Evidence map›Paper›PMID 24304920›Full record

ArticleActa pharmacologica Sinica2013

Molecular modeling, quantum polarized ligand docking and structure-based 3D-QSAR analysis of the imidazole series as dual AT(1) and ET(A) receptor antagonists.

Khuraijam Dhanachandra Singh, Karthikeyan Muthusamy

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Article in Acta pharmacologica Sinica, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

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19citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
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  9. BioMed research international · 2022
    Article
  10. Article
  11. Novel allosteric ligands of the angiotensin receptor AT1R as autoantibody blockers.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Molecular Modeling of ClonedIndian journal of microbiology · 2017
    Article
  16. Article
  17. Article
  18. CombinatorialFrontiers in molecular neuroscience · 2017
    Article
  19. Review
4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Khuraijam Dhanachandra SinghDepartment of Bioinformatics, Alagappa University, Karaikudi - 630 004, Tamil Nadu, India.
Karthikeyan Muthusamy

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimBoth endothelin ETA receptor antagonists and angiotensin AT1 receptor antagonists lower blood pressure in hypertensive patients. A dual AT1 and ETA receptor antagonist may be more efficacious antihypertensive drug. In this study we identified the mode and mechanism of binding of imidazole series of compounds as dual AT1 and ETA receptor antagonists.

methodsMolecular modeling approach combining quantum-polarized ligand docking (QPLD), MM/GBSA free-energy calculation and 3D-QSAR analysis was used to evaluate 24 compounds as dual AT1 and ETA receptor antagonists and to reveal their binding modes and structural basis of the inhibitory activity. Pharmacophore-based virtual screening and docking studies were performed to identify more potent dual antagonists.

results3D-QSAR models of the imidazole compounds were developed from the conformer generated by QPLD, and the resulting models showed a good correlation between the predicted and experimental activity. The visualization of the 3D-QSAR model in the context of the compounds under study revealed the details of the structure-activity relationship: substitution of methoxymethyl and cyclooctanone might increase the activity against AT1 receptor, while substitution of cyclohexone and trimethylpyrrolidinone was important for the activity against ETA receptor; addition of a trimethylpyrrolidinone to compound 9 significantly reduced its activity against AT1 receptor but significantly increased its activity against ETA receptor, which was likely due to the larger size and higher intensities of the H-bond donor and acceptor regions in the active site of ETA receptor. Pharmacophore-based virtual screening followed by subsequent Glide SP, XP, QPLD and MM/GBSA calculation identified 5 potential lead compounds that might act as dual AT1 and ETA receptor antagonists.

conclusionThis study may provide some insights into the development of novel potent dual ETA and AT1 receptor antagonists. As a result, five compounds are found to be the best dual antagonists against AT1R and ETA receptors.

Indexed as

Endothelin A Receptor AntagonistsQuantum TheoryAmino Acid SequenceAngiotensin II Type 1 Receptor BlockersHumansImidazolesLigandsModels, MolecularMolecular Dynamics SimulationMolecular Sequence DataProtein BindingQuantitative Structure-Activity RelationshipSequence Homology, Amino AcidAngiotensin II Type 1 Receptor BlockersEndothelin A Receptor AntagonistsImidazolesLigands

Identifiers

PMID24304920
PMCPMC4002566

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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.