Design of SARS-CoV-2 Mpro, PLpro dual-target inhibitors based on deep reinforcement learning and virtual screening

Author:

Zhang Li-chuan1,Zhao Hui-lin1,Liu Jin1,He Lei1,Yu Ri-lei2,Kang Cong-min1ORCID

Affiliation:

1. College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China

2. Key Laboratory of Marine Drugs, Chinese Ministry of Education, School of Medicine & Pharmacy, Ocean University of China, Qingdao, 266003, China

Abstract

Background: Since December 2019, SARS-CoV-2 has continued to spread rapidly around the world. The effective drugs may provide a long-term strategy to combat this virus. The main protease (Mpro) and papain-like protease (PLpro) are two important targets for the inhibition of SARS-CoV-2 virus replication and proliferation. Materials & methods: In this study, deep reinforcement learning, covalent docking and molecular dynamics simulations were used to identify novel compounds that have the potential to inhibit both Mpro and PLpro. Results & conclusion: Three compounds were identified that can effectively occupy the Mpro protein cavity with the PLpro protein cavity and form high-frequency contacts with key amino acid residues (Mpro: His41, Cys145, Glu166; PLpro: Cys111). These three compounds can be further investigated as potential lead compounds for SARS-CoV-2 inhibitors.

Funder

National Natural Science Foundation of China

Publisher

Future Science Ltd

Subject

Drug Discovery,Pharmacology,Molecular Medicine

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