Extraction of secondary metabolites and computational prediction of their anti-inflammatory potential

次生代谢产物的提取及其抗炎潜力的计算机预测

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Abstract

The increasing demand for herbal medicines as an alternative to synthetic drugs has gained significant attention due to their lower side effects and potential therapeutic benefits. This study aims to extract secondary metabolites from Curcuma longa (Turmeric), Zingiber officinale (Ginger), and Valeriana officinalis (Valerian) using four extraction techniques: Soxhlet, Clevenger, maceration, and hydro distillation. The extracted compounds were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS), and their interaction with TNF-α (PDB ID: 2AZ5), a key protein involved in rheumatoid arthritis, was evaluated through molecular docking studies using AutoDock software. The results indicated that valerian metabolites exhibited superior anti-inflammatory potential compared to Curcuma longa and Ginger, with the lowest binding energy and most stable interactions. These findings highlight the potential use of valerian as a natural inhibitor for autoimmune diseases like rheumatoid arthritis.

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