O. Ilesanmi

A critical appraisal of structure-based virtual screening, binding free energy methods, and AI-driven molecular design across the evolving computational landscape of drug discovery

Activity cliffs resist prediction within and across protein kinases: a leakage-controlled machine-learning analysis of structure-potency discontinuities.

Activity cliffs, that is pairs of closely related molecules with large potency differences, limit the reliability of structure-activity models, and inferences about target specificity are highly sensitive to how within-target validation is grouped.