LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates
Abstract 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...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2020-11-01
|
Series: | Journal of Cheminformatics |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s13321-020-00471-2 |
id |
doaj-d7ad762727154e5c9632923de0c2b23e |
---|---|
record_format |
Article |
spelling |
doaj-d7ad762727154e5c9632923de0c2b23e2020-11-25T03:58:35ZengBMCJournal of Cheminformatics1758-29462020-11-0112111210.1186/s13321-020-00471-2LigGrep: a tool for filtering docked poses to improve virtual-screening hit ratesEmily J. Ha0Cara T. Lwin1Jacob D. Durrant2Department of Biological Sciences, Carnegie Mellon UniversityDepartment of Biological Sciences, University of PittsburghDepartment of Biological Sciences, University of PittsburghAbstract 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/ .http://link.springer.com/article/10.1186/s13321-020-00471-2Virtual screeningComputer-aided drug discoveryComputational biologyFilters |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Emily J. Ha Cara T. Lwin Jacob D. Durrant |
spellingShingle |
Emily J. Ha Cara T. Lwin Jacob D. Durrant LigGrep: a tool for filtering docked poses to improve virtual-screening hit rates Journal of Cheminformatics Virtual screening Computer-aided drug discovery Computational biology Filters |
author_facet |
Emily J. Ha Cara T. Lwin Jacob D. Durrant |
author_sort |
Emily J. Ha |
title |
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_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_sort |
liggrep: a tool for filtering docked poses to improve virtual-screening hit rates |
publisher |
BMC |
series |
Journal of Cheminformatics |
issn |
1758-2946 |
publishDate |
2020-11-01 |
description |
Abstract 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/ . |
topic |
Virtual screening Computer-aided drug discovery Computational biology Filters |
url |
http://link.springer.com/article/10.1186/s13321-020-00471-2 |
work_keys_str_mv |
AT emilyjha liggrepatoolforfilteringdockedposestoimprovevirtualscreeninghitrates AT caratlwin liggrepatoolforfilteringdockedposestoimprovevirtualscreeninghitrates AT jacobddurrant liggrepatoolforfilteringdockedposestoimprovevirtualscreeninghitrates |
_version_ |
1724456324602789888 |