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

Journal: Future medicinal chemistry
Published Date:

Abstract

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. 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. 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.

Authors

  • Li-Chuan Zhang
    College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China.
  • Hui-Lin Zhao
    College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China.
  • Jin Liu
    School of Computer Science and Engineering, Central South University, Changsha, China.
  • Lei He
    Guangxi Medical University, Nanning 530021; State Key Laboratory of Pathogen and Biosecurity, Beijing 100071, China.
  • Ri-Lei Yu
    Key Laboratory of Marine Drugs, Chinese Ministry of Education, School of Medicine & Pharmacy, Ocean University of China, Qingdao, 266003, China.
  • Cong-Min Kang
    College of Chemical Engineering, Qingdao University of Science & Technology, Qingdao, 266042, China.