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Published on: December 1, 2020
BioLiP: a semi-manually curated database for biologically relevant ligand-protein interactions
Jianyi Yang1, Ambrish Roy, Yang Zhang
1Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI 48109-2218, USA.
Nucleic Acids Research
|October 23, 2012
Summary
BioLiP is a curated database of biologically relevant ligand-protein interactions, crucial for understanding protein functions. It filters Protein Data Bank (PDB) entries to ensure ligand relevance, aiding docking and function annotation.
Area of Science:
- Biochemistry
- Structural Biology
- Bioinformatics
Background:
- Understanding protein function relies on identifying biologically relevant ligand-protein interactions.
- The Protein Data Bank (PDB) contains many ligands, but not all are biologically relevant, complicating their use in downstream applications.
- Existing methods for predicting ligand-binding sites often use PDB structures, necessitating a reliable way to filter for biologically relevant ligands.
Purpose of the Study:
- To develop and implement a robust method for assessing the biological relevance of ligands in PDB structures.
- To construct BioLiP, a comprehensive database of biologically relevant ligand-protein interactions.
- To create a novel algorithm (COACH) for predicting ligand-binding sites to aid protein function annotation.
Main Methods:
- A hierarchical procedure involving four-step biological feature filtering and manual verification was developed to assess ligand relevance.
- This procedure was applied to curate the BioLiP database.
- The COACH algorithm was developed as a consensus-based method for predicting ligand-binding sites from protein sequence or structure.
Main Results:
- BioLiP was constructed, containing detailed annotations for each entry, including ligand-binding residues, affinity, catalytic sites, Enzyme Commission numbers, Gene Ontology terms, and database cross-links.
- The database is updated weekly, with the current release featuring 204,223 entries.
- The COACH algorithm provides a new tool for predicting ligand-binding sites, enhancing the functional annotation of uncharacterized proteins.
Conclusions:
- BioLiP provides a valuable resource for studying biologically relevant ligand-protein interactions, supporting applications like docking and function prediction.
- The developed filtering procedure effectively identifies relevant ligands from PDB structures.
- The COACH algorithm offers an effective approach for ligand-binding site prediction, facilitating protein function annotation.
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