Protein Thoughts: AI Framework for Interpretable PPI Discovery

An innovative AI framework named Protein Thoughts redefines the discovery of protein-protein interactions (PPIs) as a search problem that emphasizes interpretability and reasoning. This system breaks down binding evidence into four significant biological signals: sequence similarity indicating evolutionary ties, structural complementarity representing geometric alignment, interface balance, and chemical compatibility that details residue-level interactions. Instead of merging these signals into a non-transparent score, it maintains their distinct contributions via a clear value function, facilitating both ranking and mechanistic explanation. This approach tackles a critical challenge in computational biology, where ranked predictions often lack biochemical clarity, thus impeding their acceptance among researchers.