ArticleNucleic acids research2019
Systematic domain-based aggregation of protein structures highlights DNA-, RNA- and other ligand-binding positions.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 19 citations in OpenAlex.
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- Faltwerk: a library for spatial exploratory data analysis of protein structures.Bioinformatics advances · 2023Article
- Neuroepigenetic Mechanisms of Action of Ultrashort Peptides in Alzheimer's Disease.International journal of molecular sciences · 2022Review
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- Protein domain-based prediction of drug/compound-target interactions and experimental validation on LIM kinases.PLoS computational biology · 2021Article
- dSPRINT: predicting DNA, RNA, ion, peptide and small molecule interaction sites within protein domains.Nucleic acids research · 2021Article
- CATH functional families predict functional sites in proteins.Bioinformatics (Oxford, England) · 2021Article
- "Protein aggregates" contain RNA and DNA, entrapped by misfolded proteins but largely rescued by slowing translational elongation.Aging cell · 2021Article
- PremPRI: Predicting the Effects of Missense Mutations on Protein-RNA Interactions.International journal of molecular sciences · 2020Article
- PertInInt: An Integrative, Analytical Approach to Rapidly Uncover Cancer Driver Genes with Perturbed Interactions and Functionalities.Cell systems · 2020Article
- Sharing DNA-binding information across structurally similar proteins enables accurate specificity determination.Nucleic acids research · 2020Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Domains 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 'frequencies' by aggregating protein co-complex structures by domain and ascertaining how often residues mapping to each domain position interact with ligands. We perform this domain-based analysis on ∼91000 co-complex structures, and infer positions involved in binding DNA, RNA, peptides, ions or small molecules across 4128 domains, which we refer to collectively as the InteracDome. Cross-validation testing reveals that ligand-binding positions for 2152 domains are highly consistent and can be used to identify residues facilitating interactions in ∼63-69% 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.
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