Computer-aided drug design for the pain-like protease (PLpro) inhibitors against SARS-CoV-2

被引:6
作者
Gao, Hongwei [1 ]
Dai, Renhui [1 ]
Su, Ruiling [1 ]
机构
[1] Ludong Univ, Sch Life Sci, Yantai 264025, Shandong, Peoples R China
关键词
SARS-CoV-2; PL pro inhibitors; Virtual screening; Molecular docking; CORONAVIRUS PAPAIN-LIKE; RESPIRATORY SYNDROME CORONAVIRUS; AUTOMATED DOCKING; GLIDE; POLYPHARMACOLOGY; PERFORMANCE; SIMULATION; DISCOVERY; PROTEINS; POTENT;
D O I
10.1016/j.biopha.2023.114247
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
A new coronavirus, known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a highly contagious virus and has caused a massive worldwide health crisis. While large-scale vaccination efforts are underway, the management of population health, economic impact and asof-yet unknown long-term effects on physical and mental health will be a key challenge for the next decade. The papain-like protease (PLpro) of SARS-CoV-2 is a promising target for antiviral drugs. This report used pharmacophore-based drug design technology to identify potential compounds as PLpro inhibitors against SARS-CoV-2. The optimal pharmacophore model was fully validated using different strategies and then was employed to virtually screen out 10 compounds with inhibitory. Molecular docking and non-bonding interactions between the targeted protein PLpro and compounds showed that UKR1129266 was the best compound. These results provided a theoretical foundation for future studies of PLpro inhibitors against SARS-CoV-2.
引用
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页数:18
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