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

组织蛋白酶L 药物重新定位 药物发现 化学 药理学
作者
Wei-Li Yang,Qi Li,Jing Sun,Sia Huat Tan,Yan-Hong Tang,Miao-Miao Zhao,Yu-Yang Li,Xi Cao,Jin-Cun Zhao,Jin-Kui Yang
出处
期刊:Computational and structural biotechnology journal [Elsevier BV]
卷期号:20: 2442-2454 被引量:1
标识
DOI:10.1016/j.csbj.2022.05.023
摘要

• Cathepsin L(CTSL) is a promising therapeutic target for COVID-19. • A new deep learning model was used to predict CTSL inhibitor based on structure. • 5 molecules for inhibiting CTSL and treating COVID-19 at nmol level were identified. • Daptomycin can distinctly inhibit CTSL and has potential for COVID-19 treatment. 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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
林林总总发布了新的文献求助10
1秒前
852应助prim采纳,获得10
7秒前
嬛嬛完成签到,获得积分20
8秒前
图治完成签到,获得积分10
17秒前
鹿lu完成签到 ,获得积分10
19秒前
云不暇完成签到 ,获得积分10
20秒前
HEIKU应助jjj采纳,获得10
22秒前
暴躁的寻云完成签到 ,获得积分10
22秒前
安详尔岚完成签到 ,获得积分10
22秒前
星辰大海应助peanut采纳,获得10
24秒前
背后的小白菜完成签到,获得积分10
31秒前
LHL完成签到,获得积分10
32秒前
穿多点完成签到,获得积分10
32秒前
zz完成签到 ,获得积分10
33秒前
jiemo_111完成签到,获得积分10
35秒前
35秒前
小江不饿完成签到,获得积分10
38秒前
sunrase完成签到,获得积分10
38秒前
太吾墨完成签到,获得积分10
39秒前
疯狂的虔完成签到,获得积分10
45秒前
小王好饿完成签到 ,获得积分10
47秒前
听风完成签到 ,获得积分10
55秒前
剑指东方是为谁应助彬彬采纳,获得10
56秒前
笨笨芯应助小巧曼冬采纳,获得20
57秒前
Pattis完成签到 ,获得积分10
59秒前
huhdcid完成签到,获得积分10
59秒前
欣喜的人龙完成签到 ,获得积分10
1分钟前
1分钟前
左一酱完成签到 ,获得积分10
1分钟前
情怀应助科研通管家采纳,获得10
1分钟前
wanci应助科研通管家采纳,获得10
1分钟前
彭于彦祖应助科研通管家采纳,获得20
1分钟前
打打应助科研通管家采纳,获得10
1分钟前
Akim应助科研通管家采纳,获得10
1分钟前
1分钟前
..完成签到,获得积分10
1分钟前
1分钟前
华青ww发布了新的文献求助10
1分钟前
烟花应助坚强的严青采纳,获得10
1分钟前
1分钟前
高分求助中
【此为提示信息,请勿应助】请按要求发布求助,避免被关 20000
ISCN 2024 – An International System for Human Cytogenomic Nomenclature (2024) 3000
Continuum Thermodynamics and Material Modelling 2000
Encyclopedia of Geology (2nd Edition) 2000
105th Edition CRC Handbook of Chemistry and Physics 1600
Maneuvering of a Damaged Navy Combatant 650
Mindfulness and Character Strengths: A Practitioner's Guide to MBSP 380
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3776445
求助须知:如何正确求助?哪些是违规求助? 3321879
关于积分的说明 10208141
捐赠科研通 3037221
什么是DOI,文献DOI怎么找? 1666605
邀请新用户注册赠送积分活动 797579
科研通“疑难数据库(出版商)”最低求助积分说明 757872