Evidence map›Paper›PMID 41973126›Full record

ArticleJournal of molecular modeling2026

Exploration of potential neuroprotective agents from medicinal plants for the treatment of Alzheimer's disease-approach through in silico ADMET, network pharmacology, docking, and dynamics studies.

Pooja Shinde, Arulmozhi Sathiyanarayanan, Sathiyanarayanan Lohidasan

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Article in Journal of molecular modeling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Pooja ShindeDepartment of Pharmaceutical Chemistry, Poona College of Pharmacy, Bharati Vidyapeeth (Deemed to Be University), Pune, Maharashtra, India.
Arulmozhi SathiyanarayananDepartment of Pharmacology, Poona College of Pharmacy, Bharati Vidyapeeth (Deemed to Be University), Pune, Maharashtra, India.
Sathiyanarayanan LohidasanDepartment of Pharmaceutical Chemistry, Poona College of Pharmacy, Bharati Vidyapeeth (Deemed to Be University), Pune, Maharashtra, India. l.satyanarayan@bharatividyapeeth.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextA degenerative brain disorder that causes memory loss is Alzheimer's disease (AD). Phytoconstituents represent a promising therapeutic strategy due to their diverse bioactivities and favourable safety profiles. This study aimed to identify potential neuroprotective phytoconstituents for AD by pharmacokinetic screening, network pharmacology, molecular docking and molecular dynamics simulation. Among 22 phytoconstituents analysed, the network revealed GSK3β, STAT3, MAOB, ESR1, and PTGS2 as key AD-associated targets. Docking results were supported by dynamic stability analysis. The combined computational results support rosmariquinone as a potential neuroprotective lead compound for AD treatment.

methodsPharmacokinetic and toxicity profiling of 22 phytoconstituents was performed using Swiss ADME and ProTox III software. Target prediction and construction of the phytoconstituent-disease target-gene interaction network were conducted using Swiss Target Prediction, Gene Card and Cytoscape. Pathway enrichment was evaluated via KEGG and GO analysis. Molecular docking of all shortlisted phytoconstituents against AD-related targets was carried out using AutoDock Vina, while 500 ns molecular dynamics simulations were performed using the Desmond module of the Schrödinger Suite to assess complex stability, RMSD, RMSF and hydrogen-bond fluctuation.

Indexed as

Alzheimer DiseaseMolecular Docking SimulationMolecular Dynamics SimulationNeuroprotective AgentsPhytochemicalsPlants, MedicinalHumansNetwork PharmacologyNeuroprotective AgentsPhytochemicalsADMETAlzheimerMolecular dockingSimulation study

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.