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Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening

The quest for effective virtual screening algorithms is hindered by the scarcity of training data, calling for innovative approaches. This study presents the use of experimental electron density (ED) data for improving active compound enrichment in virtual screening, supported by ED’s ability to ref...

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Autores principales: Ma, Wenzhi, Zhang, Wei, Le, Yuan, Shi, Xiaoxuan, Xu, Qingbo, Xiao, Yang, Dou, Yueying, Wang, Xiaoman, Zhou, Wenbiao, Peng, Wei, Zhang, Hongbo, Huang, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444862/
https://www.ncbi.nlm.nih.gov/pubmed/37608192
http://dx.doi.org/10.1038/s42004-023-00984-5
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author Ma, Wenzhi
Zhang, Wei
Le, Yuan
Shi, Xiaoxuan
Xu, Qingbo
Xiao, Yang
Dou, Yueying
Wang, Xiaoman
Zhou, Wenbiao
Peng, Wei
Zhang, Hongbo
Huang, Bo
author_facet Ma, Wenzhi
Zhang, Wei
Le, Yuan
Shi, Xiaoxuan
Xu, Qingbo
Xiao, Yang
Dou, Yueying
Wang, Xiaoman
Zhou, Wenbiao
Peng, Wei
Zhang, Hongbo
Huang, Bo
author_sort Ma, Wenzhi
collection PubMed
description The quest for effective virtual screening algorithms is hindered by the scarcity of training data, calling for innovative approaches. This study presents the use of experimental electron density (ED) data for improving active compound enrichment in virtual screening, supported by ED’s ability to reflect the time-averaged behavior of ligands and solvents in the binding pocket. Experimental ED-based grid matching score (ExptGMS) was developed to score compounds by measuring the degree of matching between their binding conformations and a series of multi-resolution experimental ED grids. The efficiency of ExptGMS was validated using both in silico tests with the Directory of Useful Decoys-Enhanced dataset and wet-lab tests on Covid-19 3CLpro-inhibitors. ExptGMS improved the active compound enrichment in top-ranked molecules by approximately 20%. Furthermore, ExptGMS identified four active inhibitors of 3CLpro, with the most effective showing an IC(50) value of 1.9 µM. We also developed an online database containing experimental ED grids for over 17,000 proteins to facilitate the use of ExptGMS for academic users.
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spelling pubmed-104448622023-08-24 Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening Ma, Wenzhi Zhang, Wei Le, Yuan Shi, Xiaoxuan Xu, Qingbo Xiao, Yang Dou, Yueying Wang, Xiaoman Zhou, Wenbiao Peng, Wei Zhang, Hongbo Huang, Bo Commun Chem Article The quest for effective virtual screening algorithms is hindered by the scarcity of training data, calling for innovative approaches. This study presents the use of experimental electron density (ED) data for improving active compound enrichment in virtual screening, supported by ED’s ability to reflect the time-averaged behavior of ligands and solvents in the binding pocket. Experimental ED-based grid matching score (ExptGMS) was developed to score compounds by measuring the degree of matching between their binding conformations and a series of multi-resolution experimental ED grids. The efficiency of ExptGMS was validated using both in silico tests with the Directory of Useful Decoys-Enhanced dataset and wet-lab tests on Covid-19 3CLpro-inhibitors. ExptGMS improved the active compound enrichment in top-ranked molecules by approximately 20%. Furthermore, ExptGMS identified four active inhibitors of 3CLpro, with the most effective showing an IC(50) value of 1.9 µM. We also developed an online database containing experimental ED grids for over 17,000 proteins to facilitate the use of ExptGMS for academic users. Nature Publishing Group UK 2023-08-22 /pmc/articles/PMC10444862/ /pubmed/37608192 http://dx.doi.org/10.1038/s42004-023-00984-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ma, Wenzhi
Zhang, Wei
Le, Yuan
Shi, Xiaoxuan
Xu, Qingbo
Xiao, Yang
Dou, Yueying
Wang, Xiaoman
Zhou, Wenbiao
Peng, Wei
Zhang, Hongbo
Huang, Bo
Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening
title Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening
title_full Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening
title_fullStr Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening
title_full_unstemmed Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening
title_short Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening
title_sort using macromolecular electron densities to improve the enrichment of active compounds in virtual screening
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444862/
https://www.ncbi.nlm.nih.gov/pubmed/37608192
http://dx.doi.org/10.1038/s42004-023-00984-5
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