A computational study of cooperative binding to multiple SARS-CoV-2 proteins

Abstract Structure-based drug design targeting the SARS-CoV-2 virus has been greatly facilitated by available virus-related protein structures. However, there is an urgent need for effective, safe small-molecule drugs to control the spread of the virus and variants. While many efforts are devoted to...

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Autores principales:	Jianing Li, Kyle T. McKay, Jacob M. Remington, Severin T. Schneebeli
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2821bc4e151f414ba4c52588287f8f20
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spelling	oai:doaj.org-article:2821bc4e151f414ba4c52588287f8f202021-12-02T16:27:55ZA computational study of cooperative binding to multiple SARS-CoV-2 proteins10.1038/s41598-021-95826-62045-2322https://doaj.org/article/2821bc4e151f414ba4c52588287f8f202021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95826-6https://doaj.org/toc/2045-2322Abstract Structure-based drug design targeting the SARS-CoV-2 virus has been greatly facilitated by available virus-related protein structures. However, there is an urgent need for effective, safe small-molecule drugs to control the spread of the virus and variants. While many efforts are devoted to searching for compounds that selectively target individual proteins, we investigated the potential interactions between eight proteins related to SARS-CoV-2 and more than 600 compounds from a traditional Chinese medicine which has proven effective at treating the viral infection. Our original ensemble docking and cooperative docking approaches, followed by a total of over 16-micorsecond molecular simulations, have identified at least 9 compounds that may generally bind to key SARS-CoV-2 proteins. Further, we found evidence that some of these compounds can simultaneously bind to the same target, potentially leading to cooperative inhibition to SARS-CoV-2 proteins like the Spike protein and the RNA-dependent RNA polymerase. These results not only present a useful computational methodology to systematically assess the anti-viral potential of small molecules, but also point out a new avenue to seek cooperative compounds toward cocktail therapeutics to target more SARS-CoV-2-related proteins.Jianing LiKyle T. McKayJacob M. RemingtonSeverin T. SchneebeliNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jianing Li Kyle T. McKay Jacob M. Remington Severin T. Schneebeli A computational study of cooperative binding to multiple SARS-CoV-2 proteins
description	Abstract Structure-based drug design targeting the SARS-CoV-2 virus has been greatly facilitated by available virus-related protein structures. However, there is an urgent need for effective, safe small-molecule drugs to control the spread of the virus and variants. While many efforts are devoted to searching for compounds that selectively target individual proteins, we investigated the potential interactions between eight proteins related to SARS-CoV-2 and more than 600 compounds from a traditional Chinese medicine which has proven effective at treating the viral infection. Our original ensemble docking and cooperative docking approaches, followed by a total of over 16-micorsecond molecular simulations, have identified at least 9 compounds that may generally bind to key SARS-CoV-2 proteins. Further, we found evidence that some of these compounds can simultaneously bind to the same target, potentially leading to cooperative inhibition to SARS-CoV-2 proteins like the Spike protein and the RNA-dependent RNA polymerase. These results not only present a useful computational methodology to systematically assess the anti-viral potential of small molecules, but also point out a new avenue to seek cooperative compounds toward cocktail therapeutics to target more SARS-CoV-2-related proteins.
format	article
author	Jianing Li Kyle T. McKay Jacob M. Remington Severin T. Schneebeli
author_facet	Jianing Li Kyle T. McKay Jacob M. Remington Severin T. Schneebeli
author_sort	Jianing Li
title	A computational study of cooperative binding to multiple SARS-CoV-2 proteins
title_short	A computational study of cooperative binding to multiple SARS-CoV-2 proteins
title_full	A computational study of cooperative binding to multiple SARS-CoV-2 proteins
title_fullStr	A computational study of cooperative binding to multiple SARS-CoV-2 proteins
title_full_unstemmed	A computational study of cooperative binding to multiple SARS-CoV-2 proteins
title_sort	computational study of cooperative binding to multiple sars-cov-2 proteins
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/2821bc4e151f414ba4c52588287f8f20
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A computational study of cooperative binding to multiple SARS-CoV-2 proteins

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