ArticleBioinformatics advances2021
pdCSM-GPCR: predicting potent GPCR ligands with graph-based signatures.
Article in Bioinformatics advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 24 citations in OpenAlex.
- Labels as a feature: Network homophily for systematically annotating human GPCR drug-target interactions.Nature communications · 2025Article
- AiGPro: a multi-tasks model for profiling of GPCRs for agonist and antagonist.Journal of cheminformatics · 2025Article
- Leveraging Artificial Intelligence in GPCR Activation Studies: Computational Prediction Methods as Key Drivers of Knowledge.Methods in molecular biology (Clifton, N.J.) · 2025Article
- piscesCSM: prediction of anticancer synergistic drug combinations.Journal of cheminformatics · 2024Article
- Engineering G protein-coupled receptors for stabilization.Protein science : a publication of the Protein Society · 2024Article
- Exploring the Therapeutic Potential ofMolecules (Basel, Switzerland) · 2024Article
- Decrypting orphan GPCR drug discovery via multitask learning.Journal of cheminformatics · 2024Article
- Opsin expression varies across larval development and taxa in pteriomorphian bivalves.Frontiers in neuroscience · 2024Article
- AI-Driven Enhancements in Drug Screening and Optimization.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Orphan G protein-coupled receptors: the ongoing search for a home.Frontiers in pharmacology · 2024Review
- FP-MAP: an extensive library of fingerprint-based molecular activity prediction tools.Frontiers in chemistry · 2023Article
- cropCSM: designing safe and potent herbicides with graph-based signatures.Briefings in bioinformatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 3 countries.
Funding
Abstract
motivationG protein-coupled receptors (GPCRs) can selectively bind to many types of ligands, ranging from light-sensitive compounds, ions, hormones, pheromones and neurotransmitters, modulating cell physiology. Considering their role in many essential cellular processes, they are one of the most targeted protein families, with over a third of all approved drugs modulating GPCR signalling. Despite this, the large diversity of receptors and their multipass transmembrane architectures make the identification and development of novel specific, and safe GPCR ligands a challenge. While computational approaches have the potential to assist GPCR drug development, they have presented limited performance and generalization capabilities. Here, we explored the use of graph-based signatures to develop pdCSM-GPCR, a method capable of rapidly and accurately screening potential GPCR ligands.
resultsBioactivity data (IC50, EC50, AVAILABILITY AND IMPLEMENTATION: pdCSM-GPCR predictive models and datasets used have been made available via a freely accessible and easy-to-use web server at http://biosig.unimelb.edu.au/pdcsm_gpcr/. SUPPLEMENTARY INFORMATION: Supplementary data are available at
Identifiers
What OpenQuestion holds
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.