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International Journal of Bioinformatics and Computational Biology Original Research

Exploring the Role of MAPK3 in Major Depressive Disorder: Molecular Docking, Dynamics, and Binding Free Energy Analysis of Natural Compounds as Alternatives to Conventional Drugs

  1. Abhimanyu Chauhan Department of Biotechnology, Jaypee Institute of Information Technology, Noida
  2. Chakresh Kumar Jain Department of Biotechnology, Jaypee Institute of Information Technology, Noida

Abstract

Major Depressive Disorder (MDD) is a prevalent neuropsychiatric disorder with limited treatment efficacy and significant side effects associated with conventional antidepressants. Recent studies have highlighted the role of mitogen-activated protein kinase 3 (MAPK3) in the mechanisms underlying MDD, positioning it as a potential target for the development of novel therapeutic drugs. In this study, we employed various computational approaches to explore natural compounds as viable alternatives to synthetic antidepressants. Researchers used several advanced methods—like molecular docking, ADMET analysis, molecular dynamics simulations, and binding energy calculations (MM-GBSA)—to study how these natural compounds interact with the MAPK3 protein. Out of all the compounds tested, Cannflavin A showed the strongest ability to bind with the target protein and had favorable pharmacokinetic properties, which is why it was chosen for more detailed study. To gain deeper insight into its function, researchers conducted Gene Ontology (GO) enrichment and Protein-Protein Interaction (PPI) network analyses for MAPK3. The GO analysis revealed significant enrichment in biological processes such as the ERK1 and ERK2 cascade, thyroid gland development, lung morphogenesis, and positive regulation of miRNA maturation, reinforcing its involvement in cellular signaling and neurobiological pathways. The PPI analysis identified key interactions between MAPK3 and regulatory proteins such as MAP2K1, TP53, DUSP1, and FOS, suggesting its role in signal transduction, stress response, and neuronal activity. A 200-nanosecond molecular dynamics simulation was conducted to analyze the behavior of the Cannflavin A-MAPK3 complex. Important structural measures—such as RMSF, RMSD, SASA, and radius of gyration (Rg)—confirmed that the complex was stable. Additionally, MM-GBSA analysis showed that it had strong binding free energy. When compared to standard antidepressants like Paroxetine and Amitriptyline, Cannflavin A was found to interact with key residues of the MAPK3 protein, suggesting it may have promising therapeutic potential. These findings highlight the promise of natural compounds in MDD treatment and provide a foundation for further in vivo and in vitro investigations toward the development of safer and more effective antidepressant therapies.

Keywords

References (22)

  1. Wang JQ, Mao L. The ERK Pathway: Molecular Mechanisms and Treatment of Depression. Molecular Neurobiology. 2019;56(9):6197-6205. doi:10.1007/s12035-019-1524-3
  2. World Health Organization. Depressive disorder (depression) [Internet]. [cited 2024 Mar 18]. Available from: https://www.who.int/news-room/fact-sheets/detail/depression
  3. Cui L, Li S, Wang S, Wu X, Liu Y, Yu W, et al. Major depressive disorder: hypothesis, mechanism, prevention and treatment. Signal Transduction and Targeted Therapy. 2024;9(1). doi:10.1038/s41392-024-01738-y
  4. Ormel J, Oldehinkel AJ, Nolen WA, Vollebergh W. Psychosocial Disability Before, During, and After a Major DepressiveEpisode. Archives of General Psychiatry. 2004;61(4):387. doi:10.1001/archpsyc.61.4.387
  5. Lu Z, Gao F, Teng F, Tian X, Guan H, Li J, et al. Exploring the pathogenesis of depression and potential antidepressants through the integration of reverse network pharmacology, molecular docking, and molecular dynamics. Medicine. 2023;102(44):e35793. doi:10.1097/md.0000000000035793
  6. Volmat V, Pouysségur J. Spatiotemporal regulation of the p42/p44 MAPK pathway. Biology of the Cell. 2001;93(1-2):71-79. doi:10.1016/s0248-4900(01)01129-7
  7. Suga H, Torruella G, Burger G, Brown MW, Ruiz-Trillo I. Earliest Holozoan Expansion of Phosphotyrosine Signaling. Molecular Biology and Evolution. 2013;31(3):517-528. doi:10.1093/molbev/mst241
  8. Mao LM, Wang JQ. Synaptically Localized Mitogen-Activated Protein Kinases: Local Substrates and Regulation. Molecular Neurobiology. 2015;53(9):6309-6315. doi:10.1007/s12035-015-9535-1
  9. Sweatt JD. Mitogen-activated protein kinases in synaptic plasticity and memory. Current Opinion in Neurobiology. 2004;14(3):311-317. doi:10.1016/j.conb.2004.04.001
  10. Thome J, Sakai N, Shin KH, Steffen C, Zhang YJ, Impey S, et al. cAMP Response Element-Mediated Gene Transcription Is Upregulated by Chronic Antidepressant Treatment. The Journal of Neuroscience. 2000;20(11):4030-4036. doi:10.1523/jneurosci.20-11-04030.2000
  11. Chauhan A, Jain CK. Exploring gene regulatory interaction networks and predicting therapeutic molecules among major depressive disorder and bipolar disorder: A bioinformatics approach. Journal of Affective Disorders. 2025;375:64-74. doi:10.1016/j.jad.2025.01.078
  12. Dwivedi Y, Rizavi HS, Roberts RC, Conley RC, Tamminga CA, Pandey GN. Reduced activation and expression of ERK1/2 MAP kinase in the post‐mortem brain of depressed suicide subjects. Journal of Neurochemistry. 2001;77(3):916-928. doi:10.1046/j.1471-4159.2001.00300.x
  13. Fries GR, Saldana VA, Finnstein J, Rein T. Molecular pathways of major depressive disorder converge on the synapse. Molecular Psychiatry. 2022;28(1):284-297. doi:10.1038/s41380-022-01806-1
  14. Hirschfeld RM. History and evolution of the monoamine hypothesis of depression. J Clin Psychiatry. 2000;61 Suppl 6:4–6.
  15. Abhimanyu, Jain CK. Computational Interaction Study of Immunomodulatory Plant Derivatives Against SARS-Cov-2 Mpro Target. Phytochemical Genomics. 2022:681-698. doi:10.1007/978-981-19-5779-6_29
  16. Taherkhani A, Khodadadi P, Samie L, Azadian Z, Bayat Z. Flavonoids as Strong Inhibitors of MAPK3: A Computational Drug Discovery Approach. International Journal of Analytical Chemistry. 2023;2023:1-16. doi:10.1155/2023/8899240
  17. Murthy KHHVSSN, Chandre R, Upadhyay B. Clinical evaluation of Kushmanda Ghrita in the management of depressive illness. AYU (An international quarterly journal of research in Ayurveda). 2011;32(2):230. doi:10.4103/0974-8520.92592
  18. Ye B, Tian W, Wang B, Liang J. CASTpFold: Computed Atlas of Surface Topography of the universe of protein Folds. Nucleic Acids Research. 2024;52(W1):W194-W199. doi:10.1093/nar/gkae415
  19. Pires DEV, Blundell TL, Ascher DB. pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures. Journal of Medicinal Chemistry. 2015;58(9):4066-4072. doi:10.1021/acs.jmedchem.5b00104
  20. Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports. 2017;7(1). doi:10.1038/srep42717
  21. Valdés-Tresanco MS, Valdés-Tresanco ME, Valiente PA, Moreno E. gmx_MMPBSA: A New Tool to Perform End-State Free Energy Calculations with GROMACS. Journal of Chemical Theory and Computation. 2021;17(10):6281-6291. doi:10.1021/acs.jctc.1c00645
  22. Mering CV. STRING: a database of predicted functional associations between proteins. Nucleic Acids Research. 2003;31(1):258-261. doi:10.1093/nar/gkg034