Structure-based maximal affinity model predicts small-molecule druggability.

TLDR: It is shown that a model-based approach using basic biophysical principles yields good prediction of druggability based solely on the crystal structure of the target binding site and that these calculated values correlate with drug discovery outcomes.

Abstract: Lead generation is a major hurdle in small-molecule drug discovery, with an estimated 60% of projects failing from lack of lead matter or difficulty in optimizing leads for drug-like properties It would be valuable to identify these less-druggable targets before incurring substantial expenditure and effort Here we show that a model-based approach using basic biophysical principles yields good prediction of druggability based solely on the crystal structure of the target binding site We quantitatively estimate the maximal affinity achievable by a drug-like molecule, and we show that these calculated values correlate with drug discovery outcomes We experimentally test two predictions using high-throughput screening of a diverse compound collection The collective results highlight the utility of our approach as well as strategies for tackling difficult targets