Evidence map›Paper›PMID 30390544›Full record

ArticleJournal of molecular graphics & modelling2019

GPCR homology model template selection benchmarking: Global versus local similarity measures.

Paige N Castleman, Chandler K Sears, Judith A Cole, Daniel L Baker, Abby L Parrill

Abstract read
In one paragraph

Article in Journal of molecular graphics & modelling, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. TBM preferred to AlphaFold 3 for functional models of insect odorant receptors.Computational and structural biotechnology journal · 2025
    Article
  2. G Protein-Coupled Receptor-Ligand Pose and Functional Class Prediction.International journal of molecular sciences · 2024
    Article
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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.

Paige N CastlemanThe University of Memphis, Department of Chemistry, USA.
Chandler K SearsThe University of Memphis, Department of Chemistry, USA.
Judith A ColeThe University of Memphis, Department of Biological Sciences, USA.
Daniel L BakerThe University of Memphis, Department of Chemistry, USA.
Abby L ParrillThe University of Memphis, Department of Chemistry, USA; The University of Memphis, Computational Research on Materials Institute (CROMIUM), USA. Electronic address: aparrill@memphis.edu.

Funding

GPR88 Ligand DiscoveryR15MH109034 · NIMH · UNIVERSITY OF MEMPHIS · PI PARRILL, ABBY L. · 2016 to 2016
$408k
NIMH NIH HHS R15 MH109034
6 · The paper itself

Abstract

G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for drug development. GPCR ligand interaction studies often have a starting point with either crystal structures or comparative models. The majority of GPCR do not have experimentally-characterized 3-dimensional structures, so comparative modeling, also called homology modeling, is a good structure-based starting point. Comparative modeling is a widely used method for generating models of proteins with unknown structures by analogy to crystallized proteins that are expected to exhibit structural conservation. Traditionally, comparative modeling template selection is based on global sequence identity and shared function. However high sequence identity localized to the ligand binding pocket may produce better models to examine protein-ligand interactions. This in silico benchmark study examined the performance of a global versus local similarity measure applied to comparative modeling template selection for 6 previously crystallized, class A GCPR (CXCR4, FFAR1, NOP, P2Y12, OPRK, and M1) with the long-term goal of optimizing GPCR ligand identification efforts. Comparative models were generated from templates selected using both global and local similarity measures. Similarity to reference crystal structures was reflected in RMSD values between atom positions throughout the structure or localized to the ligand binding pocket. Overall, models deviated from the reference crystal structure to a similar degree regardless of whether the template was selected using a global or local similarity measure. Ligand docking simulations were performed to assess relative performance in predicting protein-ligand complex structures and interaction networks. Calculated RMSD values between ligand poses from docking simulations and crystal structures indicate that models based on locally selected templates give docked poses that better mimic crystallographic ligand positions than those based on globally-selected templates in five of the six benchmark cases. However, protein model refinement strategies in advance of ligand docking applications are clearly essential as the average RMSD between crystallographic poses and poses docked into local template models was 9.7 Å and typically less than half of the ligand interaction sites are shared between the docked and crystallographic poses. These data support the utilization of local similarity measures to guide template selection in protocols using comparative models to investigate ligand-receptor interactions.

Indexed as

Molecular Dynamics SimulationProtein ConformationStructural Homology, ProteinLigandsMolecular Docking SimulationMolecular StructureReceptors, G-Protein-CoupledLigandsReceptors, G-Protein-CoupledComparative modelingComparative protein modelingDeorphanizationGPCRG protein-coupled receptorHomology modelingLigand identificationTemplate selection

Identifiers

PMID30390544
PMCPMC6449851

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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.