This is a preprint.
DrugDomain 2.0: comprehensive database of protein domains-ligands/drugs interactions across the whole Protein Data Bank
- PMID: 40672152
- PMCID: PMC12265713
- DOI: 10.1101/2025.07.03.663025
DrugDomain 2.0: comprehensive database of protein domains-ligands/drugs interactions across the whole Protein Data Bank
Update in
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DrugDomain 2.0: Comprehensive database of protein domains-ligands/drugs interactions across the whole Protein Data Bank.Comput Struct Biotechnol J. 2025 Sep 12;27:4040-4047. doi: 10.1016/j.csbj.2025.09.018. eCollection 2025. Comput Struct Biotechnol J. 2025. PMID: 41017823 Free PMC article.
Abstract
Proteins carry out essential cellular functions - signaling, metabolism, transport - through the specific interaction of small molecules and drugs within their three-dimensional structural domains. Protein domains are conserved folding units that, when combined, drive evolutionary progress. The Evolutionary Classification Of protein Domains (ECOD) places domains into a hierarchy explicitly built around distant evolutionary relationships, enabling the detection of remote homologs across the proteomes. Yet no single resource has systematically mapped domain-ligand interactions at the structural level. To fill this gap, we introduce DrugDomain v2.0, an updated comprehensive resource, that extends earlier releases by linking evolutionary domain classifications (ECOD) to ligand binding events across the entire Protein Data Bank. We also leverage AI-driven predictions from AlphaFold to extend domain-ligand annotations to human drug targets lacking experimental structures. DrugDomain v2.0 catalogs interactions with over 37,000 PDB ligands and 7,560 DrugBank molecules, integrates more than 6,000 small-molecule-associated post-translational modifications, and provides context for 14,000+ PTM-modified human protein models featuring docked ligands. The database encompasses 43,023 unique UniProt accessions and 174,545 PDB structures. The DrugDomain data is available online: https://drugdomain.cs.ucf.edu/ and https://github.com/kirmedvedev/DrugDomain.
Keywords: Database; Drug discovery; Drugs; Protein domains; Protein-drug interaction; Small molecules.
Conflict of interest statement
Competing interests The authors declare that there are no competing interests associated with the manuscript.
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