Evidence map›Paper›PMID 25141027›Full record

ArticleJournal of chemical information and modeling2014

Modeling, molecular dynamics simulation, and mutation validation for structure of cannabinoid receptor 2 based on known crystal structures of GPCRs.

Zhiwei Feng, Mohammed Hamed Alqarni, Peng Yang, Qin Tong, Ananda Chowdhury, Lirong Wang, Xiang-Qun Xie

Abstract readValidation Study
In one paragraph

Article in Journal of chemical information and modeling, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
5.6field-weighted citation impact, top 3% 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

45 citing papers in PubMed, 92 citations in OpenAlex.

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  3. Metabolism-guided development of Ko143 analogs as ABCG2 inhibitors.European journal of medicinal chemistry · 2023
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  11. ViphyllinJournal of pain research · 2022
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  15. Insight intoACS omega · 2020
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  16. Article
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  20. DAKB-GPCRs: An Integrated Computational Platform for Drug Abuse Related GPCRs.Journal of chemical information and modeling · 2019
    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

7 authors at 2 institutions in 1 country.

Zhiwei FengDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, ‡Computational Drug Abuse Research Center, §Drug Discovery Institute, and ∥Department of Computational Biology and Department of Structural Biology, University of Pittsburgh , Pittsburgh, Pennsylvania 15261, United States.
Mohammed Hamed Alqarni
Peng Yang
Qin Tong
Ananda Chowdhury
Lirong Wang
Xiang-Qun Xie
Discovery Institute · USUniversity of Pittsburgh · US

Funding

NIDA Center of Excellence OF Computational Drug Abuse Research (CDAR)P30DA035778 · NIDA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BAHAR, IVET, XIE, XIANG-QUN · 2014 to 2018
$5.4M
Structure/Function of the CB2 Receptor Binding and G-protein Recognition PocketsR01DA025612 · NIDA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI XIE, XIANG-QUN · 2010 to 2014
$1.7M
NIDA NIH HHS P30 DA035778NIDA NIH HHS P30 DA035778A1NIDA NIH HHS R01 DA025612
6 · The paper itself

Abstract

The cannabinoid receptor 2 (CB2) plays an important role in the immune system. Although a few of GPCRs crystallographic structures have been reported, it is still challenging to obtain functional transmembrane proteins and high resolution X-ray crystal structures, such as for the CB2 receptor. In the present work, we used 10 reported crystal structures of GPCRs which had high sequence identities with CB2 to construct homology-based comparative CB2 models. We applied these 10 models to perform a prescreen by using a training set consisting of 20 CB2 active compounds and 980 compounds randomly selected from the National Cancer Institute (NCI) database. We then utilized the known 170 cannabinoid receptor 1 (CB1) or CB2 selective compounds for further validation. Based on the docking results, we selected one CB2 model (constructed by β1AR) that was most consistent with the known experimental data, revealing that the defined binding pocket in our CB2 model was well-correlated with the training and testing data studies. Importantly, we identified a potential allosteric binding pocket adjacent to the orthosteric ligand-binding site, which is similar to the reported allosteric pocket for sodium ion Na(+) in the A2AAR and the δ-opioid receptor. Our studies in correlation of our data with others suggested that sodium may reduce the binding affinities of endogenous agonists or its analogs to CB2. We performed a series of docking studies to compare the important residues in the binding pockets of CB2 with CB1, including antagonist, agonist, and our CB2 neutral compound (neutral antagonist) XIE35-1001. Then, we carried out 50 ns molecular dynamics (MD) simulations for the CB2 docked with SR144528 and CP55940, respectively. We found that the conformational changes of CB2 upon antagonist/agonist binding were congruent with recent reports of those for other GPCRs. Based on these results, we further examined one known residue, Val113(3.32), and predicted two new residues, Phe183 in ECL2 and Phe281(7.35), that were important for SR144528 and CP55940 binding to CB2. We then performed site-directed mutation experimental study for these residues and validated the predictions by radiometric binding affinity assay.

Indexed as

Molecular Dynamics SimulationCrystallography, X-RayMutagenesis, Site-DirectedProtein ConformationReceptor, Cannabinoid, CB2Receptors, G-Protein-CoupledReceptor, Cannabinoid, CB2Receptors, G-Protein-Coupled

Identifiers

PMID25141027
PMCPMC4170816
OpenAlexW2064573845

What OpenQuestion holds

Textmetadata
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.