Evidence map›Paper›PMID 38702178›Full record

ArticleBMJ open ophthalmology2024

Unveiling molecular insights: in silico exploration of TLR4 antagonist for management of dry eye syndrome.

Kothandan Sudhakar, Neeru Dugar, Srikanth Jupudi, Ravichandran Ashwin, Kuppusamy Gowthamarajan

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Article in BMJ open ophthalmology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Kothandan SudhakarDepartment of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Ooty,The Nilgiris-643001, Tamil Nadu, India.ORCID 0000-0002-7643-2374
Neeru DugarDepartment of Pharmaceutical Chemistry, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Ooty, The Nilgiris-643001, Tamil Nadu, India.
Srikanth JupudiDepartment of Pharmaceutical Chemistry, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Ooty, The Nilgiris-643001, Tamil Nadu, India.
Ravichandran AshwinDepartment of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Ooty,The Nilgiris-643001, Tamil Nadu, India.
Kuppusamy GowthamarajanDepartment of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education and Research, Ooty,The Nilgiris-643001, Tamil Nadu, India gowthamsang@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDry eye disease is the most commonplace multifractional ocular complication, which has already affected millions of people in the world. It is identified by the excessive buildup of reactive oxygen species, leading to substantial corneal epithelial cell demise and ocular surface inflammation attributed to TLR4. In this study, we aimed to identify potential compounds to treat of dry eye syndrome by exploring in silico methods.

methodsIn this research, molecular docking and dynamics simulation tests were used to examine the effects of selected compounds on TLR4 receptor. Compounds were extracted from different databases and were prepared and docked against TLR4 receptor via Autodock Vina. Celastrol, lumacaftor and nilotinib were selected for further molecular dynamics studies for a deeper understanding of molecular systems consisting of protein and ligands by using the Desmond module of the Schrodinger Suite.

resultsThe docking results revealed that the compounds are having binding affinity in the range of -5.1 to -8.78 based on the binding affinity and three-dimensional interactions celastrol, lumacaftor and nilotinib were further studied for their activity by molecular dynamics. Among the three compounds, celastrol was the most stable based on molecular dynamics trajectory analysis from 100 ns in the catalytic pockets of 2Z63.pdb.pdb. Root mean square deviation of celastrol/2Z63 was in the range of 1.8-4.8 Å.

conclusionIn particular, Glu376 of TLR4 receptor is crucial for the identification and binding of lipopolysaccharides (LPS), which are part of Gram-negative bacteria's outer membrane. In our investigation, celastrol binds to Glu376, suggesting that celastrol may prevent the dry eye syndrome by inhibiting LPS's binding to TLR4.

Indexed as

Dry Eye SyndromesMolecular Docking SimulationMolecular Dynamics SimulationPentacyclic TriterpenesPyrimidinesToll-Like Receptor 4AminopyridinesComputer SimulationHumansLigandsTriterpenesAminopyridinescelastrolLigandsnilotinibPentacyclic TriterpenesPyrimidinesTLR4 protein, humanToll-Like Receptor 4TriterpenesEye LidsInfectionInflammationLacrimal glandOcular surface

Identifiers

PMID38702178
PMCPMC11086362

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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.