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image of Integrated Network Pharmacology and Molecular Modeling Approach for Potential PTGS2 Inhibitors against Rheumatoid Arthritis

Abstract

Introduction

Rheumatoid arthritis (RA) is a chronic inflammatory condition of the joints and a leading cause of global disability. However, the use of current anti-inflammatory treatments is often limited by serious side effects and multi-organ toxicity, necessitating the exploration of safer alternatives.

Objective

This study aims to investigate the anti-rheumatic potential of natural compounds of as small-molecule inhibitors of PTGS2.

Methods

The therapeutic potential of was evaluated through antioxidant and anti-inflammatory assays. Gas chromatography-mass spectrometry (GC-MS) was used to identify its constituents. ADMET profiling (absorption, distribution, metabolism, excretion, and toxicity), network pharmacology, and molecular dynamics simulation were employed to uncover the active compounds against PTGS2 for RA treatment.

Results

extract contained significant phenolic (18.2 ± 0.008 mg GAE/g DW) and flavonoid (27.57 ± 0.03 mg RE/g DW) content. GC-MS yielded 288 compounds of which four passed the toxicity parameters. Protein-protein interaction analysis revealed 10 RA-related targets, with PTGS2 emerging as the most prominent one. Molecular docking and simulations revealed that compound-2 [2-Benzo [1,3] dioxol-5-yl-8-methoxy-3-nitro-2H-chromene] and compound-4 [alpha-hydroxy-N-[2-methoxyphenyl]-benzene propanamide] binds strongly with PTGS2 (-7.7 kcal/mol and -7.9 kcal/mol, respectively) predicting its stable interaction.

Conclusion

compounds present a significant potential as PTGS2 inhibitors, warranting further and investigations to confirm their therapeutic efficacy against RA.

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2025-07-09
2025-09-10

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Integrated Network Pharmacology and Molecular Modeling Approach for Potential PTGS2 Inhibitors against Rheumatoid Arthritis
Bentham Science Publishers ; https://doi.org/10.2174/0113816128370525250407164738
/content/journals/cpd/10.2174/0113816128370525250407164738
/content/journals/cpd/10.2174/0113816128370525250407164738
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  • Article Type:     Research Article
Keywords: ADMET ; Rheumatoid arthritis ; inflammation ; molecular dynamics simulation ; Cassia angustifolia ; network pharmacology

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