Motivation: Protein–protein interactions are central to cardiovascular disease, yet relevant information is scattered across the literature and general databases, making it difficult to curate. Protein–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.
Results: We 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. These were analysed with AlphaFold3 to infer interaction interfaces and thermodynamic properties linked to complex stability, and to estimate the likelihood that each protein pair forms a complex. Benchmarking showed CAPRINI-M outperformed general-purpose PPI resources in hypertrophy-focused edge-topology enrichment. 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 more complete, mechanistically informative access to cardiovascular-disease–relevant protein-protein interactions by integrating literature evidence with structural interface and stability-aware annotations.
Availability: The CAPRINI-M web application is available at https://shiny.dieterichlab.org/app/caprinim. The source code used in this study is linked in the Availability section of the manuscripts.
Contact: E.Gjerga@uni-heidelberg.de
Supplementary information: Supplementary data are available at Bioinformatics online

Co-authors: Philipp Wiesenbach, Chris-Andris Görner, Ying Zhang, Konstantin Pelz, Markus List, Christoph Dieterich