DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design

作者：Yang Liu, Jianhong Gan, Rongqi Wang, Xiaocong Yang, Zhi‐Xiong Jim Xiao, Yang Cao · 发表于：Molecules · 年份：2022 · DOI：10.3390/molecules27030683 · 被引用次数：16 · 研究领域：Computational Drug Discovery Methods、vaccines and immunoinformatics approaches、SARS-CoV-2 and COVID-19 Research

Since the outbreak of SARS-CoV-2, numerous compounds against COVID-19 have been derived by computer-aided drug design (CADD) studies. They are valuable resources for the development of COVID-19 therapeutics. In this work, we reviewed these studies and analyzed 779 compounds against 16 target proteins from 181 CADD publications. We performed unified docking simulations and neck-to-neck comparison with the solved co-crystal structures. We computed their chemical features and classified these compounds, aiming to provide insights for subsequent drug design. Through detailed analyses, we recommended a batch of compounds that are worth further study. Moreover, we organized all the abundant data and constructed a freely available database, DrugDevCovid19, to facilitate the development of COVID-19 therapeutics.