Capturing domain-level detail of molecular interactions in the IMEx Consortium binding domain data set
- 1University of Rome Tor Vergata
Abstract
The machinery of the cell depends on physical interactions, between proteins themselves, and between proteins and other biomolecules. The detailed characterisation of these interactions, including the identification of the precise sequence regions mediating binding events, is essential to understand both normal cell biology and disease mechanisms. Protein binding domains are specific regions of a protein sequence that mediate direct contact with a partner and represent a critical layer of functional annotation, bridging sequence, structure, and cellular function. Here we present the IMEx binding domain dataset, a large-scale, manually curated open-access set of molecular interactions assembled over more than two decades by the International Molecular Exchange (IMEx) Consortium. The dataset compiles experimentally derived binding region annotations from peer-reviewed literature, systematically linked to protein-protein interaction (PPI) records and mapped to standardised protein sequences in UniProtKB. We describe the curation model, data format, and content of the dataset, provide a descriptive and comparative analysis, and demonstrate the utility of the dataset as a gold standard for benchmarking interface prediction and variant effect annotation methods. Its integration with genomic variations further offers a route to elucidate the mechanistic basis of disease-associated mutations. The datasets are freely available through IntAct in the dedicated PSI-MI FeatureTAB format at https://ftp.ebi.ac.uk/pub/databases/intact/current/psimitab/features/ and are updated and enhanced with every release.
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BibTeX
@misc{pinto2026capturing,
title = {{Capturing domain-level detail of molecular interactions in the IMEx Consortium binding domain data set}},
author = {A. Pinto and P. Lo Surdo and J. J. Medina Reyes and L. Bergogne and C. Padilla Franzotti and M. Iannuccelli and S. Panni and K. Panneerselvam and S. Ricard Blum and E. Ragueneau and S. Orchard and H. Hermjakob and A. Zanzoni and L. Licata},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.15.759378},
url = {https://www.biorxiv.org/content/10.64898/2026.10.15.759378v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Capturing domain-level detail of molecular interactions in the IMEx Consortium binding domain data set
AU - A. Pinto
AU - P. Lo Surdo
AU - J. J. Medina Reyes
AU - L. Bergogne
AU - C. Padilla Franzotti
AU - M. Iannuccelli
AU - S. Panni
AU - K. Panneerselvam
AU - S. Ricard Blum
AU - E. Ragueneau
AU - S. Orchard
AU - H. Hermjakob
AU - A. Zanzoni
AU - L. Licata
PY - 2026
DA - 2026/10/15
PB - bioRxiv
DO - 10.64898/2026.10.15.759378
UR - https://www.biorxiv.org/content/10.64898/2026.10.15.759378v1
AB - The machinery of the cell depends on physical interactions, between proteins themselves, and between proteins and other biomolecules. The detailed characterisation of these interactions, including the identification of the precise sequence regions mediating binding events, is essential to understand both normal cell biology and disease mechanisms. Protein binding domains are specific regions of a protein sequence that mediate direct contact with a partner and represent a critical layer of functional annotation, bridging sequence, structure, and cellular function. Here we present the IMEx binding domain dataset, a large-scale, manually curated open-access set of molecular interactions assembled over more than two decades by the International Molecular Exchange (IMEx) Consortium. The dataset compiles experimentally derived binding region annotations from peer-reviewed literature, systematically linked to protein-protein interaction (PPI) records and mapped to standardised protein sequences in UniProtKB. We describe the curation model, data format, and content of the dataset, provide a descriptive and comparative analysis, and demonstrate the utility of the dataset as a gold standard for benchmarking interface prediction and variant effect annotation methods. Its integration with genomic variations further offers a route to elucidate the mechanistic basis of disease-associated mutations. The datasets are freely available through IntAct in the dedicated PSI-MI FeatureTAB format at https://ftp.ebi.ac.uk/pub/databases/intact/current/psimitab/features/ and are updated and enhanced with every release.
ER -