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GLASS: a comprehensive database for experimentally validated GPCR-ligand associations
Wallace K B Chan1, Hongjiu Zhang1, Jianyi Yang1
1Department of Biological Chemistry, Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA, Department of Basic Sciences, University of North Dakota, School of Medicine and Health Sciences, Grand Forks, ND 58203, USA and Department of Computer Engineering, Bogazici University, Istanbul, Turkey.
A new database, GLASS, offers manually curated, experimentally validated G protein-coupled receptor (GPCR) and ligand associations. It uses a text-mining algorithm and cross-references pharmacological data to improve accuracy for drug discovery and functional annotation studies.
Area of Science:
- Biochemistry
- Pharmacology
- Bioinformatics
Background:
- G protein-coupled receptors (GPCRs) are crucial membrane proteins and represent nearly half of drug targets in drug discovery.
- Existing drug discovery efforts often rely on known GPCR-ligand interactions, but there's a lack of databases with precise association data.
Purpose of the Study:
- To develop GLASS, a comprehensive, manually curated database of experimentally validated GPCR-ligand associations.
- To enhance the accuracy and coverage of GPCR-ligand association data through a novel text-mining approach and cross-referencing with pharmacological datasets.
Main Methods:
- A text-mining algorithm was developed to extract GPCR-ligand interactions from biomedical literature.
- Extracted data was cross-referenced with five primary pharmacological datasets for validation and accuracy enhancement.
- A specialized architecture was implemented for homologous ligand searches with flexible bioactivity parameters.
Main Results:
- The GLASS database contains approximately 500,000 unique GPCR-ligand entries.
- The majority of entries involve associations with rhodopsin-like and secretin-like receptors.
- The database is designed for in silico GPCR screening and functional annotation.
Conclusions:
- GLASS provides a valuable resource for researchers in GPCR drug discovery.
- The database facilitates in silico screening and functional annotation of GPCRs.
- The manual curation and cross-validation ensure high-quality GPCR-ligand association data.