Evidence map›Paper›PMID 34581863›Full record

ArticleJournal of molecular modeling2021

Identification of novel acetylcholinesterase inhibitors through 3D-QSAR, molecular docking, and molecular dynamics simulation targeting Alzheimer's disease.

Khalil El Khatabi, Reda El-Mernissi, Ilham Aanouz, Mohammed Aziz Ajana, Tahar Lakhlifi, Abbas Khan, Dong-Qing Wei, Mohammed Bouachrine

Abstract read
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In one paragraph

Article in Journal of molecular modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Novel Mono-Substituted 4International journal of molecular sciences · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Structural Bioinformatics Applied to Acetylcholinesterase Enzyme Inhibition.International journal of molecular sciences · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
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

8 authors.

Khalil El KhatabiMolecular Chemistry and Natural Substances Laboratory, Faculty of Science, University of Moulay Ismail, Meknes, Morocco. khalil.elkhatabi@edu.umi.ac.ma.ORCID http://orcid.org/0000-0001-8669-9657
Reda El-MernissiMolecular Chemistry and Natural Substances Laboratory, Faculty of Science, University of Moulay Ismail, Meknes, Morocco.
Ilham AanouzMolecular Chemistry and Natural Substances Laboratory, Faculty of Science, University of Moulay Ismail, Meknes, Morocco.
Mohammed Aziz AjanaMolecular Chemistry and Natural Substances Laboratory, Faculty of Science, University of Moulay Ismail, Meknes, Morocco.
Tahar LakhlifiMolecular Chemistry and Natural Substances Laboratory, Faculty of Science, University of Moulay Ismail, Meknes, Morocco.
Abbas KhanDepartment of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
Dong-Qing WeiDepartment of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
Mohammed BouachrineMolecular Chemistry and Natural Substances Laboratory, Faculty of Science, University of Moulay Ismail, Meknes, Morocco.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acetylcholinesterase (AChE) is a potential target for the development of small molecules as inhibitors for the therapy of Alzheimer's disease (AD). To design highly active acetylcholinesterase inhibitors, a three-dimensional quantitative structure-activity relationship (3D-QSAR) approach was performed on a series of N-benzylpyrrolidine derivatives previously evaluated for acetylcholinesterase inhibitory activity. The developed two models, CoMFA and CoMSIA, were statistically validated, and good predictability was achieved for both models. The information generated from 3D-QSAR contour maps may provide a better understanding of the structural features required for acetylcholinesterase inhibition and help to design new potential anti-acetylcholinesterase molecules. Consequently, six novel acetylcholinesterase inhibitors were designed, among which compound A1 with the highest predicted activity was subjected to detailed molecular docking and compared to the most active compound. Extra-precision molecular dynamics (MD) simulation of 50 ns and binding free energy calculations using MM-GBSA were performed for the selected compounds to validate the stability. These results may afford important structural insights needed to identify novel acetylcholinesterase inhibitors and other promising strategies in drug discovery.

Indexed as

Quantitative Structure-Activity RelationshipAlzheimer DiseaseCholinesterase InhibitorsHumansHydrogen BondingHydrophobic and Hydrophilic InteractionsLigandsMolecular Docking SimulationMolecular Dynamics SimulationPyrrolidinesRandom AllocationCholinesterase InhibitorsLigandspyrrolidinePyrrolidines3D-QSARAcetylcholinesteraseMD simulationsMM-GBSAMolecular dockingN-benzylpyrrolidine

Identifiers

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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.