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《BioRxiv，3月8日，AI-aided design of novel targeted covalent inhibitors against SARS-CoV-2》

  • 来源专题：COVID-19科研动态监测
  • 编译者： zhangmin
  • 发布时间：2020-03-09

  • AI-aided design of novel targeted covalent inhibitors against SARS-CoV-2

    Bowen Tang, Fengming He, Dongpeng Liu, Meijuan Fang, Zhen Wu, Dong Xu

    doi: https://doi.org/10.1101/2020.03.03.972133

    Abstract

    The focused drug repurposing of known approved drugs (such as lopinavir/ritonavir) has been reported failed for curing SARS-CoV-2 infected patients. It is urgent to generate new chemical entities against this virus. As a key enzyme in the life-cycle of coronavirus, the 3C-like main protease (3CLpro or Mpro) is the most attractive for antiviral drug design. Based on a recently solved structure (PDB ID: 6LU7), we developed a novel advanced deep Q-learning network with the fragment-based drug design (ADQN-FBDD) for generating potential lead compounds targeting SARS-CoV-2 3CLpro.

    *注，本文为预印本论文手稿，是未经同行评审的初步报告，其观点仅供科研同行交流，并不是结论性内容，请使用者谨慎使用.

  • 原文来源：https://www.biorxiv.org/content/10.1101/2020.03.03.972133v1
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