bioRxivBioinformaticsPreprint
Capturing domain-level detail of molecular interactions in the IMEx Consortium binding domain data set
Alessia PintoiD, Prisca Lo SurdoiD, Juan Jose Medina ReyesiD, Lou BergogneiD, Carla Luciana Padilla FranzottiiD, Marta IannuccelliiD, Simona PanniiD, Kalpana PanneerselvamiD, Sylvie Ricard‐BlumiD, Eliot RagueneauiD, Sandra E. OrchardiD, Henning HermjakobiD, Andreas ZanzoniiD, Luana LicataiD
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.
- assay: protein sequence
- assay: protein structure
- research focus: benchmarking
- research focus: variant effect prediction
- research focus: gene regulatory network inference
- research focus: protein structure prediction
- approach: statistical model
- approach: benchmark study
- Citations
- 0
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