ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.; Windus, Theresa L.; Dick-Perez, Marilu

doi:10.1021/acs.jcim.6b00654

Title: ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

Journal Article · Thu Feb 23 00:00:00 EST 2017 · Journal of Chemical Information and Modeling

DOI:https://doi.org/10.1021/acs.jcim.6b00654· OSTI ID:1347393

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.; Windus, Theresa L.; Dick-Perez, Marilu

Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides, important for metal extraction chemistry, are parametrized using ParFit.

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Research Organization:: Ames Laboratory (AMES), Ames, IA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: AC02-07CH11358

OSTI ID:: 1347393

Report Number(s):: IS-J-9104

Journal Information:: Journal of Chemical Information and Modeling, Vol. 57, Issue 3; ISSN 1549-9596

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 17 works

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References (47)

Computer modeling of the interactions of complex molecules Kollman, Peter A.; Merz, Kenneth M. Accounts of Chemical Research, Vol. 23, Issue 8 https://doi.org/10.1021/ar00176a002	journal	August 1990
Free energy calculations: Applications to chemical and biochemical phenomena Kollman, Peter. Chemical Reviews, Vol. 93, Issue 7 https://doi.org/10.1021/cr00023a004	journal	November 1993
Free Energy Via Molecular Simulation: Applications to Chemical and Biomolecular Systems Beveridge, D. L.; DiCapua, F. M. Annual Review of Biophysics and Biophysical Chemistry, Vol. 18, Issue 1 https://doi.org/10.1146/annurev.bb.18.060189.002243	journal	June 1989
Computer Simulation of Molecular Dynamics: Methodology, Applications, and Perspectives in Chemistry van Gunsteren, Wilfred F.; Berendsen, Herman J. C. Angewandte Chemie International Edition in English, Vol. 29, Issue 9 https://doi.org/10.1002/anie.199009921	journal	September 1990
Comparison of simple potential functions for simulating liquid water Jorgensen, William L.; Chandrasekhar, Jayaraman; Madura, Jeffry D. The Journal of Chemical Physics, Vol. 79, Issue 2 https://doi.org/10.1063/1.445869	journal	July 1983
First and second derivative matrix elements for the stretching, bending, and torsional energy Miller, Kenneth J.; Hinde, Robert J.; Anderson, Janet Journal of Computational Chemistry, Vol. 10, Issue 1 https://doi.org/10.1002/jcc.540100107	journal	January 1989
Macromodel?an integrated software system for modeling organic and bioorganic molecules using molecular mechanics Mohamadi, Fariborz; Richards, Nigel G. J.; Guida, Wayne C. Journal of Computational Chemistry, Vol. 11, Issue 4 https://doi.org/10.1002/jcc.540110405	journal	May 1990
What determines the van der Waals coefficient β in the LIE (linear interaction energy) method to estimate binding free energies using molecular dynamics simulations? Wang, Wei; Wang, Jian; Kollman, Peter A. Proteins: Structure, Function, and Genetics, Vol. 34, Issue 3 https://doi.org/10.1002/(SICI)1097-0134(19990215)34:3<395::AID-PROT11>3.3.CO;2-W	journal	February 1999
Continuum Solvent Studies of the Stability of RNA Hairpin Loops and Helices Srinivasan, Jayashree; Miller, Jennifer; Kollman, Peter A. Journal of Biomolecular Structure and Dynamics, Vol. 16, Issue 3 https://doi.org/10.1080/07391102.1998.10508279	journal	December 1998
Molecular dynamics and free-energy calculations applied to affinity maturation in antibody 48G7 Chong, L. T.; Duan, Y.; Wang, L. Proceedings of the National Academy of Sciences, Vol. 96, Issue 25 https://doi.org/10.1073/pnas.96.25.14330	journal	December 1999
Computational Alanine Scanning To Probe Protein−Protein Interactions: A Novel Approach To Evaluate Binding Free Energies Massova, Irina; Kollman, Peter A. Journal of the American Chemical Society, Vol. 121, Issue 36 https://doi.org/10.1021/ja990935j	journal	September 1999
Use of MM-PB/SA in estimating the free energies of proteins: Application to native, intermediates, and unfolded villin headpiece Lee, Matthew R.; Duan, Yong; Kollman, Peter A. Proteins: Structure, Function, and Genetics, Vol. 39, Issue 4 https://doi.org/10.1002/(SICI)1097-0134(20000601)39:4<309::AID-PROT40>3.0.CO;2-S	journal	June 2000
Investigating the binding specificity of U1A-RNA by computational mutagenesis Reyes, Carolina M.; Kollman, Peter A. Journal of Molecular Biology, Vol. 295, Issue 1 https://doi.org/10.1006/jmbi.1999.3319	journal	January 2000
The application of three approximate free energy calculations methods to structure based ligand design: Trypsin and its complex with inhibitors Radmer, Randall J.; Kollman, Peter A. Journal of Computer-Aided Molecular Design, Vol. 12, Issue 3, p. 215-227 https://doi.org/10.1023/A:1007905722422	journal	January 1998
Particle mesh Ewald: An N ⋅log( N ) method for Ewald sums in large systems Darden, Tom; York, Darrin; Pedersen, Lee The Journal of Chemical Physics, Vol. 98, Issue 12 https://doi.org/10.1063/1.464397	journal	June 1993
A smooth particle mesh Ewald method Essmann, Ulrich; Perera, Lalith; Berkowitz, Max L. The Journal of Chemical Physics, Vol. 103, Issue 19 https://doi.org/10.1063/1.470117	journal	November 1995
Note on an Approximation Treatment for Many-Electron Systems Møller, Chr.; Plesset, M. S. Physical Review, Vol. 46, Issue 7 https://doi.org/10.1103/PhysRev.46.618	journal	October 1934
Application of a universal force field to metal complexes Rappe, A. K.; Colwell, K. S.; Casewit, C. J. Inorganic Chemistry, Vol. 32, Issue 16 https://doi.org/10.1021/ic00068a012	journal	August 1993
A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules Cornell, Wendy D.; Cieplak, Piotr; Bayly, Christopher I. Journal of the American Chemical Society, Vol. 117, Issue 19 https://doi.org/10.1021/ja00124a002	journal	May 1995
How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules? Wang, Junmei; Cieplak, Piotr; Kollman, Peter A. Journal of Computational Chemistry, Vol. 21, Issue 12 https://doi.org/10.1002/1096-987X(200009)21:12<1049::AID-JCC3>3.0.CO;2-F	journal	January 2000
The OPLS [optimized potentials for liquid simulations] potential functions for proteins, energy minimizations for crystals of cyclic peptides and crambin Jorgensen, William L.; Tirado-Rives, Julian Journal of the American Chemical Society, Vol. 110, Issue 6 https://doi.org/10.1021/ja00214a001	journal	March 1988
Molecular mechanics. The MM3 force field for hydrocarbons. 1 Allinger, Norman L.; Yuh, Young H.; Lii, Jenn Huei Journal of the American Chemical Society, Vol. 111, Issue 23 https://doi.org/10.1021/ja00205a001	journal	November 1989
Molecular mechanics. The MM3 force field for hydrocarbons. 2. Vibrational frequencies and thermodynamics Lii, Jenn Huei; Allinger, Norman L. Journal of the American Chemical Society, Vol. 111, Issue 23 https://doi.org/10.1021/ja00205a002	journal	November 1989
Molecular mechanics. The MM3 force field for hydrocarbons. 3. The van der Waals' potentials and crystal data for aliphatic and aromatic hydrocarbons Lii, Jenn Huei; Allinger, Norman L. Journal of the American Chemical Society, Vol. 111, Issue 23 https://doi.org/10.1021/ja00205a003	journal	November 1989
Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94 Halgren, Thomas A. Journal of Computational Chemistry, Vol. 17, Issue 5-6 https://doi.org/10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P	journal	April 1996
An Empirical Polarizable Force Field Based on the Classical Drude Oscillator Model: Development History and Recent Applications Lemkul, Justin A.; Huang, Jing; Roux, Benoît Chemical Reviews, Vol. 116, Issue 9 https://doi.org/10.1021/acs.chemrev.5b00505	journal	January 2016
Potential energy functions: From consistent force fields to spectroscopically determined polarizable force fields Palmo, Kim; Mannfors, Berit; Mirkin, Noemi G. Biopolymers, Vol. 68, Issue 3 https://doi.org/10.1002/bip.10254	journal	February 2003
Effective force fields for condensed phase systems from ab initio molecular dynamics simulation: A new method for force-matching Izvekov, Sergei; Parrinello, Michele; Burnham, Christian J. The Journal of Chemical Physics, Vol. 120, Issue 23 https://doi.org/10.1063/1.1739396	journal	June 2004
Multiscale coarse graining of liquid-state systems Izvekov, Sergei; Voth, Gregory A. The Journal of Chemical Physics, Vol. 123, Issue 13 https://doi.org/10.1063/1.2038787	journal	October 2005
Potfit: effective potentials from ab initio data Brommer, Peter; Gähler, Franz Modelling and Simulation in Materials Science and Engineering, Vol. 15, Issue 3 https://doi.org/10.1088/0965-0393/15/3/008	journal	March 2007
Automated molecular mechanics parameterization with simultaneous utilization of experimental and quantum mechanical data Norrby, Per-Ola; Liljefors, Tommy Journal of Computational Chemistry, Vol. 19, Issue 10 https://doi.org/10.1002/(SICI)1096-987X(19980730)19:10<1146::AID-JCC4>3.0.CO;2-M	journal	July 1998
Automatic parameterization of force fields for liquids by simplex optimization Faller, Roland; Schmitz, Heiko; Biermann, Oliver Journal of Computational Chemistry, Vol. 20, Issue 10 https://doi.org/10.1002/(SICI)1096-987X(19990730)20:10<1009::AID-JCC3>3.0.CO;2-C	journal	July 1999
Automated conformational energy fitting for force-field development Guvench, Olgun; MacKerell, Alexander D. Journal of Molecular Modeling, Vol. 14, Issue 8 https://doi.org/10.1007/s00894-008-0305-0	journal	May 2008
Automatic parameterization of force field by systematic search and genetic algorithms Wang, Junmei; Kollman, Peter A. Journal of Computational Chemistry, Vol. 22, Issue 12 https://doi.org/10.1002/jcc.1079	journal	January 2001
Determination of best-fit potential parameters for a reactive force field using a genetic algorithm Pahari, Poonam; Chaturvedi, Shashank Journal of Molecular Modeling, Vol. 18, Issue 3 https://doi.org/10.1007/s00894-011-1124-2	journal	June 2011
Using PC clusters to evaluate the transferability of molecular mechanics force fields for proteins Okur, Asim; Strockbine, Bentley; Hornak, Viktor Journal of Computational Chemistry, Vol. 24, Issue 1 https://doi.org/10.1002/jcc.10184	journal	December 2002
MM3 parametrization of four- and five-coordinated rhenium complexes by a genetic algorithm-Which factors influence the optimization performance? Strassner, Thomas; Busold, Markus; Herrmann, Wolfgang A. Journal of Computational Chemistry, Vol. 23, Issue 2 https://doi.org/10.1002/jcc.10000	journal	January 2002
Systematic First Principles Parameterization of Force Fields for Metal−Organic Frameworks using a Genetic Algorithm Approach Tafipolsky, Maxim; Schmid, Rochus The Journal of Physical Chemistry B, Vol. 113, Issue 5 https://doi.org/10.1021/jp807487f	journal	February 2009
Systematic Parametrization of Polarizable Force Fields from Quantum Chemistry Data Wang, Lee-Ping; Chen, Jiahao; Van Voorhis, Troy Journal of Chemical Theory and Computation, Vol. 9, Issue 1 https://doi.org/10.1021/ct300826t	journal	November 2012
Building Force Fields: An Automatic, Systematic, and Reproducible Approach Wang, Lee-Ping; Martinez, Todd J.; Pande, Vijay S. The Journal of Physical Chemistry Letters, Vol. 5, Issue 11 https://doi.org/10.1021/jz500737m	journal	May 2014
Paramfit: Automated optimization of force field parameters for molecular dynamics simulations Betz, Robin M.; Walker, Ross C. Journal of Computational Chemistry, Vol. 36, Issue 2 https://doi.org/10.1002/jcc.23775	journal	November 2014
Deriving force field parameters for coordination complexes Norrby, P. Coordination Chemistry Reviews, Vol. 212, Issue 1 https://doi.org/10.1016/S0010-8545(00)00296-4	journal	February 2001
General atomic and molecular electronic structure system Schmidt, Michael W.; Baldridge, Kim K.; Boatz, Jerry A. Journal of Computational Chemistry, Vol. 14, Issue 11, p. 1347-1363 https://doi.org/10.1002/jcc.540141112	journal	November 1993
Advances in electronic structure theory Gordon, Mark S.; Schmidt, Michael W. Theory and Applications of Computational Chemistry https://doi.org/10.1016/B978-044451719-7/50084-6	book	January 2005
NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations Valiev, M.; Bylaska, E. J.; Govind, N. Computer Physics Communications, Vol. 181, Issue 9, p. 1477-1489 https://doi.org/10.1016/j.cpc.2010.04.018	journal	September 2010
A comparison of conformational energies calculated by several molecular mechanics methods Gundertofte, Klaus; Liljefors, Tommy; Norrby, Per-ola Journal of Computational Chemistry, Vol. 17, Issue 4 https://doi.org/10.1002/(SICI)1096-987X(199603)17:4<429::AID-JCC5>3.0.CO;2-W	journal	March 1996
Macmolplt: a graphical user interface for GAMESS Bode, Brett M.; Gordon, Mark S. Journal of Molecular Graphics and Modelling, Vol. 16, Issue 3, p. 133-138 https://doi.org/10.1016/S1093-3263(99)00002-9	journal	June 1998

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