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LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates
Structure-based virtual screening (VS) uses computer docking to prioritize candidate small-molecule ligands for subsequent experimental testing. Docking programs evaluate molecular binding in part by predicting the geometry with which a given compound might bind a target receptor (e.g., the docked “...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7656723/ https://www.ncbi.nlm.nih.gov/pubmed/33292486 http://dx.doi.org/10.1186/s13321-020-00471-2 |
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author | Ha, Emily J. Lwin, Cara T. Durrant, Jacob D. |
author_facet | Ha, Emily J. Lwin, Cara T. Durrant, Jacob D. |
author_sort | Ha, Emily J. |
collection | PubMed |
description | Structure-based virtual screening (VS) uses computer docking to prioritize candidate small-molecule ligands for subsequent experimental testing. Docking programs evaluate molecular binding in part by predicting the geometry with which a given compound might bind a target receptor (e.g., the docked “pose” relative to a protein target). Candidate ligands predicted to participate in the same intermolecular interactions typical of known ligands (or ligands that bind related proteins) are arguably more likely to be true binders. Some docking programs allow users to apply constraints during the docking process with the goal of prioritizing these critical interactions. But these programs often have restrictive and/or expensive licenses, and many popular open-source docking programs (e.g., AutoDock Vina) lack this important functionality. We present LigGrep, a free, open-source program that addresses this limitation. As input, LigGrep accepts a protein receptor file, a directory containing many docked-compound files, and a list of user-specified filters describing critical receptor/ligand interactions. LigGrep evaluates each docked pose and outputs the names of the compounds with poses that pass all filters. To demonstrate utility, we show that LigGrep can improve the hit rates of test VS targeting H. sapiens poly(ADPribose) polymerase 1 (HsPARP1), H. sapiens peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (HsPin1p), and S. cerevisiae hexokinase-2 (ScHxk2p). We hope that LigGrep will be a useful tool for the computational biology community. A copy is available free of charge at http://durrantlab.com/liggrep/. |
format | Online Article Text |
id | pubmed-7656723 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-76567232020-11-12 LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates Ha, Emily J. Lwin, Cara T. Durrant, Jacob D. J Cheminform Software Structure-based virtual screening (VS) uses computer docking to prioritize candidate small-molecule ligands for subsequent experimental testing. Docking programs evaluate molecular binding in part by predicting the geometry with which a given compound might bind a target receptor (e.g., the docked “pose” relative to a protein target). Candidate ligands predicted to participate in the same intermolecular interactions typical of known ligands (or ligands that bind related proteins) are arguably more likely to be true binders. Some docking programs allow users to apply constraints during the docking process with the goal of prioritizing these critical interactions. But these programs often have restrictive and/or expensive licenses, and many popular open-source docking programs (e.g., AutoDock Vina) lack this important functionality. We present LigGrep, a free, open-source program that addresses this limitation. As input, LigGrep accepts a protein receptor file, a directory containing many docked-compound files, and a list of user-specified filters describing critical receptor/ligand interactions. LigGrep evaluates each docked pose and outputs the names of the compounds with poses that pass all filters. To demonstrate utility, we show that LigGrep can improve the hit rates of test VS targeting H. sapiens poly(ADPribose) polymerase 1 (HsPARP1), H. sapiens peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (HsPin1p), and S. cerevisiae hexokinase-2 (ScHxk2p). We hope that LigGrep will be a useful tool for the computational biology community. A copy is available free of charge at http://durrantlab.com/liggrep/. Springer International Publishing 2020-11-11 /pmc/articles/PMC7656723/ /pubmed/33292486 http://dx.doi.org/10.1186/s13321-020-00471-2 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Ha, Emily J. Lwin, Cara T. Durrant, Jacob D. LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates |
title | LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates |
title_full | LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates |
title_fullStr | LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates |
title_full_unstemmed | LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates |
title_short | LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates |
title_sort | liggrep: a tool for filtering docked poses to improve virtual-screening hit rates |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7656723/ https://www.ncbi.nlm.nih.gov/pubmed/33292486 http://dx.doi.org/10.1186/s13321-020-00471-2 |
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