Evidence map›Paper›PMID 30616825›Full record

ArticleMethods in cell biology2019

Modeling the complete chemokine-receptor interaction.

Michael J Wedemeyer, Benjamin K Mueller, Brian J Bender, Jens Meiler, Brian F Volkman

Open access · greenAbstract read
In one paragraph

Article in Methods in cell biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.1field-weighted citation impact, top 9% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Controllable Protein Design by Prefix-Tuning Protein Language Models.Journal of chemical information and modeling · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Comparative modeling and docking of chemokine-receptor interactions with Rosetta.Biochemical and biophysical research communications · 2020
    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 2 institutions in 1 country.

Michael J WedemeyerDepartment of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, United States.
Benjamin K MuellerDepartment of Chemistry, Vanderbilt University, Nashville, TN, United States; Center for Structural Biology, Vanderbilt University, Nashville, TN, United States.
Brian J BenderCenter for Structural Biology, Vanderbilt University, Nashville, TN, United States; Department of Pharmacology, Vanderbilt University, Nashville, TN, United States.
Jens MeilerDepartment of Chemistry, Vanderbilt University, Nashville, TN, United States; Center for Structural Biology, Vanderbilt University, Nashville, TN, United States; Department of Pharmacology, Vanderbilt University, Nashville, TN, United States.
Brian F VolkmanDepartment of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, United States. Electronic address: bvolkman@gmail.com.
Vanderbilt University · USMedical College of Wisconsin · US

Funding

Translational Analysis CoreP30DK058404 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI RICHARD M. PEEK · 2002 to 2026
$29.9M
ROSETTA An Integrated Protein Structure Modeling SuiteR01GM073151 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KUHLMAN, BRIAN A · 2005 to 2019
$7.8M
Membrane Protein Structure Elucidation from sparse NMR data (KAMP)R01GM080403 · NIGMS · VANDERBILT UNIVERSITY · PI MEILER, JENS · 2007 to 2019
$3.0M
Structural Determinants of Allosteric Modulation of Brain GPCRsR01DA046138 · NIDA · VANDERBILT UNIVERSITY · PI MEILER, JENS · 2019 to 2023
$2.0M
Cheminformatics of Allosteric mGluR Modulation promotes Therapeutic DevelopmentR01MH090192 · NIMH · VANDERBILT UNIVERSITY · PI MEILER, JENS · 2010 to 2013
$1.5M
High-Performance Computer Cluster for Biomedical ResearchS10OD023680 · OD · VANDERBILT UNIVERSITY · PI MEILER, JENS · 2017 to 2017
$587k
NIDA NIH HHS R01 DA046138NIDDK NIH HHS P30 DK058404NIGMS NIH HHS R01 GM073151NIGMS NIH HHS R01 GM080403NIH HHS S10 OD023680NIMH NIH HHS R01 MH090192
6 · The paper itself

Abstract

Chemokines are soluble, secreted proteins that induce chemotaxis of leukocytes and other cells. Migratory cells can sense the chemokine concentration gradient following chemokine binding and activation of chemokine receptors, a subset of the G protein-coupled receptor (GPCR) superfamily. Chemokine receptor signaling plays a central role in cell migration during inflammatory responses as well as in cancer and other diseases. Given their important role in mediating essential pathologic and physiologic processes, chemokines and their receptors are attractive targets for therapeutic development. A better understanding of the molecular basis of chemokine-GPCR interactions will aid in the understanding of the mechanistic basis for chemokine function in disease-related processes, as well as aid in the design of new therapeutics. High resolution protein structures are critical for determining these mechanisms and investigating the interactions between approximately 50 chemokines and 20 chemokine receptors. Currently, three unique structures of chemokine-GPCR complexes have been determined and have greatly broadened our knowledge of this large protein-protein interaction. While these structures represent only a small fraction of clinically relevant chemokines and receptors, they can be exploited as scaffolds for homology modeling to understand the chemokine-GPCR interactions. This chapter presents a specialized methodology to construct and validate models of chemokine-GPCR complexes using the Rosetta software suite.

Indexed as

Models, MolecularAnimalsHumansReceptors, ChemokineReceptors, ChemokineChemokineChemokine receptorGPCR interfaceG protein-coupled receptorHomology modelingMulti-receptor/multi-ligand systemRosetta

Identifiers

PMID30616825
PMCPMC6790067
OpenAlexW2898933261

What OpenQuestion holds

Textmetadata
LicenceTDM
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.