Francesco Gentile
Francesco Gentile
Assistant Professor

STM 351
(613) 562-5800 ext. 3971


The Gentile Lab leverages computational strategies to discover novel drug-like molecules. We use deep learning to accelerate structure-based virtual screening and improve performance against unconventional drug targets such as protein-protein interfaces. Our research goal is to enable universal access to the chemical space and explore its therapeutic potential. In addition to developing methods of computer-aided drug discovery, we computationally investigate proteins which are involved in cancer drug resistance and identify small molecule modulators for their activities.

Selected Publications

  • Gentile, F. et al. Automated Discovery of Noncovalent Inhibitors of SARS-CoV-2 Main Protease by Consensus Deep Docking of 40 Billion Small Molecules. Chem Sci 12, 15960–15974 (2021).
  • Gentile, F. et al. Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery. ACS Cent Sci 6, 939–949 (2020).
  • Preto, J. & Gentile, F. Assessing and improving the performance of consensus docking strategies using the DockBox package. J Comput Aided Mol Des 33, 817–829 (2019).
  • Gentile, F. et al. Computer-aided drug design of small molecule inhibitors of the ERCC1-XPF protein–protein interaction. Chem Biol Drug Des 95, 460–471 (2020).