DrugDevCovid19：计算机辅助药物设计衍生的抗 COVID-19 化合物图谱。
DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design.
机构信息
Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610000, China.
Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02110, USA.
出版信息
Molecules. 2022 Jan 21;27(3):683. doi: 10.3390/molecules27030683.
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.
自 SARS-CoV-2 爆发以来，通过计算机辅助药物设计 (CADD) 研究已经衍生出许多针对 COVID-19 的化合物。它们是开发 COVID-19 疗法的宝贵资源。在这项工作中，我们回顾了这些研究，并分析了来自 181 篇 CADD 出版物的 16 个靶蛋白的 779 种化合物。我们进行了统一的对接模拟，并与已解决的共晶结构进行了颈对颈比较。我们计算了它们的化学特征，并对这些化合物进行了分类，旨在为后续的药物设计提供思路。通过详细的分析，我们推荐了一批值得进一步研究的化合物。此外，我们组织了所有丰富的数据，并构建了一个免费的数据库，DrugDevCovid19，以促进 COVID-19 疗法的开发。
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