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

TitleParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data
Publication TypeJournal Article
Year of Publication2017
AuthorsZahariev, F, De Silva, N, Gordon, MS, Windus, TL, Dick-Perez, M
JournalJournal of Chemical Information and Modeling
Volume57
Pagination391-396
Date Published03
Type of ArticleArticle
ISBN Number1549-9596
Accession NumberWOS:000397838100002
Keywordsautomatic parameterization, binding free-energies, chemistry, Computer Science, conformational energies, continuum solvent, dynamics simulations, free-energy calculations, Genetic algorithm, mm3 force-field, particle mesh ewald, Pharmacy, potential functions
Abstract

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. ParFit is in an open source program available for free on GitHub (https://github.com/fzahari/ParFit).

DOI10.1021/acs.jcim.6b00654
Custom 1

CMI

Short TitleJ. Chem Inf. Model.
Alternate JournalJ. Chem Inf. Model.