Abstract
BackgroundAlzheimer's disease is the major cause of dementia by two main factors includes an accumulation of acetylcholinesterase enzyme at cholinergic synapse and deposition of β-amyloid protein at neurofibrillary tangles. The present investigation explores the binding affinities of phytoconstituents present in the methanolic leaf extract of Erytrhroxylum monogynum identified by gas chromatography-mass spectrometry against selected targets, i.e., β-amyloid and acetylcholinesterase. ObjectivesThe main objective of present study was to explore anti-Alzheimer's potential of phytoconstituents from methanolic leaf extract of Erytrhroxylum monogynum. MethodsErytrhroxylum monogynum leaf material was subjected to Soxhlet extraction by three different solvents, namely n-hexane, chloroform and methanol. The methanolic leaf extract was subjected to Gas chromatography–mass spectrometric analysis for identification of novel phytoconstituents and chromatogram revealed the presence of 45 novel phytoconstituents. These phytoconstituents were not reported earlier from any part of this plant material. These phytoconstituents were explored for their anti-Alzheimer’s potential by iGEMDOCK software against selected targets, namely recombinant human acetylcholinesterase (protein data bank ID: 3LII) and β-amyloid (protein data bank ID: 2LMN). ResultsFrom the results of docking analysis, the top five phytoconstituents with the highest binding affinity towards the selected targets were further subjected to ADMET prediction by in silico admetSAR web portal. ConclusionsMolecular docking analysis revealed the presence of 7 phytoconstituents are having the highest binding affinity towards the selected targets when compared to their respective standard compounds namely 9, 12-octa-decadienoic acid, methyl ester, (E, E); octadecanoic acid, methyl ester; hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl) ethyl ester; 3, 6-ditigloyloxy-7-hydroxytropane; 3, 7,11, 15-tetramethyl-2-hexa-decen-1-ol; neophytadiene and phytol. The lead hits were further subjected to LigPlot analysis to understand their intermolecular interactions. Thus the result collectively obtained from the in silico studies using computational approaches may become prospective novel lead compounds against the selected targets of Alzheimer's disease.
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