登录
 机构网站
  1. 首页
  2. 情报产品
  3. 快讯详情

《ChemRxiv，3月23日，Identification of Key Interactions Between SARS-CoV-2 Main Protease and Inhibitor Drug Candidates》

  • 来源专题：COVID-19科研动态监测
  • 编译者： zhangmin
  • 发布时间：2020-03-25

  • Identification of Key Interactions Between SARS-CoV-2 Main Protease and Inhibitor Drug Candidates

    Preprint submitted on 20.03.2020, 12:10 and posted on 23.03.2020, 20:27 by Ryunosuke Yoshino Nobuaki Yasuo Masakazu Sekijima

    The number of cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (COVID-19) has reached over 114,000. SARS-CoV-2 caused a pandemic in Wuhan, China, in December 2019 and is rapidly spreading globally. It has been reported that peptide-like anti-HIV-1 drugs are effective against SARS-CoV Main protease (Mpro). Due to the close phylogenetic relationship between SARS-CoV and SARS-CoV-2, their main proteases share many structural and functional features. Thus, these drugs are also regarded as potential drug candidates targeting SARS-CoV-2 Mpro. However, the mechanism of action of SARS-CoV-2 Mpro at the atomic-level is unknown.

  • 原文来源：https://chemrxiv.org/articles/Identification_of_Key_Interactions_Between_SARS-CoV-2_Main_Protease_and_Inhibitor_Drug_Candidates/12009636
7浏览量
原文链接
相关报告

  • 《Nature，7月27日，Identification of key interactions between SARS-CoV-2 main protease and inhibitor drug candidates》
    • 来源专题：COVID-19科研动态监测
    • 编译者：zhangmin
    • 发布时间：2020-07-28
    • Identification of key interactions between SARS-CoV-2 main protease and inhibitor drug candidates Ryunosuke Yoshino, Nobuaki Yasuo & Masakazu Sekijima Scientific Reports volume 10, Article number: 12493 (2020) Abstract The number of cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (COVID-19) has reached over 114,000. SARS-CoV-2 caused a pandemic in Wuhan, China, in December 2019 and is rapidly spreading globally. It has been reported that peptide-like anti-HIV-1 drugs are effective against SARS-CoV Main protease (Mpro). Due to the close phylogenetic relationship between SARS-CoV and SARS-CoV-2, their main proteases share many structural and functional features. Thus, these drugs are also regarded as potential drug candidates targeting SARS-CoV-2 Mpro. However, the mechanism of action of SARS-CoV-2 Mpro at the atomic-level is unknown. In the present study, we revealed key interactions between SARS-CoV-2 Mpro and three drug candidates by performing pharmacophore modeling and 1 μs molecular dynamics (MD) simulations. His41, Gly143, and Glu166 formed interactions with the functional groups that were common among peptide-like inhibitors in all MD simulations. These interactions are important targets for potential drugs against SARS-CoV-2 Mpro.
    10浏览量
    原文链接

  • 《ChemRxiv，2月19日，Rapid Identification of Potential Inhibitors of SARS-CoV-2 Main Protease by Deep Docking of 1.3 Billion Compounds》
    • 来源专题：COVID-19科研动态监测
    • 编译者：zhangmin
    • 发布时间：2020-02-20
    • Rapid Identification of Potential Inhibitors of SARS-CoV-2 Main Protease by Deep Docking of 1.3 Billion Compounds Preprint submitted on 17.02.2020, 04:23 and posted on 19.02.2020, 06:04 by Anh-Tien Ton Francesco Gentile Michael Hsing Fuqiang Ban Artem Cherkasov The recently emerged 2019 Novel Coronavirus (SARS-CoV-2) and associated COVID-19 disease cause serious or even fatal respiratory tract infection and yet no FDA-approved therapeutics or effective treatment is currently available to effectively combat the outbreak. This urgent situation is pressing the world to respond with the development of novel vaccine or a small molecule therapeutics for SARS-CoV-2. Along these efforts, the structure of SARS-CoV-2 main protease (Mpro) has been rapidly resolved and made publicly available to facilitate global efforts to develop novel drug candidates. In recent month, our group has developed a novel deep learning platform – Deep Docking (DD) which enables very fast docking of billions of molecular structures and provides up to 6,000X enrichment on the top-predicted ligands compared to conventional docking workflow (without notable loss of information on potential hits). In the current work we applied DD to entire 1.3 billion compounds from ZINC15 library to identify top 1,000 potential ligands for SARS-CoV-2 Mpro. The compounds are made publicly available for further characterization and development by scientific community. *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.
    7浏览量
    原文链接