CACHE Challenge #3: Targeting the Nsp3 Macrodomain of SARS-CoV‑2

The third Critical Assessment of Computational
Hit-finding
Experiments (CACHE) challenged computational teams to identify
chemically novel ligands targeting the macrodomain 1 of SARS-CoV-2
Nsp3, a promising coronavirus drug target. Twenty-three groups deployed
diverse design strategies to collectively select 1739 ligand candidates.
While over 85% of the designed molecules were chemically novel, the
best experimentally confirmed hits were structurally similar to previously
published compounds. Confirming a trend observed in CACHE #1 and #2,
two of the best-performing workflows used compounds selected by physics-based
computational screening methods to train machine learning models able
to rapidly screen large chemical libraries, while four others used
exclusively physics-based approaches. Three pharmacophore searches
and one fragment growing strategy were also part of the seven winning
workflows. While active molecules discovered by CACHE #3 participants
largely mimicked the adenine ring of the endogenous substrate, ADP-ribose,
preserving the canonical chemotype commonly observed in previously
reported Nsp3-Mac1 ligands, they still provide novel structure–activity
relationship insights that may inform the development of future antivirals.
Collectively, these results show that multiple molecular design strategies
can efficiently converge on similar potent molecules.