Kristian Birchall

This study evaluates machine learning-based scoring functions by comparing them to baseline models that only learn dataset biases, revealing that the MLBSFs primarily capture biases rather than generalizable physics knowledge.

STRIFE improves fragment elaboration by incorporating pharmacophoric information from protein targets, outperforming existing methods in generating ligand-efficient structures.