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Crystal structure prediction of flexible molecules using parallel genetic algorithms with a standard force field
Author(s) -
Kim Seonah,
Orendt Anita M.,
Ferraro Marta B.,
Facelli Julio C.
Publication year - 2009
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.21189
Subject(s) - crystal structure prediction , force field (fiction) , algorithm , computer science , crystal (programming language) , sorting , field (mathematics) , genetic algorithm , crystal structure , energy minimization , ranking (information retrieval) , molecule , minification , computational science , artificial intelligence , computational chemistry , crystallography , mathematics , machine learning , chemistry , organic chemistry , pure mathematics , programming language
Abstract This article describes the application of our distributed computing framework for crystal structure prediction (CSP) the modified genetic algorithms for crystal and cluster prediction (MGAC), to predict the crystal structure of flexible molecules using the general Amber force field (GAFF) and the CHARMM program. The MGAC distributed computing framework includes a series of tightly integrated computer programs for generating the molecule's force field, sampling crystal structures using a distributed parallel genetic algorithm and local energy minimization of the structures followed by the classifying, sorting, and archiving of the most relevant structures. Our results indicate that the method can consistently find the experimentally known crystal structures of flexible molecules, but the number of missing structures and poor ranking observed in some crystals show the need for further improvement of the potential. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009