Potential 2019-nCoV 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches

The emergence of the 2019 novel coronavirus (2019-nCoV), for which there is no vaccine or any known effective treatment created a sense of urgency for novel drug discovery approaches One of the most important 2019-nCoV protein targets is the 3C-like protease for which the crystal structure is known Most of the immediate efforts are focused on drug repurposing of known clin -approved drugs and virtual screening for the mols available from chem libraries that may not work well For example, the IC50 of lopinavir, an HIV protease inhibitor, against the 3C-like protease is approx 50 micromolar In an attempt to address this challenge, on Jan 28th, 2020 Insilico Medicine decided to utilize a part of its generative chem pipeline to design novel drug-like inhibitors of 2019-nCoV and started generation on Jan 30th It utilized three of its previously validated generative chem approaches: crystal-derived pocked-based generator, homol modeling-based generation, and ligand-based generation Novel druglike compounds generated using these approaches are being published at www insilico com/ncov-sprint/ and will be continuously updated Several mols will be synthesized and tested using the internal resources;however, the team is seeking collaborations to synthesize, test, and, if needed, optimize the published mols