Evidence map›Paper›PMID 41212470›Full record

ArticleCell biochemistry and biophysics2026

Therapeutic Potential of Phytocompounds Gentisic Acid and Alpha Resorcylic Acid against Alzheimer's Disease: A Network Pharmacology, In Silico, and In Vitro Approach.

Urvashi Soni, Rohini Pujari

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Article in Cell biochemistry and biophysics, 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

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Urvashi SoniSchool of Health Sciences and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, 411038, Maharashtra, India.ORCID http://orcid.org/0000-0001-8828-173X
Rohini PujariSchool of Health Sciences and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, 411038, Maharashtra, India. rohinirpujari@gmail.com.ORCID http://orcid.org/0000-0003-4169-6094

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by memory loss, cognitive decline, and impaired cholinergic signaling. Natural polyphenolic compounds have gained attention for their antioxidant, anti-inflammatory, and multi-target neuroprotective effects. In this study, we explored the potential of gentisic acid and alpha-resorcylic acid as therapeutic candidates against AD using a combination of computational and experimental approaches. We first identified potential protein targets for these compounds using SwissTargetPrediction and STITCH databases and compiled 67 AD-related genes from GeneCards. Network analysis highlighted acetylcholinesterase (AChE) as a key target, supported by its established role in AD pathology. Molecular docking showed that gentisic acid and alpha-resorcylic acid bind effectively to AChE, with docking scores of − 6.6 and − 6.9 kcal/mol, respectively, compared to standard drugs donepezil (− 9.2 kcal/mol) and galantamine (− 7.7 kcal/mol). Molecular dynamics simulations over 100 ns confirmed the stability of these ligand–protein complexes, with RMSD values remaining below 3 Å and consistent hydrogen-bond interactions throughout the simulation. Experimental validation revealed that both compounds inhibit AChE in a concentration-dependent manner, with IC₅₀ values of 3.59 µg/mL for gentisic acid and 89.99 µg/mL for alpha-resorcylic acid. Functional enrichment analyses further indicated that these compounds may influence multiple pathways relevant to AD, including Tau phosphorylation, neuropeptide receptor activity, glycerolipid metabolism, and anti-inflammatory signaling. Together, these findings suggest that gentisic acid and alpha-resorcylic acid can act as multi-target agents with promising neuroprotective effects. Their moderate binding to AChE, coupled with favorable pharmacological properties, positions them as potential leads for the development of novel therapies for AD. These results provide a strong foundation for future preclinical and clinical investigations into their therapeutic applications.

Indexed as

Alzheimer DiseaseCholinesterase InhibitorsGentisatesHydroxybenzoatesAcetylcholinesteraseHumansMolecular Docking SimulationMolecular Dynamics SimulationNetwork PharmacologyNeuroprotective AgentsProtein Binding2,5-dihydroxybenzoic acidAcetylcholinesteraseCholinesterase InhibitorsGentisatesHydroxybenzoatesNeuroprotective AgentsAlpha resorcylic acidAlzheimer’s diseaseGentisic acidMolecular dockingMolecular dynamics simulationNetwork pharmacology

Identifiers

PMID41212470

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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.