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

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.

SUBMITTER: Zhang LC

PROVIDER: S-EPMC8920029 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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

Zhang Li-Chuan LC Zhao Hui-Lin HL Liu Jin J He Lei L Yu Ri-Lei RL Kang Cong-Min CM

Future medicinal chemistry 20220227 6

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 hav ...[more]

PMID: 35220726

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