Evidence map›Paper›PMID 21488099›Full record

ArticleProteins2011

Predicted structures of agonist and antagonist bound complexes of adenosine A3 receptor.

Soo-Kyung Kim, Lindsay Riley, Ravinder Abrol, Kenneth A Jacobson, William A Goddard

Open access · bronzeAbstract read
In one paragraph

Article in Proteins, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
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

17 citing papers in PubMed, 32 citations in OpenAlex.

  1. 4'-Thionucleosides as adenosine AMedicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026
    Review
  2. Article
  3. Review
  4. Review
  5. Identification and characterization of an atypical Gαs-biased βProceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  6. AJournal of computer-aided molecular design · 2019
    Article
  7. Article
  8. Article
  9. Predicting glycosaminoglycan surface protein interactions and implications for studying axonal growth.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Ligand- and mutation-induced conformational selection in the CCR5 chemokine G protein-coupled receptor.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
  16. SuperBiHelix method for predicting the pleiotropic ensemble of G-protein-coupled receptor conformations.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
  17. Article
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

5 authors at 3 institutions in 1 country.

Soo-Kyung KimDivision of Chemistry and Chemical Engineering, Materials and Process Simulation Center MC139-74, California Institute of Technology, Pasadena, California 91125, USA.
Lindsay Riley
Ravinder Abrol
Kenneth A Jacobson
William A Goddard
California Institute of Technology · USNational Institute of Diabetes and Digestive and Kidney Diseases · USUniversity of California, Los Angeles · US

Funding

Computer Modeling of G Protein-Coupled ReceptorsZIADK031126 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI JACOBSON, KENNETH ALAN · 2009 to 2025
$6.6M
Subtype Specific Agonists for D1-D5 Dopamine ReceptorsR21MH073910 · NIMH · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI GODDARD, WILLIAM ANDREW · 2006 to 2007
$357k
NIMH NIH HHS R21 MH073910
6 · The paper itself

Abstract

We used the GEnSeMBLE Monte Carlo method to predict ensemble of the 20 best packings (helix rotations and tilts) based on the neutral total energy (E) from a vast number (10 trillion) of potential packings for each of the four subtypes of the adenosine G protein-coupled receptors (GPCRs), which are involved in many cytoprotective functions. We then used the DarwinDock Monte Carlo methods to predict the binding pose for the human A(3) adenosine receptor (hAA(3)R) for subtype selective agonists and antagonists. We found that all four A(3) agonists stabilize the 15th lowest conformation of apo-hAA(3)R while also binding strongly to the 1st and 3rd. In contrast the four A(3) antagonists stabilize the 2nd or 3rd lowest conformation. These results show that different ligands can stabilize different GPCR conformations, which will likely affect function, complicating the design of functionally unique ligands. Interestingly all agonists lead to a trans χ1 angle for W6.48 that experiments on other GPCRs associate with G-protein activation while all 20 apo-AA(3)R conformations have a W6.48 gauche+ χ1 angle associated experimentally with inactive GPCRs for other systems. Thus docking calculations have identified critical ligand-GPCR structures involved with activation. We found that the predicted binding site for selective agonist Cl-IB-MECA to the predicted structure of hAA(3)R shows favorable interactions to three subtype variable residues, I253(6.58), V169(EL2), and Q167(EL2), while the predicted structure for hAA(2A)R shows weakened to the corresponding amino acids: T256(6.58), E169(EL2), and L167(EL2), explaining the observed subtype selectivity.

Indexed as

Adenosine A3 Receptor AgonistsAdenosine A3 Receptor AntagonistsAmino Acid SequenceBinding SitesComputer SimulationHumansModels, MolecularMolecular Sequence DataMonte Carlo MethodProtein BindingReceptor, Adenosine A3Sequence AlignmentAdenosine A3 Receptor AgonistsAdenosine A3 Receptor AntagonistsReceptor, Adenosine A3

Identifiers

PMID21488099
PMCPMC3092833
OpenAlexW2136171034

What OpenQuestion holds

Textmetadata
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Read underepoch 390

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.