Virtual screening and molecular dynamics of anti-Alzheimer compounds from Cardiospermum halicacabum via GC-MS DOI Creative Commons

Selvan Kaviyarasu,

Nallamuthu Padmanaban,

Sulekha Khute

et al.

Frontiers in Chemistry, Journal Year: 2025, Volume and Issue: 13

Published: April 4, 2025

Background Ayurveda is an ancient Indian medicinal system that uses plants for their neuroprotective effects. claims the ( C. halicacabum ) leaves possess significant properties. Alzheimer’s characterized by accumulation of amyloid-β, acetylcholinesterase, and tau tangles interfere with neural transmission impair cognitive abilities. Objectives This study aimed to identify novel potential anti-Alzheimer phytoconstituents using in silico methods. Methods utilized Box–Behnken design within response surface methodology (RSM) optimize combine effects process variables, namely powder weight, solvent volume, extraction time, on microwave-assisted (MAE) leaves. The optimization revealed these along microwave usage, significantly influenced yield. ethanolic extract was examined gas chromatography-mass spectrometry (GC–MS) analysis, identified were further analyzed through computer-based simulations, including docking, absorption, distribution, metabolism, excretion, toxicity (ADMET) studies, assessment drug-likeness, molecular dynamics, LigPlot density functional theory (DFT) analysis. Results Gas (GC-MS) analysis 40 37 successfully characterized. Molecular docking dynamics simulations 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)], 1-(2-hydroxyethoxy)-2-methyldodecane, which exhibited superior stability docked complex compared galantamine. Conclusion Based computational predictions observed pharmacological properties, findings suggest may have therapeutic against selected AD targets.

Language: Английский

Alzheimer’s Disease: Exploring Pathophysiological Hypotheses and the Role of Machine Learning in Drug Discovery DOI Open Access
Jose Dominguez-Gortaire,

Alejandra Ruiz,

Ana B. Porto-Pazos

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(3), P. 1004 - 1004

Published: Jan. 24, 2025

Alzheimer’s disease (AD) is a major neurodegenerative dementia, with its complex pathophysiology challenging current treatments. Recent advancements have shifted the focus from traditionally dominant amyloid hypothesis toward multifactorial understanding of disease. Emerging evidence suggests that while amyloid-beta (Aβ) accumulation central to AD, it may not be primary driver but rather part broader pathogenic process. Novel hypotheses been proposed, including role tau protein abnormalities, mitochondrial dysfunction, and chronic neuroinflammation. Additionally, gut–brain axis epigenetic modifications gained attention as potential contributors AD progression. The limitations existing therapies underscore need for innovative strategies. This study explores integration machine learning (ML) in drug discovery accelerate identification novel targets candidates. ML offers ability navigate AD’s complexity, enabling rapid analysis extensive datasets optimizing clinical trial design. synergy between these themes presents promising future more effective

Language: Английский

Citations

0
Hydrazide-Hydrazone Derivatives and Their Antitubercular Activity DOI
Bapu R. Thorat, Suraj N. Mali, Umang Shah

et al.

Russian Journal of Bioorganic Chemistry, Journal Year: 2025, Volume and Issue: 51(1), P. 35 - 52

Published: Feb. 1, 2025

Language: Английский

Citations

0
Virtual screening and molecular dynamics of anti-Alzheimer compounds from Cardiospermum halicacabum via GC-MS DOI Creative Commons

Selvan Kaviyarasu,

Nallamuthu Padmanaban,

Sulekha Khute

et al.

Frontiers in Chemistry, Journal Year: 2025, Volume and Issue: 13

Published: April 4, 2025

Background Ayurveda is an ancient Indian medicinal system that uses plants for their neuroprotective effects. claims the ( C. halicacabum ) leaves possess significant properties. Alzheimer’s characterized by accumulation of amyloid-β, acetylcholinesterase, and tau tangles interfere with neural transmission impair cognitive abilities. Objectives This study aimed to identify novel potential anti-Alzheimer phytoconstituents using in silico methods. Methods utilized Box–Behnken design within response surface methodology (RSM) optimize combine effects process variables, namely powder weight, solvent volume, extraction time, on microwave-assisted (MAE) leaves. The optimization revealed these along microwave usage, significantly influenced yield. ethanolic extract was examined gas chromatography-mass spectrometry (GC–MS) analysis, identified were further analyzed through computer-based simulations, including docking, absorption, distribution, metabolism, excretion, toxicity (ADMET) studies, assessment drug-likeness, molecular dynamics, LigPlot density functional theory (DFT) analysis. Results Gas (GC-MS) analysis 40 37 successfully characterized. Molecular docking dynamics simulations 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)], 1-(2-hydroxyethoxy)-2-methyldodecane, which exhibited superior stability docked complex compared galantamine. Conclusion Based computational predictions observed pharmacological properties, findings suggest may have therapeutic against selected AD targets.

Language: Английский

Citations

0