药效团
虚拟筛选
药物重新定位
重新调整用途
对接(动物)
计算生物学
化学
分子动力学
药物发现
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
共价键
组合化学
药理学
药品
2019年冠状病毒病(COVID-19)
生物化学
生物
医学
计算化学
传染病(医学专业)
病理
护理部
有机化学
疾病
生态学
作者
Ying Wang,Qiushuang Gao,Yao Peng,Qizheng Yao,Ji Zhang
标识
DOI:10.1080/07391102.2023.2193994
摘要
The outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused an unprecedented global pandemic, and new cases are still on the rise due to the absence of effective medicines. However, developing new drugs within a short time is extremely difficult. Repurposing the existing drugs provides a fast and effective strategy to identify promising inhibitors. Here we focus on the screening of drugs database for discovering potential covalent inhibitors that target 3-chymotrypsin-like protease (3CLpro), an essential enzyme mediating viral replication and transcription. Firstly, we constructed a receptor-ligand pharmacophore model and verified it through decoy set. The importance of pharmacophore features was evaluated by combining molecular dynamics simulation with interaction analyses. Then, covalent docking was used to perform further screening. According to docking score and Prime/Molecular Mechanics Generalized Born Surface Area (MM-GBSA) score, total ten compounds obtained good scores and successfully established covalent bonds with the catalytic Cys145 residue. They also formed favorable interactions with key residues in active sites and closely integrated with 3CLpro with binding modes similar to known 3CLpro inhibitor. Finally, the top four hits DB08732, DB04653, DB01871 and DB07299 were further subjected to 100 ns molecular dynamics (MD) simulation and MM-GBSA binding free energy calculations. The results suggest that the four candidates show good binding affinities for 3CLpro, which warrants further evaluation for their in-vitro/in-vivo activities. Overall, our research methods provide a valuable reference for discovering promising inhibitors against SARS-CoV-2 and help to fight against the epidemic.Communicated by Ramaswamy H. Sarma.
科研通智能强力驱动
Strongly Powered by AbleSci AI