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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...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2009
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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. |
format | Text |
id | pubmed-2746282 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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