Year: 2026
Type: preprint
Abstract: Drug-drug interactions (DDIs) are largely catalogued empirically, with limited structural explanation of why two drugs interact. We asked whether a purely structural mechanism - competing or cooperating engagement of the same protein pocket - is sufficient to recover documented DDIs without any training on clinical interaction labels. Using composite protein multiple-ligand (COLIG) assignments, which classify co-bound ligand pairs as attractive or repulsive, we scored 21,945 pairs of 210 drugs by predicted engagement of each proteins top-ranked pocket. Confidence-summed COLIG ranking achieved top-5% precision of 49.3% against DDInter and 25.1% against KEGG, versus background prevalences of 29.6% and 14.7%, respectively; pooled top-pocket engagement reached 50.3% DDInter precision. These results support pocket-based DDI screening and class-dependent hypotheses about direct and noncontact ligand engagement, while leaving causal mechanisms to be established.
Authors: Jeffrey Skolnick, Bharath Srinivasan
Institutions: Georgia Institute of Technology, Robert Gordon University
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225162928