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High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations

Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtain...

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Autores principales: Okimoto, Noriaki, Futatsugi, Noriyuki, Fuji, Hideyoshi, Suenaga, Atsushi, Morimoto, Gentaro, Yanai, Ryoko, Ohno, Yousuke, Narumi, Tetsu, Taiji, Makoto
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2746282/
https://www.ncbi.nlm.nih.gov/pubmed/19816553
http://dx.doi.org/10.1371/journal.pcbi.1000528
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author Okimoto, Noriaki
Futatsugi, Noriyuki
Fuji, Hideyoshi
Suenaga, Atsushi
Morimoto, Gentaro
Yanai, Ryoko
Ohno, Yousuke
Narumi, Tetsu
Taiji, Makoto
author_facet Okimoto, Noriaki
Futatsugi, Noriyuki
Fuji, Hideyoshi
Suenaga, Atsushi
Morimoto, Gentaro
Yanai, Ryoko
Ohno, Yousuke
Narumi, Tetsu
Taiji, Makoto
author_sort Okimoto, Noriaki
collection PubMed
description Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtained by molecular docking in order to improve the enrichment performance of molecular docking. Our screening approach employed the molecular mechanics/Poisson-Boltzmann and surface area method to estimate the binding free energies. For the top-ranking 1,000 compounds obtained by docking to a target protein, approximately 6,000 molecular dynamics simulations were performed using multiple docking poses in about a week. As a result, the enrichment performance of the top 100 compounds by our approach was improved by 1.6–4.0 times that of the enrichment performance of molecular dockings. This result indicates that the application of molecular dynamics simulations to virtual screening for lead discovery is both effective and practical. However, further optimization of the computational protocols is required for screening various target proteins.
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spelling pubmed-27462822009-10-09 High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations Okimoto, Noriaki Futatsugi, Noriyuki Fuji, Hideyoshi Suenaga, Atsushi Morimoto, Gentaro Yanai, Ryoko Ohno, Yousuke Narumi, Tetsu Taiji, Makoto PLoS Comput Biol Research Article Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, this method is not completely reliable and therefore unsatisfactory. In this study, we used massive molecular dynamics simulations of protein-ligand conformations obtained by molecular docking in order to improve the enrichment performance of molecular docking. Our screening approach employed the molecular mechanics/Poisson-Boltzmann and surface area method to estimate the binding free energies. For the top-ranking 1,000 compounds obtained by docking to a target protein, approximately 6,000 molecular dynamics simulations were performed using multiple docking poses in about a week. As a result, the enrichment performance of the top 100 compounds by our approach was improved by 1.6–4.0 times that of the enrichment performance of molecular dockings. This result indicates that the application of molecular dynamics simulations to virtual screening for lead discovery is both effective and practical. However, further optimization of the computational protocols is required for screening various target proteins. Public Library of Science 2009-10-09 /pmc/articles/PMC2746282/ /pubmed/19816553 http://dx.doi.org/10.1371/journal.pcbi.1000528 Text en Okimoto et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Okimoto, Noriaki
Futatsugi, Noriyuki
Fuji, Hideyoshi
Suenaga, Atsushi
Morimoto, Gentaro
Yanai, Ryoko
Ohno, Yousuke
Narumi, Tetsu
Taiji, Makoto
High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations
title High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations
title_full High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations
title_fullStr High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations
title_full_unstemmed High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations
title_short High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations
title_sort high-performance drug discovery: computational screening by combining docking and molecular dynamics simulations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2746282/
https://www.ncbi.nlm.nih.gov/pubmed/19816553
http://dx.doi.org/10.1371/journal.pcbi.1000528
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