Evidence map›Paper›PMID 39052643›Full record

ArticlePloS one2024

Exploring the most promising anti - Depressant drug targeting Microtubule Affinity Receptor Kinase 4 involved in Alzheimer's Disease through molecular docking and molecular dynamics simulation.

S Rehan Ahmad, Md Zeyaullah, Abdullah M AlShahrani, Mohammad Suhail Khan, Khursheed Muzammil, Faheem Ahmed, Adam Dawria, Ali Mohieldin, Haroon Ali, Abdelrhman A G Altijani

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

S Rehan AhmadHiralal Mazumdar Memorial College for Women, West Bengal State University, Kolkata, West Bengal, India.ORCID 0000-0003-0796-5238
Md ZeyaullahDepartment of Basic Medical Science, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.
Abdullah M AlShahraniDepartment of Basic Medical Science, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.
Mohammad Suhail KhanDepartment of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.
Khursheed MuzammilDepartment of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.ORCID 0000-0003-1676-8092
Faheem AhmedDepartment of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.
Adam DawriaDepartment of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.
Ali MohieldinDepartment of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.
Haroon AliDepartment of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.
Abdelrhman A G AltijaniDepartment of Public Health, College of Applied Medical Sciences, Khamis Mushait Campus, King Khalid University (KKU), Abha, Saudi Arabia.ORCID 0000-0002-9560-2607

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's Disease (AD) is the prevailing type of neurodegenerative illness, characterised by the accumulation of amyloid beta plaques. The symptoms associated with AD are memory loss, emotional variability, and a decline in cognitive functioning. To date, the pharmaceuticals currently accessible in the marketplace are limited to symptom management. According to several research, antidepressants have demonstrated potential efficacy in the management of AD. In this particular investigation, a total of 24 anti-depressant medications were selected as ligands, while the Microtubule Affinity Receptor Kinase 4 (MARK4) protein was chosen as the focal point of our study. The selection of MARK4 was based on its known involvement in the advancement of AD and other types of malignancies, rendering it a highly prospective target for therapeutic interventions. The initial step involved doing ADMET analysis, which was subsequently followed by molecular docking of 24 drugs. This was succeeded by molecular dynamics simulation and molecular mechanics generalised Born surface area (MMGBSA) calculations. Upon conducting molecular docking experiments, it has been determined that the binding affinities observed fall within the range of -5.5 kcal/mol to -9.0 kcal/mol. In this study, we selected six anti-depressant compounds (CID ID - 4184, 2771, 4205, 5533, 4543, and 2160) based on their binding affinities, which were determined to be -9.0, -8.7, -8.4, -8.3, -8.2, and -8.2, respectively. Molecular dynamics simulations were conducted for all six drugs, with donepezil serving as the control drug. Various analyses were performed, including basic analysis and post-trajectory analysis such as free energy landscape (FEL), polarizable continuum model (PCM), and MMGBSA calculations. Based on the findings from molecular dynamics simulations and the MMGBSA analysis, it can be inferred that citalopram and mirtazapine exhibit considerable potential as anti-depressant agents. Consequently, these compounds warrant further investigation through in vitro and in vivo investigations in the context of treating AD.

Indexed as

Alzheimer DiseaseAntidepressive AgentsMolecular Docking SimulationMolecular Dynamics SimulationProtein Serine-Threonine KinasesHumansLigandsProtein BindingAntidepressive AgentsLigandsMARK4 protein, humanProtein Serine-Threonine Kinases

Identifiers

PMID39052643
PMCPMC11271900

What Socratic holds

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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 Socratic graph.