蛋白酶
对接(动物)
虚拟筛选
计算生物学
木瓜蛋白酶
生物信息学
药物发现
小分子
药效团
化学
化学型
生物化学
生物
酶
基因
护理部
医学
精油
色谱法
作者
Olivia Garland,Anh‐Tien Ton,Shoeib Moradi,Jason R. Smith,Suzana Kovacic,Kurtis Ng,Mohit Pandey,Fuqiang Ban,Jaeyong Lee,M. Vuckovic,L.J. Worrall,Robert N. Young,Ralph Pantophlet,N.C.J. Strynadka,Artem Cherkasov
标识
DOI:10.1021/acs.jcim.2c01641
摘要
The rapid global spread of the SARS-CoV-2 virus facilitated the development of novel direct-acting antiviral agents (DAAs). The papain-like protease (PLpro) has been proposed as one of the major SARS-CoV-2 targets for DAAs due to its dual role in processing viral proteins and facilitating the host's immune suppression. This dual role makes identifying small molecules that can effectively neutralize SARS-CoV-2 PLpro activity a high-priority task. However, PLpro drug discovery faces a significant challenge due to the high mobility and induced-fit effects in the protease's active site. Herein, we virtually screened the ZINC20 database with Deep Docking (DD) to identify prospective noncovalent PLpro binders and combined ultra-large consensus docking with two pharmacophore (ph4)-filtering strategies. The analysis of active compounds revealed their somewhat-limited diversity, likely attributed to the induced-fit nature of PLpro's active site in the crystal structures, and therefore, the use of rigid docking protocols poses inherited limitations. The top hits were assessed against recombinant viral proteins and live viruses, demonstrating desirable inhibitory activities. The best compound VPC-300195 (IC50: 15 μM) ranks among the top noncovalent PLpro inhibitors discovered through in silico methodologies. In the search for novel SARS-CoV-2 PLpro-specific chemotypes, the identified inhibitors could serve as diverse templates for the development of effective noncovalent PLpro inhibitors.
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