ArticleIn silico pharmacology2024
Virtual screening of acetylcholinesterase inhibitors through pharmacophore-based 3D-QSAR modeling, ADMET, molecular docking, and MD simulation studies.
Article in In silico pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Integration of network pharmacology, structure-based pharmacophore modeling, DFT, molecular docking, and molecular dynamics simulations to identify multi-target small molecule inhibitors against Alzheimer's disease.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Integrative computational and experimental identification of marine bacterial acetylcholinesterase inhibitors against alzheimer's disease.Molecular diversity · 2026Article
- Potential ofFood science & nutrition · 2026Article
- Carpoxylon macrospermum leaf extract and its phenolic compounds: a multi-targeted therapeutic remedy for Alzheimer's disease.BMC complementary medicine and therapies · 2026Article
- Molecular Modeling and Analysis of Cannabinoid and Cannabinoid-like Molecules Combining K-Means Clustering with Pearson Correlation and PCA.International journal of molecular sciences · 2025Article
- Identification of Phytoconstituents from Natural Product Database as SIRT2 Inhibitors for Potential Role in Alzheimer's Disease: An In-Silico Screening.Central nervous system agents in medicinal chemistry · 2025Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alzheimer's disease (AD) is a leading cause of dementia in elderly patients. The pathophysiology of AD includes various pathways, such as the degradation of acetylcholine, amyloid-beta deposition, neurofibrillary tangle formation, and neuroinflammation. Many studies showed that targeting acetylcholinesterase enzyme (AChE) to improve acetylcholine can be an effective option to treat AD. In the current work, we employed a 3D QSAR-based approach to generate a pharmacophore to screen a chemical library of compounds that may inhibit AChE. Data from experimental studies were collected and used for the generation of pharmacophores. More than 1 million compounds were screened, and further drug-like properties were determined via Graphical Abstract: Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00189-1.
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Registered trials
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