ASAP Discovery: A Community Blind Challenge for Open Source Structure-enabled Drug Discovery for Pandemic Preparedness
Year: 2025
Type: article
Abstract: During the SARS-CoV-2 pandemic the COVID Moonshot consortium demonstrated the feasibility of developing a straight-to-generics Mpro inhibitor in record time. Building on this success, the ASAP Discovery Consortium was launched as an AViDD center that leverages structure-enabled and artificial-intelligence approaches together with a global team to tackle structural biology, medicinal chemistry, biochemistry and (pre-)clinical trials for antiviral drug discovery. With over three years of drug discovery under its belt, ASAP Discovery hosted a community blind challenge using the Polaris platform in collaboration with Valence Labs and OpenADMET. The challenge consisted of several sub-challenges (ligand potency, pose and ADMET predictions) designed to be closely analogous to the challenges that ASAP Discovery faced during these campaigns. During this talk, the background to the data will be outlined as well as the challenge outcomes and the practical processes considered during the design of this challenge.
Author: Scheen, Jenke
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893223486
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