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基于深度学习策略针对组织蛋白酶L的新型冠状病毒肺炎治疗潜在药物发现

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

作者信息

Yang Wei-Li, Li Qi, Sun Jing, Huat Tan Sia, Tang Yan-Hong, Zhao Miao-Miao, Li Yu-Yang, Cao Xi, Zhao Jin-Cun, Yang Jin-Kui

机构信息

Beijing Key Laboratory of Diabetes Research and Care, Beijing Diabetes Institute, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China.

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.

出版信息

Comput Struct Biotechnol J. 2022;20:2442-2454. doi: 10.1016/j.csbj.2022.05.023. Epub 2022 May 17.

Abstract

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.

摘要

组织蛋白酶L(CTSL)是一种半胱氨酸蛋白酶,能够切割并激活严重急性呼吸综合征冠状病毒2(SARS-CoV-2)刺突蛋白,可能是2019冠状病毒病(COVID-19)的一个有前景的治疗靶点。然而,目前仍没有可临床使用的CTSL抑制剂。在此,我们应用Chemprop(一种新训练的定向消息传递深度神经网络方法)来识别能够阻断CTSL活性的小分子和美国食品药品监督管理局(FDA)批准的药物,以扩大用于药物开发和COVID-19药物重新利用的CTSL抑制剂的发现。我们发现5种分子(Mg-132、Z-FA-FMK、半胱氨酸蛋白酶抑制剂E、Mg-101和钙蛋白酶抑制剂)能够在纳摩尔范围内显著抑制CTSL的活性,并抑制假型和活SARS-CoV-2的感染。值得注意的是,我们发现FDA批准的抗生素达托霉素具有显著的CTSL抑制作用,并且能够抑制SARS-CoV-2假病毒感染。此外,分子对接计算表明这些化合物与CTSL的结合稳定且牢固。总之,本研究首次表明Chemprop非常适合预测酶的其他抑制剂,并揭示了筛选用于治疗COVID-19和其他有未满足需求疾病的新型分子和药物的重要策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b01/9133704/065c85b9f63d/ga1.jpg

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