SKRINING SENYAWA METABOLIT SEKUNDER Lansium domesticum YANG BERPOTENSI SEBAGAI ANTIINFLAMASI TERHADAP ENZIM INDUCIBLE NITRIC OXIDE SYNTHASE SECARA IN SILICO

HABIBURRAHMAN, MUHAMMAD and Hanum, Laila (2025) SKRINING SENYAWA METABOLIT SEKUNDER Lansium domesticum YANG BERPOTENSI SEBAGAI ANTIINFLAMASI TERHADAP ENZIM INDUCIBLE NITRIC OXIDE SYNTHASE SECARA IN SILICO. Undergraduate thesis, Sriwijaya University.

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Abstract

Inflammation is one of the many ways the body's immune system fights disease, but uncontrolled inflammation can lead to acute inflammation. NSAIDs have several side effects, necessitating the need for natural alternative medications. INOS is one of the enzymes that cause acute inflammation if it cannot be stopped. Compounds from Lansium domesticum are known to have anti-inflammatory properties. Molecular docking can be performed to predict the interaction of compounds with the INOSOX enzyme target in silico, thus screening secondary metabolite compounds of Lansium domesticum that have the potential as anti-inflammatory agents by inhibiting INOSOX activity, yielding low binding affinity values from molecular docking results. The method used is experimental, in silico approach, involving the prediction of biological activity, physicochemical properties, pharmacokinetics, and molecular docking. Molecular docking is conducted to obtain affinity values and visualize ligand-receptor interactions. From the screening, 53 compounds were predicted to have anti-inflammatory biological activity, and further physicochemical and pharmacokinetic predictions narrowed it down to 9 compounds for molecular docking. The molecular docking results identified potential anti-inflammatory compounds, including Ellagic Acid, (+)-Spathulenol, α-cadinene, and τ-Muurolol, which are capable of inhibiting the active site of the INOSOX enzyme in silico.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Antiinflamasi, Lansium domesticum, INOSOX, In silico
Subjects:	Q Science > QH Natural history > QH301 Biology
Divisions:	08-Faculty of Mathematics and Natural Science > 46201-Biology (S1)
Depositing User:	Muhammad Habiburrahman
Date Deposited:	14 May 2025 05:35
Last Modified:	14 May 2025 05:35
URI:	http://repository.unsri.ac.id/id/eprint/172090

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