Molecules (Jan 2022)

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

  • Yang Liu,
  • Jianhong Gan,
  • Rongqi Wang,
  • Xiaocong Yang,
  • Zhixiong Xiao,
  • Yang Cao

DOI
https://doi.org/10.3390/molecules27030683
Journal volume & issue
Vol. 27, no. 3
p. 683

Abstract

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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.

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