Screening of Potential Inhibitors Against SARS-CoV-2 Based on Prescription Mining and Molecular Dynamics Simulations

ABSTRACT

Objective To detect the active ingredients in the traditional Chinese medicine prescription and its molecular mechanisms against SARS-CoV-2 by prescription mining and molecular dynamics simulations. Methods Herein, prescription mining and virtual screening of drugs were performed to screen the potential inhibitors against SARS-CoV-2. Molecular docking and molecular dynamics (MDs) simulations were further performed to explore the molecular recognition and inhibition mechanism between the potential inhibitors and SARS-CoV-2. Results The natural compounds library was constructed by 143 prescriptions of traditional Chinese medicine, which contained 640 natural compounds. Ten compounds were screened out from the natural compounds library. Among the 10 compounds, 23-trans-p-coumaryhormentic acid, the main active constituent of the Loquat leaf, showed the best binding affinity targeting the recognizing interface of SARS-CoV-2 S protein/ACE2. Upon binding 23-trans-p-coumaryhormentic acid, the key interactions between SARS-CoV-2 S protein and ACE2 were almost interrupted. Conclusion Ten compounds targeting SARS-CoV-2 S protein/ACE2 interface were screened out from natural compound library. And we inferred that 23-trans-p-coumaryhormentic acid is a potential inhibitor against SARS-CoV-2, which would contribute to the development of the antiviral drug for SARS-CoV-2.