Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 368

The DOI matches its Crossref record.

Diversity and Selectivity of Receptor-G Protein Interaction

Gudermann, T, Kalkbrenner, F, Schultz, G·1996·Annual Review of Pharmacology and Toxicology

Abstract

Cells in a living organism communicate with each other through extracellular molecules such as hormones, neurotransmitters, and growth factors. The majority of these molecules transmit their signal by interacting with a three-protein transmembrane signal transduction system whose single components interact sequentially and reversibly. Agonist binding to a heptahelical receptor results in activation of heterotrimeric guanine nucleotide-binding proteins (G proteins) that modulate the activity of one or more effector systems. Considering that hundreds of G protein-coupled receptors transduce signals by interacting with a limited repertoire of G proteins, the question of specificity governing the coupling of receptors to G proteins arises. The conceptualization of signal transduction pathways in a linear fashion (one receptor coupling to one G protein that activates one effector) is inadequate to explain experimental results. In the present review, G protein-mediated signal transduction is depicted as a complex signaling network with divergent and convergent pathways at each transduction level, i.e. receptor, G protein, and effector. The recent realization that "classical" signaling pathways appear to be activated in parallel with signaling cascades primarily described for growth factors and cytokines adds an additional level of intriguing complexity.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1146/annurev.pa.36.040196.002241

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 368

Metadata

Authors
Gudermann, T., Kalkbrenner, F., & Schultz, G.
Venue
Annual Review of Pharmacology and Toxicology
Published
1996-04
Volume
36
Issue
1
Pages
429-459
ISSN
  • 0362-1642 (ISSN-L)
  • 1545-4304
OpenAlex
W2172659222
Cited by
368
References
0
FWCI
14.72
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Diversity and Selectivity of Receptor-G Protein Interaction. https://app.cochat.ai/papers/10.1146/annurev.pa.36.040196.002241
The paper
Gudermann, T., Kalkbrenner, F., & Schultz, G. (1996). Diversity and Selectivity of Receptor-G Protein Interaction. Annual Review of Pharmacology and Toxicology. https://doi.org/10.1146/annurev.pa.36.040196.002241

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.