Abstract
AbstractDomains are fundamental subunits of proteins, and while they play major roles in facilitating protein–DNA, protein–RNA and other protein–ligand interactions, a systematic assessment of their various interaction modes is still lacking. A comprehensive resource identifying positions within domains that tend to interact with nucleic acids, small molecules and other ligands would expand our knowledge of domain functionality as well as aid in detecting ligand-binding sites within structurally uncharacterized proteins. Here we introduce an approach to identify per-domain-position interaction “propensities” by aggregating protein co-complex structures by domain and ascertaining how frequently residues mapping to each domain position interact with ligands. We perform this domain-based analysis on ∼82,000 co-complex structures, and infer positions involved in binding DNA, RNA, peptides, ions, or small molecules across 4,120 domains, which we refer to collectively as the InteracDome. Cross-validation testing reveals that ligand-binding positions for 1,327 domains can be confidently modeled and used to identify residues facilitating interactions in ∼60–69% of human genes. Our resource of domain-inferred ligand-binding sites should be a great aid in understanding disease etiology: whereas these sites are enriched in Mendelian-associated and cancer somatic mutations, they are depleted in polymorphisms observed across healthy populations. The InteracDome is available at http://interacdome.princeton.edu.
Publisher
Cold Spring Harbor Laboratory