Building Force Fields: An Automatic, Systematic, and Reproducible Approach.

The development of accurate molecular mechanics force fields is a significant challenge that must be addressed for the continued success of molecular simulation. We developed the ForceBalance method to automatically derive accurate force field parameters using flexible combinations of experimental and theoretical reference data. The method is demonstrated in the parametrization of two rigid water models, yielding new parameter sets (TIP3P-FB and TIP4P-FB) that accurately describe many physical properties of water.

[1]  J. Alejandre,et al.  Non-polarizable force field of water based on the dielectric constant: TIP4P/ε. , 2014, The journal of physical chemistry. B.

[2]  Kenneth Levenberg.  A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[3]  Diwakar Shukla,et al.  OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation. , 2013, Journal of chemical theory and computation.

[4]  Yihan Shao,et al.  Dual-basis second-order Moller-Plesset perturbation theory: A reduced-cost reference for correlation calculations. , 2006, The Journal of chemical physics.

[5]  Junmei Wang,et al.  Development and testing of a general amber force field , 2004, J. Comput. Chem..

[6]  W. Wagner,et al.  The IAPWS Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use , 2002 .

[7]  D. Tieleman,et al.  Force fields for classical molecular dynamics. , 2013, Methods in molecular biology.

[8]  Martin Head-Gordon,et al.  The analytical gradient of dual-basis resolution-of-the-identity second-order Møller–Plesset perturbation theory , 2007 .

[9]  Peter M. Kasson,et al.  GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit , 2013, Bioinform..

[10]  D. Marquardt.  An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[11]  W. L. Jorgensen,et al.  Comparison of simple potential functions for simulating liquid water , 1983 .

[12]  John E. Dennis,et al.  Algorithm 573: NL2SOL—An Adaptive Nonlinear Least-Squares Algorithm [E4] , 1981, TOMS.

[13]  Michael R. Shirts,et al.  Statistically optimal analysis of samples from multiple equilibrium states. , 2008, The Journal of chemical physics.

[14]  Martin Head-Gordon,et al.  Advances in Methods and Algorithms in a Modern Quantum Chemistry Program Package , 2006 .

[15]  Pengyu Y. Ren,et al.  The Polarizable Atomic Multipole-based AMOEBA Force Field for Proteins. , 2013, Journal of chemical theory and computation.

[16]  Xiao Zhu,et al.  Recent developments and applications of the CHARMM force fields , 2012, Wiley interdisciplinary reviews. Computational molecular science.

[17]  Per-Ola Norrby,et al.  Automated molecular mechanics parameterization with simultaneous utilization of experimental and quantum mechanical data , 1998, J. Comput. Chem..

[18]  John E. Dennis,et al.  An Adaptive Nonlinear Least-Squares Algorithm , 1977, TOMS.

[19]  Hal Daumé,et al.  A Bayesian statistics approach to multiscale coarse graining. , 2008, The Journal of chemical physics.

[20]  Greg L. Hura,et al.  Development of an improved four-site water model for biomolecular simulations: TIP4P-Ew. , 2004, The Journal of chemical physics.

[21]  T. H. Dunning.  Gaussian basis sets for use in correlated molecular calculations. I. The atoms boron through neon and hydrogen , 1989 .

[22]  C. Vega,et al.  A general purpose model for the condensed phases of water: TIP4P/2005. , 2005, The Journal of chemical physics.

[23]  Gregory A Voth,et al.  A multiscale coarse-graining method for biomolecular systems. , 2005, The journal of physical chemistry. B.

[24]  Jorge J. Moré,et al.  Computing a Trust Region Step , 1983 .

[25]  Douglas Thain,et al.  Work Queue + Python: A Framework For Scalable Scientific Ensemble Applications , 2011 .

[26]  Timothy D. Fenn,et al.  Polarizable atomic multipole X-ray refinement: application to peptide crystals , 2009, Acta crystallographica. Section D, Biological crystallography.

[27]  Pengyu Y. Ren,et al.  Systematic improvement of a classical molecular model of water. , 2013, The journal of physical chemistry. B.

[28]  Martin Head-Gordon,et al.  Non-Covalent Interactions with Dual-Basis Methods: Pairings for Augmented Basis Sets. , 2009, Journal of chemical theory and computation.

[29]  G. Kell.  Density, thermal expansivity, and compressibility of liquid water from 0.deg. to 150.deg.. Correlations and tables for atmospheric pressure and saturation reviewed and expressed on 1968 temperature scale , 1975 .

[30]  S. Erramilli,et al.  Predicting the melting temperature of ice-Ih with only electronic structure information as input. , 2012, The Journal of chemical physics.

[31]  Liliana Wroblewska,et al.  Protein model refinement using an optimized physics-based all-atom force field , 2008, Proceedings of the National Academy of Sciences.

[32]  Lee-Ping Wang,et al.  Systematic Parametrization of Polarizable Force Fields from Quantum Chemistry Data. , 2013, Journal of chemical theory and computation.

[33]  Alexander D. MacKerell,et al.  Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ(1) and χ(2) dihedral angles. , 2012, Journal of chemical theory and computation.

[34]  Di Pierro Michele,et al.  Automated Optimization of Potential Parameters. , 2013, Journal of chemical theory and computation.