Evidence map›Paper›PMID 40947475›Full record

ReviewHandbook of experimental pharmacology2026

Future Directions in GPCR Biased Signaling and Ligand Pharmacology.

Dannya Estau, Zijian Li

Abstract readReview
PubMed Publisher
In one paragraph

Review in Handbook of experimental pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Dannya EstauDepartment of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; Beijing Key Laboratory of Cardiovascular Receptors Research, State Key Laboratory of Vascular Homeostasis and Remodeling, and NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Peking University; Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking University, Beijing, China.
Zijian LiDepartment of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; Beijing Key Laboratory of Cardiovascular Receptors Research, State Key Laboratory of Vascular Homeostasis and Remodeling, and NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Peking University; Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking University, Beijing, China. lizijian@bjmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

G protein-coupled receptor (GPCR) biased signaling has emerged as a transformative paradigm, reshaping both fundamental understanding of receptor biology and pharmacological intervention. Significant advances have been made in deciphering the mechanisms underlying biased signaling and in the development of ligands that selectively engage specific pathways. Here, we outline key future directions in GPCR biased signaling and ligand pharmacology including the biased signaling theories, structural insights, methodological innovations and ligand pharmacology theories. We hope that these perspectives will contribute to pharmacological research, drug R & D, and clinical drug research and promoting safer and more effective GPCR-targeted treatments for human diseases.

Indexed as

Receptors, G-Protein-CoupledSignal TransductionAnimalsHumansLigandsLigandsReceptors, G-Protein-CoupledBiased signalingFuture directionsG protein-coupled receptorLigand pharmacology

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.