ArticleBioinformatics (Oxford, England)2015
GLASS: a comprehensive database for experimentally validated GPCR-ligand associations.
Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 1 of them a synthesis that pooled it.
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Who cites it
66 citing papers in PubMed, 1 synthesis or guideline pooled it, 146 citations in OpenAlex.
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- Integrated Computer-Aided Drug Design: Advances in GPCR Natural Ligand Discovery.Cell biochemistry and biophysics · 2026Review
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- MoleProLink-RL: geometric transport for domain-policy reinforcement learning in drug-target interaction prediction.NPJ digital medicine · 2025Article
- In silico methods for drug-target interaction prediction.Cell reports methods · 2025Review
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- Developing muscarinic receptor M1 classification models utilizing transfer learning and generative AI techniques.Scientific reports · 2025Article
- The chordata olfactory receptor database.Protein & cell · 2025Article
- Recent trends in machine learning and deep learning-based prediction of G-protein coupled receptor-ligand binding affinities.Frontiers in bioinformatics · 2025Review
- Leveraging Artificial Intelligence in GPCR Activation Studies: Computational Prediction Methods as Key Drivers of Knowledge.Methods in molecular biology (Clifton, N.J.) · 2025Article
- BASE: a web service for providing compound-protein binding affinity prediction datasets with reduced similarity bias.BMC bioinformatics · 2024Article
- A comprehensive comparison of deep learning-based compound-target interaction prediction models to unveil guiding design principles.Journal of cheminformatics · 2024Article
- A deep learning framework combining molecular image and protein structural representations identifies candidate drugs for pain.Cell reports methods · 2024Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
motivationG protein-coupled receptors (GPCRs) are probably the most attractive drug target membrane proteins, which constitute nearly half of drug targets in the contemporary drug discovery industry. While the majority of drug discovery studies employ existing GPCR and ligand interactions to identify new compounds, there remains a shortage of specific databases with precisely annotated GPCR-ligand associations.
resultsWe have developed a new database, GLASS, which aims to provide a comprehensive, manually curated resource for experimentally validated GPCR-ligand associations. A new text-mining algorithm was proposed to collect GPCR-ligand interactions from the biomedical literature, which is then crosschecked with five primary pharmacological datasets, to enhance the coverage and accuracy of GPCR-ligand association data identifications. A special architecture has been designed to allow users for making homologous ligand search with flexible bioactivity parameters. The current database contains ∼500 000 unique entries, of which the vast majority stems from ligand associations with rhodopsin- and secretin-like receptors. The GLASS database should find its most useful application in various in silico GPCR screening and functional annotation studies. AVAILABILITY AND IMPLEMENTATION: The website of GLASS database is freely available at http://zhanglab.ccmb.med.umich.edu/GLASS/. CONTACT: zhng@umich.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.