Evidence map›Paper›PMID 39638823›Full record

ArticleScientific reports2024

Identification of AChE targeted therapeutic compounds for Alzheimer's disease: an in-silico study with DFT integration.

Kalpana Rawat, Disha Tewari, Amisha Bisht, Subhash Chandra, Yewulsew Kebede Tiruneh, Hesham M Hassan, Ahmed Al-Emam, Emad Rashad Sindi, Al-Anood M Al-Dies

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Mechanisms Underlying the Cognitive Benefits ofPlants (Basel, Switzerland) · 2025
    Article
  4. Article
  5. Article
  6. Structural Bioinformatics Applied to Acetylcholinesterase Enzyme Inhibition.International journal of molecular sciences · 2025
    Review
  7. Article
  8. Article
4 · The record

Corrections and comments

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

9 authors.

Kalpana RawatComputational Biology and Biotechnology Laboratory, Department of Botany, Soban Singh Jeena University, Almora, Uttarakhand, India.
Disha TewariDepartment of Biotechnology, Kumaun University, Bhimtal, Uttarakhand, India.
Amisha BishtDepartment of Botany, Soban Singh Jeena University, Pt. Badridutt Pandey Campus Bageshwar, Almora, Uttarakhand, 263601, India.
Subhash ChandraComputational Biology and Biotechnology Laboratory, Department of Botany, Soban Singh Jeena University, Almora, Uttarakhand, India. scjnu@yahoo.co.in.
Yewulsew Kebede TirunehDepartment of Biology, Biomedical Sciences stream, Bahir Dar University, P.O.Box=79, Bahir, Ethiopia. yewult82@gmail.com.
Hesham M HassanDepartment of Pathology, College of Medicine, King Khalid University, 61421, Asir, Saudi Arabia.
Ahmed Al-EmamDepartment of Pathology, College of Medicine, King Khalid University, 61421, Asir, Saudi Arabia.
Emad Rashad SindiDivision of Clinical Biochemistry, Department of Basic Medical Sciences, College of Medicine, University of Jeddah, 23890, Jeddah, Saudi Arabia.
Al-Anood M Al-DiesChemistry Department, Umm Al-Qura University, Al-Qunfudah University College, Mecca, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by cognitive deterioration and changes in behavior. Acetylcholinesterase (AChE), which hydrolyzes acetylcholine, is a key drug target for treating AD. This research aimed to identify new AChE inhibitors using the IMPPAT database. We used known drugs as a basis to search for similar chemicals in the IMPPAT database and created a library of 127 plant-based compounds. Initial screening of these compounds was performed using molecular docking, followed by an analysis of their drug-likeness and ADMET properties. Compounds with favorable properties underwent density functional theory (DFT) calculations to assess their electronic properties such as HOMO-LUMO gap, electron density, and molecular orbital distribution. These descriptors provided insights into each compound's reactivity, stability, and binding potential with AChE. Promising candidates were further evaluated through molecular dynamics (MD) simulations over 100 ns and MMPBSA analysis for the last 30 ns. Two compounds, Biflavanone (IMPHY013027) with a binding free energy of - 130.394 kcal/mol and Calomelanol J (IMPHY007737) with - 107.908 kcal/mol, demonstrated strong binding affinities compared to the reference molecule HOR, which has a binding free energy of - 105.132 kcal/mol. These compounds exhibited promising drug-ability profiles in both molecular docking and MD simulations, indicating their potential as novel AChE inhibitors for AD treatment. However, further experimental validation is necessary to verify their effectiveness and safety.

Indexed as

AcetylcholinesteraseAlzheimer DiseaseCholinesterase InhibitorsMolecular Docking SimulationMolecular Dynamics SimulationComputer SimulationDensity Functional TheoryHumansProtein BindingAcetylcholinesteraseCholinesterase InhibitorsAlzheimer’s diseaseChemical similarity searchDFTMD simulationMolecular docking

Identifiers

PMID39638823
PMCPMC11621528

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Registered trials

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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.