Abstract
As a theoretically rigorous and accurate method, FEP-ABFE (Free Energy Perturbation-Absolute Binding Free Energy) calculations showed great potential in drug discovery, but its practical application was difficult due to high computational cost. To rapidly discover antiviral drugs targeting SARS-CoV-2 Mpro and TMPRSS2, we performed FEP-ABFE–based virtual screening for ∼12,000 protein-ligand binding systems on a new generation of Tianhe supercomputer. A task management tool was specifically developed for automating the whole process involving more than 500,000 MD tasks. In further experimental validation, 50 out of 98 tested compounds showed significant inhibitory activity towards Mpro, and one representative inhibitor, dipyridamole, showed remarkable outcomes in subsequent clinical trials. This work not only demonstrates the potential of FEP-ABFE in drug discovery but also provides an excellent starting point for further development of anti-SARS-CoV-2 drugs. Besides, ∼500 TB of data generated in this work will also accelerate the further development of FEP-related methods.
| Original language | English |
|---|---|
| Pages (from-to) | 45-57 |
| Number of pages | 13 |
| Journal | International Journal of High Performance Computing Applications |
| Volume | 37 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2023 |
Bibliographical note
Publisher Copyright:© The Author(s) 2022.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: We cordially acknowledge National Key R&D Program of China (2017YFB0202600), National Natural Science Foundation of China (81903542, 21877134, 22077143, and U1811462), Fundamental Research Funds for Hainan University (KYQD (ZR)-21,031), Science Foundation of Guangzhou City (202102021151, 201904020023), Guangdong Province Higher Vocational Colleges & Schools Pearl River Scholar Funded Scheme (2016), the National Science Foundation (NSF, grant CHE-1111761), the Taishan Scholars Program (tsqn201909170), the Innovative Leader of Qingdao Program (19-3-2–26-zhc), the special scientific research fund for COVID-19 from the Pilot National Laboratory for Marine Science and Technology (QNLM202001), and open fund from the State Key Laboratory of High Performance Computing (201901–11).
| Funders | Funder number |
|---|---|
| Fundamental Research Funds for Hainan University | |
| Innovative Leader of Qingdao Program | 19-3-2–26-zhc |
| KYQD | |
| State Key Laboratory of High Performance Computing | 201901–11 |
| Taishan Scholars Program | tsqn201909170 |
| National Science Foundation Arctic Social Science Program | CHE-1111761 |
| National Science Foundation Arctic Social Science Program | |
| Natural Science Foundation of Guangzhou City | 201904020023, 202102021151 |
| Natural Science Foundation of Guangzhou City | |
| National Natural Science Foundation of China (NSFC) | 81903542, 21877134, U1811462, 22077143 |
| National Natural Science Foundation of China (NSFC) | |
| National Key Basic Research and Development Program of China | 2017YFB0202600 |
| National Key Basic Research and Development Program of China | |
| Guangdong Province Higher Vocational Colleges and Schools Pearl River Scholar Funded Scheme | |
| Polit National Laboratory for Marine Science and Technology | QNLM202001 |
| Polit National Laboratory for Marine Science and Technology |
Keywords
- SARS-CoV-2
- Supercomputing
- absolute binding free energy
- free energy perturbation
- virtual screening
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Hardware and Architecture