{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T11:38:02Z","timestamp":1771328282219,"version":"3.50.1"},"reference-count":64,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T00:00:00Z","timestamp":1743724800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Chem."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Ayurveda is an ancient Indian medicinal system that uses medicinal plants for their neuroprotective effects. Ayurveda claims that the (<jats:italic>C. halicacabum<\/jats:italic>) leaves possess significant neuroprotective properties. Alzheimer\u2019s is characterized by the accumulation of amyloid-\u03b2, acetylcholinesterase, and tau tangles that interfere with neural transmission and impair cognitive abilities.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objectives<\/jats:title><jats:p>This study aimed to identify novel potential anti-Alzheimer phytoconstituents of <jats:italic>C. halicacabum<\/jats:italic> leaves using <jats:italic>in silico<\/jats:italic> methods.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This study utilized the Box\u2013Behnken design within the response surface methodology (RSM) to optimize and combine the effects of process variables, namely powder weight, solvent volume, and extraction time, on the microwave-assisted extraction (MAE) <jats:italic>of C. halicacabum<\/jats:italic> leaves. The optimization process revealed that these variables, along with microwave usage, significantly influenced the extraction yield. The ethanolic extract was examined using gas chromatography-mass spectrometry (GC\u2013MS) analysis, and the identified phytoconstituents were further analyzed through computer-based simulations, including docking, absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies, assessment of drug-likeness, molecular dynamics, LigPlot analysis, and density functional theory (DFT) analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Gas chromatography-mass spectrometry (GC-MS) analysis identified 40 phytoconstituents and 37 were successfully characterized. Molecular docking and dynamics simulations revealed two lead compounds, acetic acid (dodecahydro-7-hydroxy-1,4b,8,8-tetramethyl-10-oxo-2(1H)-phenanthrenylidene)-,2-(dimethylamino)ethyl ester, [1R-(1. alpha)], and 1-(2-hydroxyethoxy)-2-methyldodecane, which exhibited superior stability in the docked complex compared to galantamine.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Based on computational predictions and observed pharmacological properties, these findings suggest that phytoconstituents may have therapeutic effects against selected AD targets.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fchem.2025.1586728","type":"journal-article","created":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T18:34:39Z","timestamp":1743791679000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Virtual screening and molecular dynamics of anti-Alzheimer compounds from Cardiospermum halicacabum via GC-MS"],"prefix":"10.3389","volume":"13","author":[{"given":"Selvan","family":"Kaviyarasu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nallamuthu","family":"Padmanaban","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sulekha","family":"Khute","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gokhan","family":"Zengin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paranthaman","family":"Subash","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,4,4]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"12040","DOI":"10.1080\/07391102.2023.2266524","article-title":"VinaLigGen: a method to generate LigPlots and retrieval of hydrogen and hydrophobic interactions from protein-ligand complexes","volume":"42","author":"Agrawal","year":"2024","journal-title":"J. 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