# 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

**Authors:** 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, Sajjad Ahmad, Sajjad Ahmad, Sajjad Ahmad, Sajjad Ahmad

PMC · DOI: 10.1371/journal.pone.0301179 · PLOS ONE · 2024-07-25

## TL;DR

This study identifies citalopram and mirtazapine as promising antidepressants for Alzheimer's Disease by analyzing their binding to a key protein.

## Contribution

The study introduces a computational approach to evaluate antidepressants targeting MARK4 for Alzheimer's treatment.

## Key findings

- Citalopram and mirtazapine showed strong binding affinities to MARK4, suggesting therapeutic potential.
- Molecular dynamics simulations confirmed stable interactions between the top compounds and the MARK4 protein.

## 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.

## Linked entities

- **Proteins:** MARK4 (microtubule affinity regulating kinase 4)
- **Chemicals:** citalopram (PubChem CID 2771), mirtazapine (PubChem CID 4205), donepezil (PubChem CID 3152)
- **Diseases:** Alzheimer’s Disease (MONDO:0004975)

## Full-text entities

- **Genes:** MARK4 (microtubule affinity regulating kinase 4) [NCBI Gene 57787] {aka MARK4L, MARK4S, MARKL1, MARKL1L, PAR-1D}, APP (amyloid beta precursor protein) [NCBI Gene 351] {aka AAA, ABETA, ABPP, AD1, APPI, CTFgamma}
- **Diseases:** neurodegenerative illness (MESH:D019636), AD (MESH:D000544), decline in cognitive functioning (MESH:D003072), memory loss (MESH:D008569), malignancies (MESH:D009369)

## Full text

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## Figures

47 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11271900/full.md

## References

30 references — full list in the complete paper: https://tomesphere.com/paper/PMC11271900/full.md

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Source: https://tomesphere.com/paper/PMC11271900