Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs

Zhe Li, Xin Li, Yi You Huang, Yaoxing Wu, Runduo Liu, Lingli Zhou, Yuxi Lin, Deyan Wu, Lei Zhang, Hao Liu, Ximing Xu, Kunqian Yu, Yuxia Zhang, Jun Cui, Chang Guo Zhan, Xin Wang, Hai Bin Luo

Research output: Contribution to journalArticlepeer-review

121 Scopus citations

Abstract

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global crisis. There is no therapeutic treatment specific for COVID-19. It is highly desirable to identify potential antiviral agents against SARS-CoV-2 from existing drugs available for other diseases and thus repurpose them for treatment of COVID-19. In general, a drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. Here we report a virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions and its use in identifying drugs targeting SARS-CoV-2 main protease (Mpro). The accurate FEP-ABFE predictions were based on the use of a restraint energy distribution (RED) function, making the practical FEP-ABFE−based virtual screening of the existing drug library possible. As a result, out of 25 drugs predicted, 15 were confirmed as potent inhibitors of SARS-CoV-2 Mpro. The most potent one is dipyridamole (inhibitory constant Ki = 0.04 μM) which has shown promising therapeutic effects in subsequently conducted clinical studies for treatment of patients with COVID-19. Additionally, hydroxychloroquine (Ki = 0.36 μM) and chloroquine (Ki = 0.56 μM) were also found to potently inhibit SARS-CoV-2 Mpro. We anticipate that the FEP-ABFE prediction-based virtual screening approach will be useful in many other drug repurposing or discovery efforts.

Original languageEnglish
Pages (from-to)27381-27387
Number of pages7
JournalProceedings of the National Academy of Sciences of the United States of America
Volume117
Issue number44
DOIs
StatePublished - Nov 3 2020

Bibliographical note

Funding Information:
We cordially acknowledge Tencent Cloud, National Supercomputing centers in Shenzhen, Tianjing, and Guangzhou, and Beijing Super Cloud Computing Center for providing high performance computing resources for virtual screening and FEP calculations. We cordially acknowledge National Key R&D Program of China (Grant 2017YFB0202600), National Natural Science Foundation of China (Grants 81903542, 81522041, and 21877134), Science Foundation of Guangdong Province (Grants 2020A111128007, 2018A030313215, and 201904020023), Guangdong Provincial Key Laboratory of Construction Foundation (Grant 2017B030314030), Fundamental Research Funds for the Central Universities (Sun Yat-Sen University, Grant 18ykpy23), Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (Grant 2017BT01Y093), the National Science and Technology Major Projects for “Major New Drugs Innovation and Development” (Grant 2018ZX09711003-003-005), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant XDC01040100), the NSF (Grant CHE-1111761), the Taishan Scholars Program (Grant tsqn201909170), the Innovative Leader of Qingdao Program (Grant 19-3-2-26-zhc), the special scientific research fund for COVID-19 from the Pilot National Laboratory for Marine Science and Technology (Grant QNLM202001), Sun Yat-Sen University and Zhejiang University special scientific research fund for COVID-19 prevention and control, and philanthropy donation from individuals. The funders had no roles in the design and execution of the study.

Funding Information:
ACKNOWLEDGMENTS. We cordially acknowledge Tencent Cloud, National Supercomputing centers in Shenzhen, Tianjing, and Guangzhou, and Beijing Super Cloud Computing Center for providing high performance computing resources for virtual screening and FEP calculations. We cordially acknowledge National Key R&D Program of China (Grant 2017YFB0202600), National Natural Science Foundation of China (Grants 81903542, 81522041, and 21877134), Science Foundation of Guangdong Province (Grants 2020A111128007, 2018A030313215, and 201904020023), Guangdong Provincial Key Laboratory of Construction Foundation (Grant 2017B030314030), Fundamental Research Funds for the Central Universities (Sun Yat-Sen University, Grant 18ykpy23), Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (Grant 2017BT01Y093), the National Science and Technology Major Projects for “Major New Drugs Innovation and Development” (Grant 2018ZX09711003-003-005), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant XDC01040100), the NSF (Grant CHE-1111761), the Taishan Scholars Program (Grant tsqn201909170), the Innovative Leader of Qingdao Program (Grant 19-3-2-26-zhc), the special scientific research fund for COVID-19 from the Pilot National Laboratory for Marine Science and Technology (Grant QNLM202001), Sun Yat-Sen University and Zhejiang University special scientific research fund for COVID-19 prevention and control, and philanthropy donation from individuals. The funders had no roles in the design and execution of the study.

Publisher Copyright:
© 2020 National Academy of Sciences. All rights reserved.

Keywords

  • Drug repurposing
  • Free energy perturbation
  • Main protease
  • SARS-CoV-2
  • Virtual screening

ASJC Scopus subject areas

  • General

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