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
Abstract
Significance 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. It has been demonstrated that a new virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions can reach an unprecedentedly high hit rate, leading to successful identification of 15 potent inhibitors of SARS-CoV-2 main protease (M pro ) from 25 computationally selected drugs under a threshold of K i = 4 μM. The outcomes of this study are valuable for not only drug repurposing to treat COVID-19 but also demonstrating the promising potential of the FEP-ABFE prediction-based virtual screening approach.