Potential COVID-2019 3C-like Protease Inhibitors Designed Using Generative DeeLearning Approaches

The emergence of the 2019 novel coronavirus (COVID-19), 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 COVID-19 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 clinically-approved drugs and virtual screening for the molecules available from chemical libraries that may not work well For example, the IC50 of lopinavir, an HIV protease inhibitor, against the 3C-like protease is approximately 50 micromolar, which is far from ideal In an attempt to address this challenge, on January 28th, 2020 Insilico Medicine decided to utilize a part of its generative chemistry pipeline to design novel drug-like inhibitors of COVID-19 and started generation on January 30th It utilized three of its previously validated generative chemistry approaches: crystal-derived pocked-based generator, homology modelling-based generation, and ligand-based generation Novel druglike compounds generated using these approaches were published at a href="http://www insilico com/ncov-sprint/" www insilico com/ncov-sprint/ /a Several molecules will be synthesized and tested using the internal resources;however, the team is seeking collaborations to synthesize, test, and, if needed, optimize the published molecules br / / /div