Abstract

In March 2020 an international consortium of academic and industrial scientists self-organised to discover and develop new SARS-CoV2 antivirals by combining crowdsourcing, high-throughput experiments, computational simulations, machine learning, fragment based lead generation and centuries of medicinal chemistry experience directed against the main protease(MPro) of SARS-CoV2. In the next 24 months rapid lead optimisation was pursued to generate pre-clinical candidates with good predicted human dose and low drug-drug interaction potential. All the primary data has been placed in the public domain(over 2000 IC50’s) with over 550 crystal structures also available. Here we will describe the approach and the Wellcome Trust supported direct-to-generic development plan that we are using to ensure global, equitable access to anti-COVID-19 therapeutics. We will briefly describe how the approach is being built upon in an international NIH funded centre for future pandemic preparedness. For references see bioarxiv: https://doi.org/10.1101/2020.10.29.339317. For data see: https://covid.postera.ai/covid/activity_data For crystal structures see: https://fragalysis.diamond.ac.uk/viewer/react/preview/target/Mpro