TY - JOUR
T1 - Free energy perturbation–based large-scale virtual screening for effective drug discovery against COVID-19
AU - Li, Zhe
AU - Wu, Chengkun
AU - Li, Yishui
AU - Liu, Runduo
AU - Lu, Kai
AU - Wang, Ruibo
AU - Liu, Jie
AU - Gong, Chunye
AU - Yang, Canqun
AU - Wang, Xin
AU - Zhan, Chang Guo
AU - Luo, Hai Bin
N1 - Publisher Copyright:
© The Author(s) 2022.
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
KW - SARS-CoV-2
KW - Supercomputing
KW - absolute binding free energy
KW - free energy perturbation
KW - virtual screening
UR - http://www.scopus.com/inward/record.url?scp=85136988438&partnerID=8YFLogxK
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U2 - 10.1177/10943420221117797
DO - 10.1177/10943420221117797
M3 - Article
AN - SCOPUS:85136988438
SN - 1094-3420
VL - 37
SP - 45
EP - 57
JO - International Journal of High Performance Computing Applications
JF - International Journal of High Performance Computing Applications
IS - 1
ER -