Towards Exact Molecular Dynamics Simulations with Machine-Learned Force fields
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Using Constrained Density Functional Theory to Track Proton Transfers and to Sample Their Associated Free Energy Surface
Using Constrained Density Functional Theory to Track Proton Transfers and to Sample Their Associated Free Energy Surface Chenghan Li and Gregory A. Voth* Department of Chemistry, Chicago Center for Theoretical Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, University of Chicago, Chicago, IL, 60637 Keywords: free energy sampling, proton transport, density functional theory, proton transfer ABSTRACT: The ab initio molecular dynamics (AIMD) and quantum mechanics/molecular mechanics (QM/MM) methods are powerful tools for studying proton solvation, transfer, and transport processes in various environments. However, due to the high computational cost of such methods, achieving sufficient sampling of rare events involving excess proton motion – especially when Grotthuss proton shuttling is involved – usually requires enhanced free energy sampling methods to obtain informative results. Moreover, an appropriate collective variable (CV) that describes the effective position of the net positive charge defect associated with an excess proton is essential for both tracking the trajectory of the defect and for the free energy sampling of the processes associated with the resulting proton transfer and transport. In this work, such a CV is derived from first principles using constrained density functional theory (CDFT). This CV is applicable to a broad array of proton transport and transfer processes as studied via AIMD and QM/MM simulation. 1 INTRODUCTION The accurate and efficient delineation of proton transport (PT) and -
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 -
Molecular Dynamics Study of the Stress–Strain Behavior of Carbon-Nanotube Reinforced Epon 862 Composites R
Materials Science and Engineering A 447 (2007) 51–57 Molecular dynamics study of the stress–strain behavior of carbon-nanotube reinforced Epon 862 composites R. Zhu a,E.Pana,∗, A.K. Roy b a Department of Civil Engineering, University of Akron, Akron, OH 44325, USA b Materials and Manufacturing Directorate, Air Force Research Laboratory, AFRL/MLBC, Wright-Patterson Air Force Base, OH 45433, USA Received 9 March 2006; received in revised form 2 August 2006; accepted 20 October 2006 Abstract Single-walled carbon nanotubes (CNTs) are used to reinforce epoxy Epon 862 matrix. Three periodic systems – a long CNT-reinforced Epon 862 composite, a short CNT-reinforced Epon 862 composite, and the Epon 862 matrix itself – are studied using the molecular dynamics. The stress–strain relations and the elastic Young’s moduli along the longitudinal direction (parallel to CNT) are simulated with the results being also compared to those from the rule-of-mixture. Our results show that, with increasing strain in the longitudinal direction, the Young’s modulus of CNT increases whilst that of the Epon 862 composite or matrix decreases. Furthermore, a long CNT can greatly improve the Young’s modulus of the Epon 862 composite (about 10 times stiffer), which is also consistent with the prediction based on the rule-of-mixture at low strain level. Even a short CNT can also enhance the Young’s modulus of the Epon 862 composite, with an increment of 20% being observed as compared to that of the Epon 862 matrix. © 2006 Elsevier B.V. All rights reserved. Keywords: Carbon nanotube; Epon 862; Nanocomposite; Molecular dynamics; Stress–strain curve 1. -
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. -
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. -
The Fip35 WW Domain Folds with Structural and Mechanistic Heterogeneity in Molecular Dynamics Simulations
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Biophysical Journal Volume 96 April 2009 L53–L55 L53 The Fip35 WW Domain Folds with Structural and Mechanistic Heterogeneity in Molecular Dynamics Simulations Daniel L. Ensign and Vijay S. Pande* Department of Chemistry, Stanford University, Stanford, California ABSTRACT We describe molecular dynamics simulations resulting in the folding the Fip35 Hpin1 WW domain. The simulations were run on a distributed set of graphics processors, which are capable of providing up to two orders of magnitude faster compu- tation than conventional processors. Using the Folding@home distributed computing system, we generated thousands of inde- pendent trajectories in an implicit solvent model, totaling over 2.73 ms of simulations. A small number of these trajectories folded; the folding proceeded along several distinct routes and the system folded into two distinct three-stranded b-sheet conformations, showing that the folding mechanism of this system is distinctly heterogeneous. Received for publication 8 September 2008 and in final form 22 January 2009. *Correspondence: [email protected] Because b-sheets are a ubiquitous protein structural motif, tories on the distributed computing environment, Folding@ understanding how they fold is imperative in solving the home (5). For these calculations, we utilized graphics pro- protein folding problem. Liu et al. (1) recently made a heroic cessing units (ATI Technologies; Sunnyvale, CA), deployed set of measurements of the folding kinetics of 35 three- by the Folding@home contributors. Using optimized code, stranded b-sheet sequences derived from the Hpin1 WW individual graphics processing units (GPUs) of the type domain. -
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.. -
Computational Biophysics: Introduction
Computational Biophysics: Introduction Bert de Groot, Jochen Hub, Helmut Grubmüller Max Planck-Institut für biophysikalische Chemie Theoretische und Computergestützte Biophysik Am Fassberg 11 37077 Göttingen Tel.: 201-2308 / 2314 / 2301 / 2300 (Secr.) Email: [email protected] [email protected] [email protected] www.mpibpc.mpg.de/grubmueller/ Chloroplasten, Tylakoid-Membran From: X. Hu et al., PNAS 95 (1998) 5935 Primary steps in photosynthesis F-ATP Synthase 20 nm F1-ATP(synth)ase ATP hydrolysis drives rotation of γ subunit and attached actin filament F1-ATP(synth)ase NO INERTIA! Proteins are Molecular Nano-Machines ! Elementary steps: Conformational motions Overview: Computational Biophysics: Introduction L1/P1: Introduction, protein structure and function, molecular dynamics, approximations, numerical integration, argon L2/P2: Tertiary structure, force field contributions, efficient algorithms, electrostatics methods, protonation, periodic boundaries, solvent, ions, NVT/NPT ensembles, analysis L3/P3: Protein data bank, structure determination by NMR / x-ray; refinement L4/P4: Monte Carlo, normal mode analysis, principal components L5/P5: Bioinformatics: sequence alignment, Structure prediction, homology modelling L6/P6: Charge transfer & photosynthesis, electrostatics methods L7/P7: Aquaporin / ATPase: two examples from current research Overview: Computational Biophysics: Concepts & Methods L08/P08: MD Simulation & Markov Theory: Molecular Machines L09/P09: Free energy calculations: Molecular recognition L10/P10: Non-equilibrium thermodynamics: -
Introduction to Computational Chemistry: Molecular Dynamics
Introduction to Computational Chemistry: Molecular Dynamics Alexander B. Pacheco User Services Consultant LSU HPC & LONI [email protected] LSU HPC Training Series Louisiana State University April 27, 2011 High Performance Computing @ Louisiana State University - http://www.hpc.lsu.edu April 27, 2011 1/39 Outline 1 Tutorial Goals 2 Introduction 3 Molecular Dynamics 4 Fundamentals of Molecular Dynamics 5 Ab Initio Molecular Dynamics Theory 6 Computational Chemistry Programs 7 Example Jobs High Performance Computing @ Louisiana State University - http://www.hpc.lsu.edu April 27, 2011 2/39 Tutorial Goals Cover the fundamentals of Molecular Dynamics Simulation: Ab-Initio and Classical. Expose researchers to the theory and computational packages used for MD simulations. Worked out examples for various computational packages such as CPMD, Gaussian, GAMESS and NWCHEM. Linux machines, LONI and LSU HPC at /home/apacheco/CompChem. Go ahead with the examples if you want but hold off all questions until tutorial is complete. My Background: Ab-Initio Molecular Dynamics. Questions about examples/tutorials and/or using Electronic Structure codes for AIMD, email me at [email protected] or [email protected] High Performance Computing @ Louisiana State University - http://www.hpc.lsu.edu April 27, 2011 3/39 What is Computational Chemistry Computational Chemistry is a branch of chemistry that uses principles of computer science to assist in solving chemical problems. Uses the results of theoretical chemistry, incorporated into efficient computer programs. Application to single molecule, groups of molecules, liquids or solids. Calculates the structure and properties such as relative energies, charge distributions, dipole and multipole moments, spectroscopy, reactivity, etc. -
Molecular Dynamics Simulations
LECTURE 6 : BASICS FOR MOLECULAR SIMULATIONS - Historical perspective - Skimming over Statistical Mechanics - General idea of Molecular Dynamics - Force calculations, structure of MD, equations of motion - Statistical Ensembles [email protected] Atomic modeling of glass – LECTURE4 MD BASICS What we want to avoid … Computing the radial distribution function of vitreous SiO 2 from a ball and stick model Bell and Dean, 1972 [email protected] Atomic modeling of glass – LECTURE4 MD BASICS 1972 … and the historical perspective of molecular simulations ~1900 Concept of force field in the analysis of spectroscopy 1929 Model vibrationl excitations: atomic potentials (P.M. Morse and J.E. Lennard- Jones ) 1937 London dispersion forces due to polarisation (origin Van der Waals forces), 1946 Molecular Mechanics: use of Newton’s equations and force fields for the caracterization of molecular conformations 1953 Monte Carlo simulations after the Manhattan project (1943): computation of thermodynamic properties (Metropolis, Van Neuman, Teller, Fermi ) 1957 Hard sphere MD simulations (Alder-Wainwright) : Potential non-differentiable, no force calculations, free flight during collisions, momentum balance. Event-driven algorithms [email protected] Atomic modeling of glass – LECTURE4 MD BASICS 1964 LJ MD of liquid Argon (Rahman): differentiable potential, solve Newton’s equation of motion, accurate trajectories. Contains already the main ingredients of modern simulations 1970s Simulation of liquids (water, molten salts and metals,…) -
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.