CAPRINI-M: An AI-curated Cardiac-Specific Atlas of Protein Interactions in Mice

Abstract

MotivationProtein-protein interactions are fundamental to cardiovascular disease biology, but the corresponding knowledge is dispersed across the literature and heterogeneous databases, making systematic curation time-consuming. Moreover, many existing PPI resources may be biased and lack detailed information on structural interaction interfaces or associated thermodynamic parameters. ResultsWe present CAPRINI-M (CArdiac PRotein INteractions In Mice), a web-based tool hosting an AI-curated atlas of cardiac protein interactions. We mined 9,105 cardiobiology manuscripts and used open-source LLMs (LLaMA-3.3 70B) to extract 11,189 protein-protein interactions. We then used AlphaFold3 to infer interaction interfaces, estimate thermodynamic properties related to complex stability, and predict the likelihood that each protein pair forms a complex. In our benchmarking analysis, CAPRINI-M showed stronger performance than the comparator PPI resources tested here. Predicted interaction favourability also agreed with published experimental evidence, with lower predicted Gibbs free energy associated with experimentally preferred binding partners. Overall, CAPRINI-M provides a more comprehensive, mechanistically annotated view of cardiovascular disease-relevant protein-protein interactions by integrating literature evidence with structural, interface-level, and stability-related information. AvailabilityThe CAPRINI-M web application is available at https://shiny.dieterichlab.org/app/caprinim. The source code used in this study is linked in the manuscripts Availability section.