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image of Targeting JNK3: An In-silico Approach to Uncover Potential Therapeutics for Alzheimer’s Disease

Abstract

Introduction

JNK3 is a specific isoform of c-Jun N-terminal kinase, mainly found in the brain, and is highly sensitive to stress-associated signals in the central nervous system. It has been reported that JNK3 plays a crucial role in neurite formation and cognition. During pathological states such as Alzheimer’s disease, cerebral ischemia, Traumatic brain injury (TBI), Parkinson’s disease, and epilepsy, it is found to be in a hyperactivated form. Hyperphosphorylation of amyloid precursor protein (APP) and tau leads to toxic Aβ42 and neurofibrillary tangles. Excess Aβ activates JNK3 signaling, causing neuronal loss. JNK3 also contributes to mitochondrial dysfunction, Oxidative stress, neuroinflammation, and apoptosis, driving AD progression.

Methods

This study aims to identify possible therapeutics based on their physicochemical, ADMET, toxicity, and drug-likeness properties. Moreover, we utilized Molecular docking and Molecular dynamics (MD) simulation to reveal possible inhibitors against JNK3.

Results

Based on the highest binding affinity against JNK3, the best compounds, Myricetin and Kaempferol, were subjected to an MD simulation study. RMSD analysis indicated that the JNK3-Kampferol complex showed more stability; at the same time, myricetin formed more hydrogen bonds with JNK3. Moreover, both compounds exhibited favorable ADMET properties.

Discussion

This study identified Kaempferol and myricetin as potential inhibitors that target JNK3 through molecular docking and MD simulation studies. Both compounds demonstrated favorable ADMET profiles, supporting their promise as safe, orally available drug candidates.

Conclusion

Therefore, Kaempferol and myricetin emerge as promising candidates for further investigations in both and studies to treat Alzheimer’s disease and other neurodegenerative disorders.

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2025-08-15
2025-11-03
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References

  1. Cowan K.J. Storey K.B. Mitogen-activated protein kinases: New signaling pathways functioning in cellular responses to environmental stress. J. Exp. Biol. 2003 206 7 1107 1115 10.1242/jeb.00220 12604570
    [Google Scholar]
  2. Hammouda M.B. Ford A.E. Liu Y. Zhang J.Y. The JNK signaling pathway in inflammatory skin disorders and cancer. Cells 2020 9 4 857 10.3390/cells9040857
    [Google Scholar]
  3. Chuang J.Y. Huang Y.L. Yen W.L. Chiang I.P. Tsai M.H. Tang C.H. Syk/JNK/AP-1 signaling pathway mediates interleukin-6-promoted cell migration in oral squamous cell carcinoma. Int. J. Mol. Sci. 2014 15 1 545 559 10.3390/ijms15010545 24398980
    [Google Scholar]
  4. Kim J.H. Chae M. Choi A.R. Sik Kim H. Yoon S. SP600125 overcomes antimitotic drug-resistance in cancer cells by increasing apoptosis with independence of P-gp inhibition. Eur. J. Pharmacol. 2014 723 1 141 147 10.1016/j.ejphar.2013.11.026 24333214
    [Google Scholar]
  5. Sato A. Sunayama J. Okada M. Watanabe E. Seino S. Shibuya K. Suzuki K. Narita Y. Shibui S. Kayama T. Kitanaka C. Glioma-initiating cell elimination by metformin activation of FOXO3 via AMPK. Stem Cells Transl. Med. 2012 1 11 811 824 10.5966/sctm.2012‑0058 23197693
    [Google Scholar]
  6. Lee S. Rauch J. Kolch W. Targeting MAPK signaling in cancer: Mechanisms of drug resistance and sensitivity. Int J. Mol Sci 2020 21 4 1102 10.3390/ijms21041102
    [Google Scholar]
  7. Lorenzati M. Boda E. Parolisi R. Bonato M. Borsello T. Herdegen T. Buffo A. Vercelli A. c-Jun N-terminal kinase 1 (JNK1) modulates oligodendrocyte progenitor cell architecture, proliferation and myelination. Sci. Rep. 2021 11 1 7264 10.1038/s41598‑021‑86673‑6 33790350
    [Google Scholar]
  8. Duong M.T.H. Lee J.H. Ahn H.C. C-Jun N-terminal kinase inhibitors: Structural insight into kinase-inhibitor complexes.Comput Struct Biotechnol J. 2020 18 1440 1457 10.1016/j.csbj.2020.06.013.
    [Google Scholar]
  9. Musi C.A. Agrò G. Santarella F. Iervasi E. Borsello T. JNK3 as therapeutic target and biomarker in neurodegenerative and neurodevelopmental brain diseases. Cells. 2020 9 10 2190 10.3390/cells9102190
    [Google Scholar]
  10. Yarza R. Vela S. Solas M. Ramirez M.J. c-Jun N-terminal kinase (JNK) signaling as a therapeutic target for Alzheimer’s disease. Front Pharmacol 2016 6 321 10.3389/fphar.2015.00321
    [Google Scholar]
  11. Breijyeh Z. Karaman R. Comprehensive review on Alzheimer’s disease: Causes and treatment. Molecules 2020 25 24 5789 10.3390/molecules25245789
    [Google Scholar]
  12. Hampel H. Hardy J. Blennow K. Chen C. Perry G. Kim S.H. The Amyloid-β pathway in alzheimer’s Disease. Molecular Psychiatry. 2021 26 5481 5503 10.1038/s41380‑021‑01249‑0.
    [Google Scholar]
  13. Zhang Y. Chen H. Li R. Sterling K. Song W. Amyloid β-based therapy for Alzheimer’s disease: Challenges, successes and future. Signal Transduction. Targ. Therap. 2023 8 248 10.1038/s41392‑023‑01484‑7.
    [Google Scholar]
  14. Chu Q. Martinez T.F. Novak S.W. Donaldson C.J. Tan D. Vaughan J.M. Chang T. Diedrich J.K. Andrade L. Kim A. Zhang T. Manor U. Saghatelian A. Regulation of the ER stress response by a mitochondrial microprotein. Nat. Commun. 2019 10 1 4883 10.1038/s41467‑019‑12816‑z 31653868
    [Google Scholar]
  15. Cai Y. Liu J. Wang B. Sun M. Yang H. Microglia in the neuroinflammatory pathogenesis of Alzheimer’s disease and related therapeutic targets. Front Immunol 2022 13 870376 10.3389/fimmu.2022.870376
    [Google Scholar]
  16. Sharma V.K. Singh T.G. Singh S. Garg N. Dhiman S. Apoptotic pathways and Alzheimer’s disease: Probing therapeutic potential. Neurochem Res 2021 46 12 3103 3122 10.1007/s11064‑021‑03436‑3
    [Google Scholar]
  17. Corrales T. de los R. Losada-Pérez M. Casas-Tintó S. JNK pathway in CNS pathologies. Int J Mol Sci 2021 22 11 5484 10.3390/ijms22115484
    [Google Scholar]
  18. Chang K.A. Kim H.S. Ha T.Y. Ha J.W. Shin K.Y. Jeong Y.H. Lee J.P. Park C.H. Kim S. Baik T.K. Suh Y.H. Phosphorylation of amyloid precursor protein (APP) at Thr668 regulates the nuclear translocation of the APP intracellular domain and induces neurodegeneration. Mol. Cell. Biol. 2006 26 11 4327 4338 10.1128/MCB.02393‑05 16705182
    [Google Scholar]
  19. Yoon S.O. Park D.J. Ryu J.C. Ozer H.G. Tep C. Shin Y.J. Lim T.H. Pastorino L. Kunwar A.J. Walton J.C. Nagahara A.H. Lu K.P. Nelson R.J. Tuszynski M.H. Huang K. JNK3 perpetuates metabolic stress induced by Aβ peptides. Neuron 2012 75 5 824 837 10.1016/j.neuron.2012.06.024 22958823
    [Google Scholar]
  20. Solas M. Vela S. Smerdou C. Martisova E. Martínez-Valbuena I. Luquin M.R. Ramírez M.J. JNK activation in Alzheimer’s disease is driven by amyloid β and is associated with tau pathology. ACS Chem. Neurosci. 2023 14 8 acschemneuro.3c00093 10.1021/acschemneuro.3c00093 36976903
    [Google Scholar]
  21. Roman Laskowski B.A. Macarthur M.W. Thornton J.M. Computer Programs PROCHECK: A program to check the stereochemical quality of protein structures. J Appl Crystallogr 1993 26 2 283 291 10.1107/S0021889892009944
    [Google Scholar]
  22. Jendele L. Krivak R. Skoda P. Novotny M. Hoksza D. PrankWeb: A web server for ligand binding site prediction and visualization. Nucleic Acids Res. 2019 47 W1 W345 W349 10.1093/nar/gkz424 31114880
    [Google Scholar]
  23. C S. S D.K. Ragunathan V. Tiwari P. A S. P B.D. Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease. J. Biomol. Struct. Dyn. 2022 40 2 585 611 10.1080/07391102.2020.1815584 32897178
    [Google Scholar]
  24. O’Boyle N.M. Banck M. James C.A. Morley C. Vandermeersch T. Hutchison G.R. Open Babel: An open chemical toolbox. J. Cheminform. 2011 3 1 33 10.1186/1758‑2946‑3‑33 21982300
    [Google Scholar]
  25. Xiong G. Wu Z. Yi J. Fu L. Yang Z. Hsieh C. Yin M. Zeng X. Wu C. Lu A. Chen X. Hou T. Cao D. ADMETlab 2.0: An integrated online platform for accurate and comprehensive predictions of ADMET properties. Nucleic Acids Res. 2021 49 W1 W5 W14 10.1093/nar/gkab255 33893803
    [Google Scholar]
  26. Daina A. Michielin O. Zoete V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 2017 7 1 42717 10.1038/srep42717 28256516
    [Google Scholar]
  27. Nogara P.A. Saraiva R.A. Caeran Bueno D. Lissner L.J. Lenz Dalla Corte C. Braga M.M. Rosemberg D.B. Rocha J.B.T. Virtual screening of acetylcholinesterase inhibitors using the Lipinski’s rule of five and ZINC databank. BioMed Res. Int. 2015 2015 1 8 10.1155/2015/870389 25685814
    [Google Scholar]
  28. Morris G.M. Goodsell D.S. Halliday R.S. Huey R. Hart W.E. Belew R.K. Automated docking using a lamarckian genetic algorithm and an empirical binding free energy function. J. Comput. Chem. 1639 19 14 16391662
    [Google Scholar]
  29. Nazir M. Abbasi M.A. Aziz-ur-Rehman A.R. Siddiqui S.Z. Raza H. Hassan M. Ali Shah S.A. Shahid M. Seo S.Y. Novel indole based hybrid oxadiazole scaffolds with N -(substituted-phenyl)butanamides: Synthesis, lineweaver–burk plot evaluation and binding analysis of potent urease inhibitors. RSC Advances 2018 8 46 25920 25931 10.1039/C8RA04987D 35541970
    [Google Scholar]
  30. Case Ross C. 2018 http://ambermd.org/contributors.html
  31. Sankaranarayanan N.V. Villuri B.K. Nagarajan B. Lewicki S. Das S.K. Fisher P.B. Desai U.R. Design and synthesis of small molecule probes of MDA-9/Syntenin. Biomolecules 2024 14 10 1287 10.3390/biom14101287 39456220
    [Google Scholar]
  32. Wang J. Wolf R.M. Caldwell J.W. Kollman P.A. Case D.A. Development and testing of a general amber force field. J. Comput. Chem. 2004 25 9 1157 1174 10.1002/jcc.20035
    [Google Scholar]
  33. Jorgensen W.L. Chandrasekhar J. Madura J.D. Impey R.W. Klein M.L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983 79 2 926 935 10.1063/1.445869
    [Google Scholar]
  34. Heinz LP Zhao Z Tajkhorshid E GOLEM: Automated and robust Cryo-EM-guided ligand docking with explicit water molecules. J Chem Inf Model. 64 14 :5680 10.1021/acs.jcim.4c00917
    [Google Scholar]
  35. Costanzo A Fata F Freda I De Sciscio ML Gugole E Bulfaro G Binding of steroid substrates reveals the key to the productive transition of the cytochrome P450 OleP. Structure 2024 32 12 1846 1859 10.1016/j.str.2024.08.018
    [Google Scholar]
  36. Esteves F Rueff J Kranendonk M The central role of cytochrome p450 in xenobiotic metabolism—a brief review on a fascinating enzyme family. J Xenobiot 2021 11 3 94 114 10.3390/jox11030007
    [Google Scholar]
  37. Parveen R. Kashif M. Srinivasan H. Khan J. Yousif A. Ghataty D.S. Ali N. Attia S.M. Waseem M. An in silico investigation of pharmacological modulators and inflammasomes in glioblastoma multiforme. Appl. Biochem. Biotechnol. 2024 196 5 2771 2797 10.1007/s12010‑023‑04655‑y 37466884
    [Google Scholar]
  38. Abraham M.J. Murtola T. Schulz R. Páll S. Smith J.C. Hess B. Lindahl E. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 2015 1-2 19 25 10.1016/j.softx.2015.06.001
    [Google Scholar]
  39. Kuzmanic A. Zagrovic B. Determination of ensemble-average pairwise root mean-square deviation from experimental B-factors. Biophys. J. 2010 98 5 861 871 10.1016/j.bpj.2009.11.011 20197040
    [Google Scholar]
  40. Hubbard R.E. Kamran Haider M. Hydrogen Bonds in Proteins: Role and Strength. Encyclopedia of Life Sciences. Wiley 2010 10.1002/9780470015902.a0003011.pub2
    [Google Scholar]
  41. Anwar S. Mohammad T. Shamsi A. Queen A. Parveen S. Luqman S. Hasan G.M. Alamry K.A. Azum N. Asiri A.M. Hassan M.I. Discovery of hordenine as a potential inhibitor of pyruvate dehydrogenase kinase 3: Implication in lung cancer therapy. Biomedicines 2020 8 5 119 10.3390/biomedicines8050119 32422877
    [Google Scholar]
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