BioinformaticsBioinformaticsPeer-reviewed journal article
Annotation of biologically relevant ligands in UniProtKB using ChEBI
Elisabeth CoudertiD, Sébastien GéhantiD, Edouard de CastroiD, Monica PozzatoiD, Delphine BaratiniD, Teresa Batista NetoiD, Christian J A SigristiD, Nicole RedaschiiD, Alan James BridgeiD, Lucila AimoiD, Ghislaine Argoud‐PuyiD, Andrea H AuchinclossiD, Kristian B. AxelseniD, Parit BansaliD, Teresa M Batista Neto, Marie-Claude BlatteriD, Jerven Tjalling BollemaniD, Emmanuel BoutetiD, Lionel BreuzaiD, Blanca Cabrera GiliD, Cristina Casals‐CasasiD, Kamal Chikh Echioukh, Beatrice CucheiD, Anne EstreicheriD, Maria Livia FamigliettiiD, , Elena SperettaiD
Abstract
MotivationTo provide high quality, computationally tractable annotation of binding sites for biologically relevant (cognate) ligands in UniProtKB using the chemical ontology ChEBI (Chemical Entities of Biological Interest), to better support efforts to study and predict functionally relevant interactions between proteins and small molecule ligands. ResultsWe structured the data model for cognate ligand binding site annotations in UniProtKB and performed a complete reannotation of all cognate ligand binding sites using stable unique identifiers from ChEBI, which we now use as the reference vocabulary for all such annotations. We developed improved search and query facilities for cognate ligands in the UniProt website, REST API and SPARQL endpoint that leverage the chemical structure data, nomenclature, and classification that ChEBI provides. AvailabilityBinding site annotations for cognate ligands described using ChEBI are available for UniProtKB protein sequence records in several formats (text, XML, and RDF), and are freely available to query and download through the UniProt website (www.uniprot.org), REST API (www.uniprot.org/help/api), SPARQL endpoint (sparql.uniprot.org/), and FTP site (https://ftp.uniprot.org/pub/databases/uniprot/). Contactalan.bridge@sib.swiss Supplementary informationSupplementary Table 1.
- assay: protein sequence
- research focus: database / resource
- research focus: cell type annotation
- research focus: clustering
- research focus: dimensionality reduction
- approach: statistical model
- Citations
- 350
- FWCI
- 23.83
- Field percentile
- top 1%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- CysLENS: Interpretable signatures of cysteine ligandability from enantiomeric chemoproteomics and protein language models
Sameek Singh, Maja Wierzbinska, … Tian Zhang·bioRxiv·Aug 27, 2026
- PrankWeb: web server for ligand binding-site prediction and visualization
Lukáš Jendele, Radoslav Krivák, … David Hoksza·Nucleic Acids ResearchPeer-reviewed·May 9, 2019
- CavitySpace: A database of potential ligand binding sites in the human proteome
Shiwei Wang, Haoyu Lin, … Luhua Lai·BiomoleculesPeer-reviewed·Jul 11, 2022
- PrePCI: A structure- and chemical similarity-informed database of predicted protein compound interactions
Stephen J. Trudeau, Howook Hwang, … Barry H. Honig·Protein SciencePeer-reviewed·Feb 13, 2023
- E3 Ligase Ligandalyzer: A Structure-First, Ligand-Centric Platform for E3 Ligase Recruiter Selection
Joseph M. Schulz, Mainak Bardhan, … Stephan C. Schürer·bioRxiv·Oct 14, 2026
- ProCogGraph: A Graph-Based Mapping of Cognate Ligand Domain Interactions
Matthew R. Crown, Matthew Bashton·Bioinformatics AdvancesPeer-reviewed·Jan 1, 2024