Evidence map›Paper›PMID 30568682›Full record

ArticleIranian journal of pharmaceutical research : IJPR2018

Multitarget Drug Design, Molecular Docking and PLIF Studies of Novel Tacrine-Coumarin Hybrids for the Treatment of Alzheimer's Disease.

Masood Fereidoonnezhad, Azar Mostoufi, Maryam Eskandari, Samaneh Zali, Fariba Aliyan

Abstract read
In one paragraph

Article in Iranian journal of pharmaceutical research : IJPR, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Computational screening of natural compounds fromVegetos (Bareilly, India) · 2022
    Article
  6. Article
  7. Review
  8. Article
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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

5 authors.

Masood FereidoonnezhadDepartment of Medicinal Chemistry, School of Pharmacy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Azar MostoufiDepartment of Medicinal Chemistry, School of Pharmacy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Maryam EskandariDepartment of Medicinal Chemistry, School of Pharmacy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Samaneh ZaliDepartment of Medicinal Chemistry, School of Pharmacy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Fariba AliyanDepartment of Medicinal Chemistry, School of Pharmacy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) as a complicated and progressive neurodegenerative disorder is the most common form of dementia and memory loss. On account of the multifactorial etiology of AD, the multi-target-directed ligand (MTDL) approach is a promising method in searching new drug candidates for this disease. Here, in this paper more than 500 tacrine-coumarin hybrids have been designed and drug-likeness, molecular docking and descriptor analysis of them were performed to find out a drug candidate with less toxicity and better binding affinity than tacrine. The docking analysis was carried out using human acetylcholineesterase (1ACJ), human butyrylcholineesterase (4BDS) and β-secretase (BACE1) (1W51) enzymes using AutoDock 4.2 and Vina. The promising results were obtained on the types of interactions. Based on docking on three targets and PLIF studies, the compounds that have better results were introduced as good candidates for synthesis. The validity of docking protocols was verified using a set of known active ligands and decoys on these targets.

Indexed as

Alzheimer’s diseaseDrug-likenessMolecular dockingMulti-target-directed ligandPLIF studies

Identifiers

PMID30568682
PMCPMC6269558

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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.