计算生物学
虚拟筛选
药物发现
蛋白质-蛋白质相互作用
血管紧张素转化酶2
支架蛋白
血浆蛋白结合
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)
病毒
病毒进入
生物
化学
2019年冠状病毒病(COVID-19)
病毒学
细胞生物学
生物信息学
医学
病毒复制
信号转导
疾病
病理
传染病(医学专业)
作者
Davide Pirolli,Benedetta Righino,Maria Cristina De Rosa
标识
DOI:10.1002/minf.202060080
摘要
The spike glycoprotein (S) of the SARS-CoV-2 virus surface plays a key role in receptor binding and virus entry. The S protein uses the angiotensin converting enzyme (ACE2) for entry into the host cell and binding to ACE2 occurs at the receptor binding domain (RBD) of the S protein. Therefore, the protein-protein interactions (PPIs) between the SARS-CoV-2 RBD and human ACE2, could be attractive therapeutic targets for drug discovery approaches designed to inhibit the entry of SARS-CoV-2 into the host cells. Herein, with the support of machine learning approaches, we report structure-based virtual screening as an effective strategy to discover PPIs inhibitors from ZINC database. The proposed computational protocol led to the identification of a promising scaffold which was selected for subsequent binding mode analysis and that can represent a useful starting point for the development of new treatments of the SARS-CoV-2 infection.
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