ArticleScientific reports2017
Systematic errors in detecting biased agonism: Analysis of current methods and development of a new model-free approach.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
37 citing papers in PubMed, 73 citations in OpenAlex.
- Mechanisms and Manifestations of Ligand Bias in Signaling: Focus on Receptor Tyrosine Kinases.Chemical reviews · 2026Review
- Agonism and Biased Signaling.Handbook of experimental pharmacology · 2026Review
- Biased Agonism at β-Adrenoceptor Subtypes: A Drug Development Perspective.Handbook of experimental pharmacology · 2026Review
- Biased Signaling and Its Role in the Genesis of Short- and Long-Acting βBiochemistry · 2025Article
- Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery.Nature reviews. Drug discovery · 2025Review
- Quantification of signal amplification for receptors: theFrontiers in pharmacology · 2025Article
- A critical re-evaluation of the slope factor of the operational model of agonism: When to exponentiate operational efficacy.Scientific reports · 2023Article
- Quantitative assessment of ligand bias from bias plots: The bias coefficient "kappa".Biochimica et biophysica acta. General subjects · 2023Article
- Structure-Activity Assessment and In-Depth Analysis of Biased Agonism in a Set of Phenylalkylamine 5-HTACS chemical neuroscience · 2023Article
- Quantitative receptor model for responses that are left- or right-shifted versus occupancy (are more or less concentration sensitive): the SABRE approach.Frontiers in pharmacology · 2023Article
- Fingerprinting heterocellular β-adrenoceptor functional expression in the brain using agonist activity profiles.Frontiers in molecular biosciences · 2023Article
- Quantification of receptor binding from response data obtained at different receptor levels: a simple individual sigmoid fitting and a unified SABRE approach.Scientific reports · 2022Article
- Community guidelines for GPCR ligand bias: IUPHAR review 32.British journal of pharmacology · 2022Review
- Biased agonists of the chemokine receptor CXCR3 differentially signal through GαScience signaling · 2022Article
- Ligands with different dimeric configurations potently activate the EphA2 receptor and reveal its potential for biased signaling.iScience · 2022Article
- The therapeutic potential of GLP-1 receptor biased agonism.British journal of pharmacology · 2022 · on this mapReview
- Comprehensive Signaling Profiles Reveal Unsuspected Functional Selectivity of δ-Opioid Receptor Agonists and Allow the Identification of Ligands with the Greatest Potential for Inducing Cyclase Superactivation.ACS pharmacology & translational science · 2021Article
- Acylation of the Incretin Peptide Exendin-4 Directly Impacts Glucagon-Like Peptide-1 Receptor Signaling and Trafficking.Molecular pharmacology · 2021Article
- Partial agonism improves the anti-hyperglycaemic efficacy of an oxyntomodulin-derived GLP-1R/GCGR co-agonist.Molecular metabolism · 2021Article
- Evaluation of efficacy- versus affinity-driven agonism with biased GLP-1R ligands P5 and exendin-F1.Biochemical pharmacology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
Abstract
Discovering biased agonists requires a method that can reliably distinguish the bias in signalling due to unbalanced activation of diverse transduction proteins from that of differential amplification inherent to the system being studied, which invariably results from the non-linear nature of biological signalling networks and their measurement. We have systematically compared the performance of seven methods of bias diagnostics, all of which are based on the analysis of concentration-response curves of ligands according to classical receptor theory. We computed bias factors for a number of β-adrenergic agonists by comparing BRET assays of receptor-transducer interactions with Gs, Gi and arrestin. Using the same ligands, we also compared responses at signalling steps originated from the same receptor-transducer interaction, among which no biased efficacy is theoretically possible. In either case, we found a high level of false positive results and a general lack of correlation among methods. Altogether this analysis shows that all tested methods, including some of the most widely used in the literature, fail to distinguish true ligand bias from "system bias" with confidence. We also propose two novel semi quantitative methods of bias diagnostics that appear to be more robust and reliable than currently available strategies.
Indexed as
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.