MAÜ GCRIS Standart veritabanının içerik oluşturulması ve kurulumu Research Ecosystems (https://www.researchecosystems.com) tarafından devam etmektedir. Bu süreçte gördüğünüz verilerde eksikler olabilir.
 

Evaluation of Extra Virgin Olive Oil Compounds Using Computational Methods: in Vitro, Admet, Dft, Molecular Docking and Human Gene Network Analysis Study

No Thumbnail Available

Date

2025

Journal Title

Journal ISSN

Volume Title

Publisher

Bmc

Open Access Color

OpenAIRE Downloads

OpenAIRE Views

Research Projects

Organizational Units

Journal Issue

Events

Abstract

This study investigates the phenolic compounds (PC), volatile compounds (VC), and fatty acids (FA) of extra virgin olive oil (EVOO) derived from the Turkish olive variety "Sar & imath; Ulak", along with ADMET, DFT, molecular docking, and gene network analyses of significant molecules identified within the EVOO. Chromatographic methods (GC-FID, HPLC) were employed to characterize FA, PC, and VC profiles, while quality parameters, antioxidant activities (TAC, ABTS, DPPH) were assessed via spectrophotometry. The analysis revealed a complex composition of 40 volatile compounds, with estragole, 7-hydroxyheptene-1, and 3-methoxycinnamaldehyde as the primary components. Hydroxytyrosol, tyrosol, oleuropein, apigenin, ferulic acid, and vanillic acid emerged as main phenolic constituents, with hydroxytyrosol and apigenin exhibiting high bioavailability. Molecular docking highlighted oleuropein and pinoresinol as compounds with strong binding affinities, though only hydroxytyrosol, apigenin, and pinoresinol fully met Lipinski and other drug-likeness criteria. DFT analysis showed that oleuropein and pinoresinol have notable dipole moments, reflecting polar and asymmetrical structures. KEGG enrichment analysis further linked key molecules like oleuropein and apigenin with pathways related to lipid metabolism and atherosclerosis, underscoring their potential bioactivity and relevance in health-related applications.

Description

ONER, Erkan/0000-0002-6332-6484; UNSAL, VELID/0000-0003-1415-0563

Keywords

Evoo, Sar & Imath, Ulak, Admet, Dft, Molecular Docking, Gene Network Analysis

Turkish CoHE Thesis Center URL

Fields of Science

Citation

WoS Q

Q2

Scopus Q

Q2

Source

Volume

19

Issue

1

Start Page

End Page