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Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation

BACKGROUND: Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem,...

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Autores principales: Liu, Xiaofeng, Bai, Fang, Ouyang, Sisheng, Wang, Xicheng, Li, Honglin, Jiang, Hualiang
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2678094/
https://www.ncbi.nlm.nih.gov/pubmed/19335906
http://dx.doi.org/10.1186/1471-2105-10-101
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author Liu, Xiaofeng
Bai, Fang
Ouyang, Sisheng
Wang, Xicheng
Li, Honglin
Jiang, Hualiang
author_facet Liu, Xiaofeng
Bai, Fang
Ouyang, Sisheng
Wang, Xicheng
Li, Honglin
Jiang, Hualiang
author_sort Liu, Xiaofeng
collection PubMed
description BACKGROUND: Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. RESULTS: The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105–112). Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 Å to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 ± 0.18 seconds per molecule) renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. CONCLUSION: On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms other four multiple conformer generators in the case of reproducing the bioactive conformations against 329 structures. The speed advantage indicates Cyndi is a powerful alternative method for extensive conformational sampling and large-scale conformer database preparation.
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spelling pubmed-26780942009-05-07 Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation Liu, Xiaofeng Bai, Fang Ouyang, Sisheng Wang, Xicheng Li, Honglin Jiang, Hualiang BMC Bioinformatics Methodology Article BACKGROUND: Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. RESULTS: The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105–112). Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 Å to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 ± 0.18 seconds per molecule) renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. CONCLUSION: On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms other four multiple conformer generators in the case of reproducing the bioactive conformations against 329 structures. The speed advantage indicates Cyndi is a powerful alternative method for extensive conformational sampling and large-scale conformer database preparation. BioMed Central 2009-03-31 /pmc/articles/PMC2678094/ /pubmed/19335906 http://dx.doi.org/10.1186/1471-2105-10-101 Text en Copyright © 2009 Liu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Liu, Xiaofeng
Bai, Fang
Ouyang, Sisheng
Wang, Xicheng
Li, Honglin
Jiang, Hualiang
Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation
title Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation
title_full Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation
title_fullStr Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation
title_full_unstemmed Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation
title_short Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation
title_sort cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2678094/
https://www.ncbi.nlm.nih.gov/pubmed/19335906
http://dx.doi.org/10.1186/1471-2105-10-101
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