First-Principles Molecular Structure Search with a Genetic Algorithm.

Published

Journal Article

The identification of low-energy conformers for a given molecule is a fundamental problem in computational chemistry and cheminformatics. We assess here a conformer search that employs a genetic algorithm for sampling the low-energy segment of the conformation space of molecules. The algorithm is designed to work with first-principles methods, facilitated by the incorporation of local optimization and blacklisting conformers to prevent repeated evaluations of very similar solutions. The aim of the search is not only to find the global minimum but to predict all conformers within an energy window above the global minimum. The performance of the search strategy is (i) evaluated for a reference data set extracted from a database with amino acid dipeptide conformers obtained by an extensive combined force field and first-principles search and (ii) compared to the performance of a systematic search and a random conformer generator for the example of a drug-like ligand with 43 atoms, 8 rotatable bonds, and 1 cis/trans bond.

Full Text

Duke Authors

Cited Authors

  • Supady, A; Blum, V; Baldauf, C

Published Date

  • November 2, 2015

Published In

Volume / Issue

  • 55 / 11

Start / End Page

  • 2338 - 2348

PubMed ID

  • 26484612

Pubmed Central ID

  • 26484612

Electronic International Standard Serial Number (EISSN)

  • 1549-960X

International Standard Serial Number (ISSN)

  • 1549-9596

Digital Object Identifier (DOI)

  • 10.1021/acs.jcim.5b00243

Language

  • eng