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Potential drug discovery for COVID-19 treatment targeting Cathepsin L using a deep learning-based strategy

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机构: [1]Beijing Key Laboratory of Diabetes Research and Care, Beijing Diabetes Institute, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China [2]State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510182, China [3]Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China [4]Guangzhou Laboratory, Bio-Island, Guangzhou, Guangdong 510320, China [5]Institute of Infectious Disease, Guangzhou Eighth People’s Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510000, China
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关键词: COVID-19 Cathepsin L Deep learning Drug prediction Daptomycin

摘要:
Cathepsin L (CTSL), a cysteine protease that can cleave and activate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein, could be a promising therapeutic target for coronavirus disease 2019 (COVID-19). However, there is still no clinically available CTSL inhibitor that can be used. Here, we applied Chemprop, a newly trained directed-message passing deep neural network approach, to identify small molecules and FDA-approved drugs that can block CTSL activity to expand the discovery of CTSL inhibitors for drug development and repurposing for COVID-19. We found 5 molecules (Mg-132, Z-FA-FMK, leupeptin hemisulfate, Mg-101 and calpeptin) that were able to significantly inhibit the activity of CTSL in the nanomolar range and inhibit the infection of both pseudotype and live SARS-CoV-2. Notably, we discovered that daptomycin, an FDA-approved antibiotic, has a prominent CTSL inhibitory effect and can inhibit SARS-CoV-2 pseudovirus infection. Further, molecular docking calculation showed stable and robust binding of these compounds with CTSL. In conclusion, this study suggested for the first time that Chemprop is ideally suited to predict additional inhibitors of enzymes and revealed the noteworthy strategy for screening novel molecules and drugs for the treatment of COVID-19 and other diseases with unmet needs.(c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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出版当年[2021]版:
大类 | 3 区 生物学
小类 | 3 区 生化与分子生物学
最新[2023]版:
大类 | 2 区 生物学
小类 | 3 区 生化与分子生物学
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出版当年[2020]版:
Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
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Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY

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第一作者机构: [1]Beijing Key Laboratory of Diabetes Research and Care, Beijing Diabetes Institute, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
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