufficient sampling of the conformational power several approaches toward the in silico folding space. -
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
processes Review Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development Outi M. H. Salo-Ahen 1,2,* , Ida Alanko 1,2, Rajendra Bhadane 1,2 , Alexandre M. J. J. Bonvin 3,* , Rodrigo Vargas Honorato 3, Shakhawath Hossain 4 , André H. Juffer 5 , Aleksei Kabedev 4, Maija Lahtela-Kakkonen 6, Anders Støttrup Larsen 7, Eveline Lescrinier 8 , Parthiban Marimuthu 1,2 , Muhammad Usman Mirza 8 , Ghulam Mustafa 9, Ariane Nunes-Alves 10,11,* , Tatu Pantsar 6,12, Atefeh Saadabadi 1,2 , Kalaimathy Singaravelu 13 and Michiel Vanmeert 8 1 Pharmaceutical Sciences Laboratory (Pharmacy), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland; ida.alanko@abo.fi (I.A.); rajendra.bhadane@abo.fi (R.B.); parthiban.marimuthu@abo.fi (P.M.); atefeh.saadabadi@abo.fi (A.S.) 2 Structural Bioinformatics Laboratory (Biochemistry), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland 3 Faculty of Science-Chemistry, Bijvoet Center for Biomolecular Research, Utrecht University, 3584 CH Utrecht, The Netherlands; [email protected] 4 Swedish Drug Delivery Forum (SDDF), Department of Pharmacy, Uppsala Biomedical Center, Uppsala University, 751 23 Uppsala, Sweden; [email protected] (S.H.); [email protected] (A.K.) 5 Biocenter Oulu & Faculty of Biochemistry and Molecular Medicine, University of Oulu, Aapistie 7 A, FI-90014 Oulu, Finland; andre.juffer@oulu.fi 6 School of Pharmacy, University of Eastern Finland, FI-70210 Kuopio, Finland; maija.lahtela-kakkonen@uef.fi (M.L.-K.); tatu.pantsar@uef.fi -
Introduction to GROMOS
CSCPB - Introduction to GROMOS Information: Prof. Dr. W.F. van Gunsteren Laboratory of Physical Chemistry, ETH-Z¨urich, 8092 Z¨urich, Switzerland Tel: +41-44-6325501 Fax: +41-44-6321039 e-mail: [email protected] Note: This MD tutorial is still under development. Please report any errors, incon- sistencies, obscurities or suggestions for improvements to [email protected]. Purpose: This molecular dynamics (MD) tutorial serves a number of objectives. These are to obtain experience with: • computer simulation in general • executing and understanding GROMOS • interpreting the results of computer simulations Version: SVN revision December 5, 2007 W.F.v.G., Z.G., J.D., A-P.K., C.C., N.S. 1 Required knowledge: Some knowledge about the following is required: • Computer programming languages: ability to read simple code (C++). • Computer operating system language of the machine on which the tutorial will be carried out: UNIX. Good books on MD are (Frenkel & Smit, 2002) and (Allen & Tildesley, 1987). 2 Contents 1 INTRODUCTION 4 1.1 The Lennard-Jones interaction . 4 1.2 Electrostatic interaction . 5 1.3 Periodic boundary conditions . 5 1.4 Newton’s equations of motion . 6 1.5 The leap-frog integration scheme . 7 1.6 Coupling to a temperature bath . 8 1.7 Pressure and the virial . 9 1.8 Center of mass motion . 9 1.9 Gaussian or Maxwellian distributions . 10 1.10 The radial distribution function g(r).................. 10 1.11 Units . 11 2 INSTALLATION OF GROMOS 12 2.1 System Requirements . 12 2.2 Getting and Installing GROMOSXX . 13 2.3 Getting and Installing GROMOS++ . -
Development of an Advanced Force Field for Water Using Variational Energy Decomposition Analysis Arxiv:1905.07816V3 [Physics.Ch
Development of an Advanced Force Field for Water using Variational Energy Decomposition Analysis Akshaya K. Das,y Lars Urban,y Itai Leven,y Matthias Loipersberger,y Abdulrahman Aldossary,y Martin Head-Gordon,y and Teresa Head-Gordon∗,z y Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley CA 94720 z Pitzer Center for Theoretical Chemistry, Departments of Chemistry, Bioengineering, Chemical and Biomolecular Engineering, University of California, Berkeley CA 94720 E-mail: [email protected] Abstract Given the piecewise approach to modeling intermolecular interactions for force fields, they can be difficult to parameterize since they are fit to data like total en- ergies that only indirectly connect to their separable functional forms. Furthermore, by neglecting certain types of molecular interactions such as charge penetration and charge transfer, most classical force fields must rely on, but do not always demon- arXiv:1905.07816v3 [physics.chem-ph] 27 Jul 2019 strate, how cancellation of errors occurs among the remaining molecular interactions accounted for such as exchange repulsion, electrostatics, and polarization. In this work we present the first generation of the (many-body) MB-UCB force field that explicitly accounts for the decomposed molecular interactions commensurate with a variational energy decomposition analysis, including charge transfer, with force field design choices 1 that reduce the computational expense of the MB-UCB potential while remaining accu- rate. We optimize parameters using only single water molecule and water cluster data up through pentamers, with no fitting to condensed phase data, and we demonstrate that high accuracy is maintained when the force field is subsequently validated against conformational energies of larger water cluster data sets, radial distribution functions of the liquid phase, and the temperature dependence of thermodynamic and transport water properties. -
Qwikmd-Tutorial.Pdf
University of Illinois at Urbana-Champaign Beckman Institute for Advanced Science and Technology Theoretical and Computational Biophysics Group Computational Biophysics Workshop QwikMD - Easy Molecular Dynamics with NAMD and VMD Tutorial by Rafael C. Bernardi, Till Rudack, Joao V. Ribeiro, Angela Barragan, Muyun Lihan, Rezvan Shahoei and Yi Zhang July 12 2017 QwikMD Developers: Joao V. Ribeiro Rafael C. Bernardi Till Rudack A current version of this tutorial is available at http://www.ks.uiuc.edu/Training/Tutorials/ CONTENTS 2 Contents 1 Introduction 3 1.1 NAMD . 3 1.2 QwikMD . 4 2 Required programs 4 2.1 For Linux/Mac Users: . 5 2.2 For Windows Users: . 5 3 Getting Started 5 4 Installing the Required Programs 6 4.1 VMD . 6 4.2 QwikMD . 6 4.3 NAMD . 6 5 Running my First Molecular Dynamics Simulation 7 5.1 Ubiquitin in implicit solvent . 8 5.1.1 Preparing structures and starting simulations . 9 5.1.2 Analyzing during a Live Simulation . 11 5.2 Ubiquitin in a Water Box . 12 5.2.1 Starting a New Simulation . 12 5.2.2 Creating a Salt Solution . 13 5.3 Running your Simulation outside of QwikMD . 14 6 Tackling common scientific problems 15 6.1 Cancer mutation in Ras . 16 6.2 HIV protease . 19 6.3 Proton transport through a membrane by bactheriorhodopsin . 25 7 Steered Molecular Dynamics 31 7.1 Biomolecular interactions during protein unfolding . 31 7.1.1 Preparing a SMD system . 32 7.1.2 Analyzing during a Live Simulation . 33 7.2 Setting-up steered molecular dynamics to study protein complex interaction . -
FORCE FIELDS for PROTEIN SIMULATIONS by JAY W. PONDER
FORCE FIELDS FOR PROTEIN SIMULATIONS By JAY W. PONDER* AND DAVIDA. CASEt *Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, 51. Louis, Missouri 63110, and tDepartment of Molecular Biology, The Scripps Research Institute, La Jolla, California 92037 I. Introduction. ...... .... ... .. ... .... .. .. ........ .. .... .... ........ ........ ..... .... 27 II. Protein Force Fields, 1980 to the Present.............................................. 30 A. The Am.ber Force Fields.............................................................. 30 B. The CHARMM Force Fields ..., ......... 35 C. The OPLS Force Fields............................................................... 38 D. Other Protein Force Fields ....... 39 E. Comparisons Am.ong Protein Force Fields ,... 41 III. Beyond Fixed Atomic Point-Charge Electrostatics.................................... 45 A. Limitations of Fixed Atomic Point-Charges ........ 46 B. Flexible Models for Static Charge Distributions.................................. 48 C. Including Environmental Effects via Polarization................................ 50 D. Consistent Treatment of Electrostatics............................................. 52 E. Current Status of Polarizable Force Fields........................................ 57 IV. Modeling the Solvent Environment .... 62 A. Explicit Water Models ....... 62 B. Continuum Solvent Models.......................................................... 64 C. Molecular Dynamics Simulations with the Generalized Born Model........ -
Force Fields for MD Simulations
Force Fields for MD simulations • Topology/parameter files • Where do the numbers an MD code uses come from? • How to make topology files for ligands, cofactors, special amino acids, … • How to obtain/develop missing parameters. • QM and QM/MM force fields/potential energy descriptions used for molecular simulations. The Potential Energy Function Ubond = oscillations about the equilibrium bond length Uangle = oscillations of 3 atoms about an equilibrium bond angle Udihedral = torsional rotation of 4 atoms about a central bond Unonbond = non-bonded energy terms (electrostatics and Lenard-Jones) Energy Terms Described in the CHARMm Force Field Bond Angle Dihedral Improper Classical Molecular Dynamics r(t +!t) = r(t) + v(t)!t v(t +!t) = v(t) + a(t)!t a(t) = F(t)/ m d F = ! U (r) dr Classical Molecular Dynamics 12 6 &, R ) , R ) # U (r) = . $* min,ij ' - 2* min,ij ' ! 1 qiq j ij * ' * ' U (r) = $ rij rij ! %+ ( + ( " 4!"0 rij Coulomb interaction van der Waals interaction Classical Molecular Dynamics Classical Molecular Dynamics Bond definitions, atom types, atom names, parameters, …. What is a Force Field? In molecular dynamics a molecule is described as a series of charged points (atoms) linked by springs (bonds). To describe the time evolution of bond lengths, bond angles and torsions, also the non-bonding van der Waals and elecrostatic interactions between atoms, one uses a force field. The force field is a collection of equations and associated constants designed to reproduce molecular geometry and selected properties of tested structures. Energy Functions Ubond = oscillations about the equilibrium bond length Uangle = oscillations of 3 atoms about an equilibrium bond angle Udihedral = torsional rotation of 4 atoms about a central bond Unonbond = non-bonded energy terms (electrostatics and Lenard-Jones) Parameter optimization of the CHARMM Force Field Based on the protocol established by Alexander D. -
FORCE FIELDS and CRYSTAL STRUCTURE PREDICTION Contents
FORCE FIELDS AND CRYSTAL STRUCTURE PREDICTION Bouke P. van Eijck ([email protected]) Utrecht University (Retired) Department of Crystal and Structural Chemistry Padualaan 8, 3584 CH Utrecht, The Netherlands Originally written in 2003 Update blind tests 2017 Contents 1 Introduction 2 2 Lattice Energy 2 2.1 Polarcrystals .............................. 4 2.2 ConvergenceAcceleration . 5 2.3 EnergyMinimization .......................... 6 3 Temperature effects 8 3.1 LatticeVibrations............................ 8 4 Prediction of Crystal Structures 9 4.1 Stage1:generationofpossiblestructures . .... 9 4.2 Stage2:selectionoftherightstructure(s) . ..... 11 4.3 Blindtests................................ 14 4.4 Beyondempiricalforcefields. 15 4.5 Conclusions............................... 17 4.6 Update2017............................... 17 1 1 Introduction Everybody who looks at a crystal structure marvels how Nature finds a way to pack complex molecules into space-filling patterns. The question arises: can we understand such packings without doing experiments? This is a great challenge to theoretical chemistry. Most work in this direction uses the concept of a force field. This is just the po- tential energy of a collection of atoms as a function of their coordinates. In principle, this energy can be calculated by quantumchemical methods for a free molecule; even for an entire crystal computations are beginning to be feasible. But for nearly all work a parameterized functional form for the energy is necessary. An ab initio force field is derived from the abovementioned calculations on small model systems, which can hopefully be generalized to other related substances. This is a relatively new devel- opment, and most force fields are empirical: they have been developed to reproduce observed properties as well as possible. There exists a number of more or less time- honored force fields: MM3, CHARMM, AMBER, GROMOS, OPLS, DREIDING.. -
Investigating the Dynamics of Aggregation in Chromophores Used in Organic Photovoltaics with the Help of Simulations
Investigating the Dynamics of Aggregation in Chromophores used in Organic Photovoltaics with the Help of Simulations Von der Universität Bayreuth zur Erlangung des Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) genehmigte Abhandlung von Axel Bourdick geboren in Frankfurt am Main 1. Gutachter: Prof. Dr. Stephan Gekle 2. Gutachter: Prof. Dr. Stephan Kümmel Tag der Einreichung: 20.12.2019 Tag des Kolloquiums: 28.04.2020 When one experiences truth, the madness of finding fault with others disappears. - S. N. Goenka Contents 1 Summary1 2 Introduction6 2.1 Motivation of this dissertation . .6 2.2 Morphology . .8 2.3 Methological details . 12 2.3.1 Molecular dynamics simulations . 12 2.3.2 Free energy and umbrella sampling . 13 2.3.3 Metadynamics . 16 2.3.4 Density functional theory . 17 2.3.5 Model building . 18 3 Overview of the publications 20 3.1 Investigated systems . 20 3.2 Summary and scientific context . 22 3.3 Summary of individual publications . 26 3.3.1 Elucidating Aggregation Pathways in the Donor-Acceptor Type Molecules p-DTS(FBTTh2)2 and p-SIDT(FBTTh2)2 . 26 3.3.2 What is the role of planarity and torsional freedom for ag- gregation in a π-conjugated donor-acceptor model oligomer? 30 3.3.3 Directing the Aggregation of Native Polythiophene during in Situ Polymerization . 33 4 References 37 5 Publications 50 5.1 Elucidating Aggregation Pathways in the Donor-Acceptor Type Molecules p-DTS(FBTTh2)2 and p-SIDT(FBTTh2)2 ......... 52 5.2 What is the role of planarity and torsional freedom for aggregation in a π-conjugated donor-acceptor model oligomer? . -
A Molecular Simulation Study of CO2 Adsorption in Metal-Organic Frameworks
A molecular simulation study of CO2 adsorption in metal-organic frameworks Pan YANG Master of Philosophy (Engineering) Supervisor: Dr Qinghua Zeng Co-Supervisor: Dr Kejun Dong School of Computing, Engineering and Mathematics Western Sydney University Sydney, Australia May 2018 ACKNOWLEDGEMENTS I would like to thank my principal supervisor Dr Qinghua Zeng for offering me the opportunity to do the molecular dynamics research on metal-organic frameworks. I really appreciate his patience, enthusiasm, encouragement and broad knowledge. I was continuously advised and supported by his guidance in all the time of research timeframe and writing of this thesis. I am also grateful for the comments and feedbacks given by my co-supervisor Dr Kejun Dong during my 2-year research period and my thesis writing. Also, I appreciate many friends and visiting scholars for their insightful views and valuable suggestions. Lastly, thanks to the research service team of SCEM and HDR, Western Sydney University for organising conferences and providing administrative and technical support. ii ABSTRACT The increasing carbon dioxide density in the atmosphere has led to the global warming and other environmental issues. Such increase in carbon dioxide comes mainly from the combustion of thousands of tons of fossil fuels (coal, oil and natural gas). Thus, the development of novel materials for CO2 capture, separation and sequestration is becoming critically essential. Many materials including aqueous amine solvent, micro and mesoporous solid substances have been extensively investigated for CO2 absorption/adsorption. It is found that quite a lot of distinct metal-organic frameworks (MOFs) have remarkable CO2 adsorption capacity in room temperature, particularly HKUST-1 and MIL-68(In). -
Dynamics of Ions in a Water Drop Using the AMOEBA Polarizable Force Field Florian Thaunay, Gilles Ohanessian, Carine Clavaguera
Dynamics of ions in a water drop using the AMOEBA polarizable force field Florian Thaunay, Gilles Ohanessian, Carine Clavaguera To cite this version: Florian Thaunay, Gilles Ohanessian, Carine Clavaguera. Dynamics of ions in a water drop using the AMOEBA polarizable force field. Chemical Physics Letters, Elsevier, 2017, 671, pp.131-137. 10.1016/j.cplett.2017.01.024. hal-01999944 HAL Id: hal-01999944 https://hal.archives-ouvertes.fr/hal-01999944 Submitted on 5 Feb 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Chemical Physics Letters 671 (2017) 131–137 Contents lists available at ScienceDirect Chemical Physics Letters journal homepage: www.elsevier.com/locate/cplett Research paper Dynamics of ions in a water drop using the AMOEBA polarizable force field ⇑ Florian Thaunay, Gilles Ohanessian, Carine Clavaguéra LCM, CNRS, Ecole Polytechnique, Université Paris Saclay, 91128 Palaiseau, France article info abstract Article history: Various ions carrying a charge from À2 to +3 were confined in a drop of 100 water molecules as a way to Received 13 October 2016 model coordination properties inside the cluster and at the interface. The behavior of the ions has been In final form 10 January 2017 followed by molecular dynamics with the AMOEBA polarizable force field. -
Trends in Atomistic Simulation Software Usage [1.3]
A LiveCoMS Perpetual Review Trends in atomistic simulation software usage [1.3] Leopold Talirz1,2,3*, Luca M. Ghiringhelli4, Berend Smit1,3 1Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingenierie Chimiques, Valais, École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland; 2Theory and Simulation of Materials (THEOS), Faculté des Sciences et Techniques de l’Ingénieur, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 3National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 4The NOMAD Laboratory at the Fritz Haber Institute of the Max Planck Society and Humboldt University, Berlin, Germany This LiveCoMS document is Abstract Driven by the unprecedented computational power available to scientific research, the maintained online on GitHub at https: use of computers in solid-state physics, chemistry and materials science has been on a continuous //github.com/ltalirz/ rise. This review focuses on the software used for the simulation of matter at the atomic scale. We livecoms-atomistic-software; provide a comprehensive overview of major codes in the field, and analyze how citations to these to provide feedback, suggestions, or help codes in the academic literature have evolved since 2010. An interactive version of the underlying improve it, please visit the data set is available at https://atomistic.software. GitHub repository and participate via the issue tracker. This version dated August *For correspondence: 30, 2021 [email protected] (LT) 1 Introduction Gaussian [2], were already released in the 1970s, followed Scientists today have unprecedented access to computa- by force-field codes, such as GROMOS [3], and periodic tional power.