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Chemical Composition, Antiaging Activities and Molecular Docking Studies of Essential Oils from Acca sellowiana (Feijoa).

Heba A S El-NasharMai AdelMohamed El-ShazlyIbrahim S YahiaHamdy S El SheshtawyAdel A AlmalkiNehal Ibrahim
Published in: Chemistry & biodiversity (2022)
This study aimed to investigate the chemical composition of essential oils isolated from Acca sellowiana (feijoa) leaves and stems and elaborate on their relevance as natural anti-aging, coupled with molecular-docking studies. The isolated oils were analysed using gas chromatography-mass spectrometry analysis and investigated for inhibitory effects against acetylcholinesterase, β-secretase, collagenase, elastase and tyrosinase. Molecular-modelling study was performed using MOE-Dock program to evaluate binding interactions of major components with the above-mentioned targets. The leaf oil revealed the predominance of caryophyllene oxide (24.3 %), linalool (7.9 %), and spathulenol (6.6 %), while the stem oil was presented by caryophyllene oxide (38.1 %), α-zingiberene (10.1 %) and humulene oxide II (6.0 %). The stem oil expressed superior inhibitory activities against acetylcholinesterase (IC 50 =0.15±0.01 μg/mL), β-secretase (IC 50 =3.99±0.23 μg/mL), collagenase (IC 50 =408.10±20.80 μg/mL), elastase (IC 50 =0.17±0.01 μg/mL) and tyrosinase (IC 50 =8.45±0.40 μg/mL). The valuable binding interactions and docking scores were observed for caryophyllene oxide and α-zingiberene with acetylcholinesterase. Besides, α-zingibirene followed by linalool and τ-cadinol revealed tight fitting with collagenase and elastase. Additionally, linalool, spathulenol and τ-cadinol showed the best binding energy to tyrosinase. This study provides valuable scientific data on A. sellowiana as potential candidates for the development of natural antiaging formulations. The current study provided scientific evidence for the potential use of feijoa essential oils in antiaging formulations and as an adjuvant for the prophylaxis against Alzheimer disease.
Keyphrases
  • molecular docking
  • molecular dynamics simulations
  • early stage
  • fatty acid
  • transcription factor
  • single cell
  • machine learning
  • deep learning
  • dna binding
  • small molecule
  • single molecule
  • electronic health record