GLIDA: GPCR-ligand database for chemical genomic drug discovery

By Yasushi Okuno, Jiyoon Yang, Kei Taneishi, H. Yabuuchi, G. Tsujimoto. 2005

80 citations recorded by the source corpus.

G-protein coupled receptors (GPCRs) represent one of the most important families of drug targets in pharmaceutical development. GPCR-LIgand DAtabase (GLIDA) is a novel public GPCR-related chemical genomic database that is primarily focused on the correlation of information between GPCRs and their ligands. It provides correlation data between GPCRs and their ligands, along with chemical information on the ligands, as well as access information to the various web databases regarding GPCRs. These data are connected with each other in a relational database, allowing users in the field of GPCR-related drug discovery to easily retrieve such information from either biological or chemical starting points. GLIDA includes structure similarity search functions for the GPCRs and for their ligands. Thus, GLIDA can provide correlation maps linking the searched homologous GPCRs (or ligands) with their ligands (or GPCRs). By analyzing the correlation patterns between GPCRs and ligands, we can gain more detailed knowledge about their interactions and improve drug design efforts by focusing on inferred candidates for GPCR-specific drugs. GLIDA is publicly available at . We hope that it will prove very useful for chemical genomic research and GPCR-related drug discovery.

Subfields: Molecular Biology, Spectroscopy

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Citations in the corpus

ChEMBL: a large-scale bioactivity database for drug discovery (2011, background): “BRENDA provides binding constants for enzymes (14), IUPHAR contains ligand information for receptors and ion channels (15), while GLIDA (16) and GPCRDB (17) provide information speciﬁcally for G-protein-coupled receptors.”
BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities (2006, background): “GPCRDB [www.gpcr.org (7)], the IUPHAR receptor database (www.iuphar-db.org) and GLIDA [http:// gdds.pharm.kyoto-u.ac.jp/services/glida/index.php ( 8 )].”
STITCH 4: integration of protein–chemical interactions with user data (2013, background): “The second channel is made up of manually curated drug–target databases: DrugBank (12), GLIDA (13), Matador (14), TTD (15) and CTD (16); and pathway databases: KEGG (17), NCI/Nature Pathway Interaction Database (18), Reactome (19) and BioCyc (20) .”
STITCH 3: zooming in on protein–chemical interactions (2011, background): “Second, manually curated sources of drug targets: DrugBank (12), GLIDA (13), Matador (14), TTD (15) and CTD (16).”