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An Enhanced Hybrid Screening Approach to Identify Potent Inhibitors for the SARS-CoV-2 Main Protease From the NCI Compound Library

The emergence and rapid spread of SARS-CoV-2, the pathogen of COVID-19, have caused a worldwide public health crisis. The SARS-CoV-2 main protease (Mpro) is an essential enzyme for the virus and therefore an appealing target for the development of antivirals to treat COVID-19 patients. Recently, man...

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Autores principales: Li, Shuhua G., Yang, Kai S., Blankenship, Lauren R., Cho, Chia-Chuan D., Xu, Shiqing, Wang, Hongbin, Liu, Wenshe Ray
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892251/
https://www.ncbi.nlm.nih.gov/pubmed/35252116
http://dx.doi.org/10.3389/fchem.2022.816576
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author Li, Shuhua G.
Yang, Kai S.
Blankenship, Lauren R.
Cho, Chia-Chuan D.
Xu, Shiqing
Wang, Hongbin
Liu, Wenshe Ray
author_facet Li, Shuhua G.
Yang, Kai S.
Blankenship, Lauren R.
Cho, Chia-Chuan D.
Xu, Shiqing
Wang, Hongbin
Liu, Wenshe Ray
author_sort Li, Shuhua G.
collection PubMed
description The emergence and rapid spread of SARS-CoV-2, the pathogen of COVID-19, have caused a worldwide public health crisis. The SARS-CoV-2 main protease (Mpro) is an essential enzyme for the virus and therefore an appealing target for the development of antivirals to treat COVID-19 patients. Recently, many in silico screenings have been performed against the main protease to discover novel hits. However, the actual hit rate of virtual screening is often low, and most of the predicted compounds are false positive hits. In this study, we developed a refined virtual screening strategy that incorporated molecular docking and post-docking filtering based on parameters including molecular weight and surface area, aiming to achieve predictions with fewer false positive hits. We applied this strategy to the NCI library containing 284,176 compounds against Mpro. In vitro potency analyses validated several potent inhibitors and thus confirmed the feasibility of our virtual screening strategy. Overall, The study resulted in several potent hit Mpro inhibitors, in which two inhibitors have IC(50) values below 1 μM, that are worth being further optimized and explored. Meanwhile, the refined virtual screen strategy is also applicable to improve general in silico screening hit rates and is useful to accelerate drug discovery for treating COVID-19 and other viral infections.
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spelling pubmed-88922512022-03-04 An Enhanced Hybrid Screening Approach to Identify Potent Inhibitors for the SARS-CoV-2 Main Protease From the NCI Compound Library Li, Shuhua G. Yang, Kai S. Blankenship, Lauren R. Cho, Chia-Chuan D. Xu, Shiqing Wang, Hongbin Liu, Wenshe Ray Front Chem Chemistry The emergence and rapid spread of SARS-CoV-2, the pathogen of COVID-19, have caused a worldwide public health crisis. The SARS-CoV-2 main protease (Mpro) is an essential enzyme for the virus and therefore an appealing target for the development of antivirals to treat COVID-19 patients. Recently, many in silico screenings have been performed against the main protease to discover novel hits. However, the actual hit rate of virtual screening is often low, and most of the predicted compounds are false positive hits. In this study, we developed a refined virtual screening strategy that incorporated molecular docking and post-docking filtering based on parameters including molecular weight and surface area, aiming to achieve predictions with fewer false positive hits. We applied this strategy to the NCI library containing 284,176 compounds against Mpro. In vitro potency analyses validated several potent inhibitors and thus confirmed the feasibility of our virtual screening strategy. Overall, The study resulted in several potent hit Mpro inhibitors, in which two inhibitors have IC(50) values below 1 μM, that are worth being further optimized and explored. Meanwhile, the refined virtual screen strategy is also applicable to improve general in silico screening hit rates and is useful to accelerate drug discovery for treating COVID-19 and other viral infections. Frontiers Media S.A. 2022-02-17 /pmc/articles/PMC8892251/ /pubmed/35252116 http://dx.doi.org/10.3389/fchem.2022.816576 Text en Copyright © 2022 Li, Yang, Blankenship, Cho, Xu, Wang and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Chemistry
Li, Shuhua G.
Yang, Kai S.
Blankenship, Lauren R.
Cho, Chia-Chuan D.
Xu, Shiqing
Wang, Hongbin
Liu, Wenshe Ray
An Enhanced Hybrid Screening Approach to Identify Potent Inhibitors for the SARS-CoV-2 Main Protease From the NCI Compound Library
title An Enhanced Hybrid Screening Approach to Identify Potent Inhibitors for the SARS-CoV-2 Main Protease From the NCI Compound Library
title_full An Enhanced Hybrid Screening Approach to Identify Potent Inhibitors for the SARS-CoV-2 Main Protease From the NCI Compound Library
title_fullStr An Enhanced Hybrid Screening Approach to Identify Potent Inhibitors for the SARS-CoV-2 Main Protease From the NCI Compound Library
title_full_unstemmed An Enhanced Hybrid Screening Approach to Identify Potent Inhibitors for the SARS-CoV-2 Main Protease From the NCI Compound Library
title_short An Enhanced Hybrid Screening Approach to Identify Potent Inhibitors for the SARS-CoV-2 Main Protease From the NCI Compound Library
title_sort enhanced hybrid screening approach to identify potent inhibitors for the sars-cov-2 main protease from the nci compound library
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892251/
https://www.ncbi.nlm.nih.gov/pubmed/35252116
http://dx.doi.org/10.3389/fchem.2022.816576
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