In Silico Study of Bioactive Compounds from Moringa oleifera Extract as Anti-Inflammatory Candidates Targeting the Inflammatory Mediator PGD2

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Abstract

Conventional anti-inflammatory drugs may cause serious adverse effects, creating a need for safer plant-derived therapeutic candidates. Although Moringa oleifera has recognized biological potential, computational evidence regarding the anti-inflammatory activity of its phytoconstituents against prostaglandin D₂ 11-ketoreductase (AKR1C3; PDB ID: 1S2A) remains limited. This in silico study evaluated 12 bioactive compounds from an ethanolic extract of M. oleifera as potential inhibitors of this molecular target. Pharmacokinetic properties and oral bioavailability were predicted using SwissADME according to Lipinski’s rule of five. Molecular docking was subsequently performed using Molecular Operating Environment 2019 to evaluate ligand–receptor binding affinities based on Gibbs free energy (ΔG) and root-mean-square deviation (RMSD). The physicochemical assessment showed that 11 compounds had favorable predicted membrane permeability and systemic absorption, whereas rutin violated Lipinski’s criteria. Docking analysis identified quercetin, apigetrin, chlorogenic acid, ellagic acid, and naringenin as the most promising candidates. These compounds exhibited the lowest ΔG values and stable binding conformations, with RMSD values below 2.0 Å. The findings indicate that these five phytoconstituents have favorable predicted interactions with AKR1C3 and may possess potential anti-inflammatory activity associated with PGD₂ metabolism. Accordingly, they represent promising lead compounds for developing selective plant-derived anti-inflammatory agents. This study provides a computational foundation for future molecular dynamics simulations and clinical validation.

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Article Details

How to Cite
Sabilla, P., & Sari, T. K. (2026). In Silico Study of Bioactive Compounds from Moringa oleifera Extract as Anti-Inflammatory Candidates Targeting the Inflammatory Mediator PGD2. Journal of Multidisciplinary Science: MIKAILALSYS, 4(3), 5692-5702. https://doi.org/10.58578/mikailalsys.v4i3.11832

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