Metabolite profiling of 96% ethanol extract from Marsilea crenata presl. leaves using UPLC-QToF-MS/MS and anti-neuroinflammatory predicition activity with molecular docking

Ma'arif, Burhan, Mirza, Denis Mery, Suryadinata, Arief and Agil, Mangestuti (2019) Metabolite profiling of 96% ethanol extract from Marsilea crenata presl. leaves using UPLC-QToF-MS/MS and anti-neuroinflammatory predicition activity with molecular docking. Journal of Tropical Pharmacy and Chemistry, 4 (6). ISSN 2407-6090

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Abstract

Phytoestrogen is a group of compounds that can replace the estrogen function in the body.
One of its roles was as anti-neuroinflammatory by inhibiting the microglia M1 polarity
activation. Marsilea crenata Presl. is a plant that suspected to contain phytoestrogens. The
aim of this research was to determine the metabolite profile of 96% ethanol extract of M.
crenata using UPLC-QToF-MS/MS, and prediction the anti-neuroinflammatory activity of
compounds with molecular docking. The 100 ppm of 96% ethanol extract in DCM and
methanol were injected 5 µl each into the UPLC-QToF-MS/MS, and then analyzed by
Masslynx 4.1 software to determine the compounds. The result of metabolite profiling shows
a total 59 compounds in both DCM and methanol. Molecular docking was done with
Autodock 4.2.6. After being analyzed, there are 3 compounds that are predicted to have
activities similar to 17β-estradiol, they are prochlorperazine, 12-Aminododecanoic acid, and
1-methyl-2-[(4-methylpiperazin-1-yl)methyl]benzimidaol-5-amine hydrochloride. The
results showed that the three compounds were predicted to be phytoestrogen compounds
from M. crenata leaves, which have potential as anti-neuroinflammatory.

Item Type: Journal Article
Keywords: Phytoestrogens, M. crenata, metabolite profiling, anti-neuroinflammatory, in silico
Subjects: 11 MEDICAL AND HEALTH SCIENCES > 1115 Pharmacology and Pharmaceutical Sciences > 111504 Pharmaceutical Sciences
Divisions: Faculty of Medical and Health Sciences > Department of Pharmacy
Depositing User: Burhan Ma'arif
Date Deposited: 29 Nov 2019 04:59

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