We use cookies to improve your experience. By continuing to browse this site, you accept our cookie policy.×

Design, synthesis and evaluation of aminothiazole derivatives as potential anti-Alzheimer’s candidates

    Arti Soni

    *Author for correspondence: Tel.: +91 881 302 5251;

    E-mail Address: artisoni26@gmail.com

    Department of Pharmaceutical Sciences, Guru Jambheshwar University of Science & Technology, Hisar, 125001, Haryana, India

    ,
    Ashwani Kumar

    Department of Pharmaceutical Sciences, Guru Jambheshwar University of Science & Technology, Hisar, 125001, Haryana, India

    ,
    Vivek Kumar

    Janta College of Pharmacy, Butana, (Sonipat), 131001, Haryana, India

    ,
    Ravi Rawat

    School of Health Sciences & Technology, UPES University, Dehradun, 248007, India

    &
    Volkan Eyupoglu

    Department of Chemistry, Cankırı Karatekin University, Cankırı, 18100, Turkey

    Published Online:https://doi.org/10.4155/fmc-2023-0290

    Aim: The objective of the present study was to design, synthesize and evaluate diverse Schiff bases and thiazolidin-4-one derivatives of aminothiazole as key pharmacophores possessing acetylcholinesterase inhibitory activity. Materials & methods: Two series of compounds (13 each) were synthesized and evaluated for their acetylcholinesterase inhibition and antioxidant activity. Molecular docking of all compounds was performed to provide an insight into their binding interactions. Results: Compounds 2j (IC50 = 0.03 μM) and 3e (IC50 = 1.58 μM) were found to be the best acetylcholinesterase inhibitors among compounds of their respective series. Molecular docking analysis supported the results of in vitro activity by displaying good docking scores with the binding pocket of human acetylcholinesterase (Protein Data Bank ID: 4EY7). Conclusion: Compound 2j emerged as a potential lead compound with excellent acetylcholinesterase inhibition, antioxidant and chelation activity.

    Graphical abstract

    Papers of special note have been highlighted as: • of interest

    References

    • 1. Fang J, Li Y, Liu R et al. Discovery of multitarget-directed ligands against Alzheimer’s disease through systematic prediction of chemical–protein interactions. J. Chem. Inf. Model. 55(1), 149–164 (2015).
    • 2. Cao J, Hou J, Ping J, Cai D. Advances in developing novel therapeutic strategies for Alzheimer’s disease. Mol. Neurodegener. 13(1), 64 (2018).
    • 3. Sun BL, Li WW, Zhu C et al. Clinical research on Alzheimer’s disease: progress and perspectives. Neurosci. Bull. 34, 1111–1118 (2018).
    • 4. Guo YY, Yang LZ, Ru JX et al. An ‘OFF–ON’ fluorescent chemosensor for highly selective and sensitive detection of Al (III) in aqueous solution. Dyes Pigm. 99(3), 693–698 (2013).
    • 5. Zhang P, Xu S, Zhu Z, Xu J. Multi-target design strategies for the improved treatment of Alzheimer’s disease. Eur. J. Med. Chem. 176, 228–247 (2019).
    • 6. de Freitas Silva M, Dias KS, Gontijo VS, Ortiz CJ, Viegas C Jr. Multi-target directed drugs as a modern approach for drug design towards Alzheimer’s disease: an update. Curr. Med. Chem. 25(29), 3491–3525 (2018).
    • 7. Huang LK, Chao SP, Hu CJ. Clinical trials of new drugs for Alzheimer disease. J. Biomed. Sci. 27(1), 18 (2020).
    • 8. Marucci G, Buccioni M, Dal Ben D, Lambertucci C, Volpini R, Amenta F. Efficacy of acetylcholinesterase inhibitors in Alzheimer’s disease. Neuropharmacology 190, 108352 (2021).
    • 9. Campbell A. The potential role of aluminium in Alzheimer’s disease. Nephrol. Dial. Transplant. 17(2), 17–20 (2002).
    • 10. Bondy SC, Kirstein S. The promotion of iron-induced generation of reactive oxygen species in nerve tissue by aluminum. Mol. Chem. Neuropathol. 27, 185–194 (1996).
    • 11. Vecchio I, Sorrentino L, Paoletti A, Marra R, Arbitrio M. The state of the art on acetylcholinesterase inhibitors in the treatment of Alzheimer’s disease. J. Cent. Nerv. Syst. Dis. 13, 11795735211029113 (2021).
    • 12. Shi L, Mao WJ, Yang Y, Zhu HL. Synthesis, characterization, and biological activity of a Schiff-base Zn (II) complex. J. Coord. Chem. 62(21), 3471–3477 (2009).
    • 13. Zhao J, Zhao B, Liu J, Xu W, Wang Z. Spectroscopy study on the photochromism of Schiff bases N,N'-bis (salicylidene)-1,2-diaminoethane and N,N'-bis (salicylidene)-1,6-hexanediamine. Spectrochim. Acta A Mol. Biomol. Spectrosc. 57(1), 149–154 (2001).
    • 14. Shanty AA, Philip JE, Sneha EJ, Kurup MR, Balachandran S, Mohanan PV. Synthesis, characterization and biological studies of Schiff bases derived from heterocyclic moiety. Bioorg. Chem. 70, 67–73 (2017).
    • 15. Desai SB, Desai PB, Desai KR. Synthesis of some Schiff bases, thiazolidinones and azetidinones derived from 2,6-diaminobenzo [1,2-d:4,5-d’]bisthiazole and their anticancer activities. Heterocycl. Commun. 7(1), 83–90 (2001).
    • 16. Pandeya SN, Sriram D, Nath G, DeClercq E. Synthesis, antibacterial, antifungal and anti-HIV activities of Schiff and Mannich bases derived from isatin derivatives and N-[4-(4′-chlorophenyl)thiazol-2-yl]thiosemicarbazide. Eur. J. Pharm. Sci. 9(1), 25–31 (1999).
    • 17. Jadhao M, Das C, Rawat A et al. Development of multifunctional heterocyclic Schiff base as a potential metal chelator: a comprehensive spectroscopic approach towards drug discovery. J. Biol. Inorg. Chem. 22, 47–59 (2017).
    • 18. Abd Razik MB, Osman H, Ezzat OM et al. Efficient synthesis and discovery of Schiff bases as potent cholinesterase inhibitors. Med. Chem. 12(6), 527–536 (2016).
    • 19. Kavitha CV, Swamy SN, Mantelingu K et al. Synthesis of new bioactive venlafaxine analogs: novel thiazolidin-4-ones as antimicrobials. Bioorg. Med. Chem. 14(7), 2290–2299 (2006).
    • 20. Omar K, Geronikaki A, Zoumpoulakis P et al. Novel 4-thiazolidinone derivatives as potential antifungal and antibacterial drugs. Bioorg. Med. Chem. 18(1), 426–432 (2010).
    • 21. Isloor AM, Sunil D, Shetty P, Malladi S, Pai KS, Maliyakkl N. Synthesis, characterization, anticancer, and antioxidant activity of some new thiazolidin-4-ones in MCF-7 cells. Med. Chem. Res. 22, 758–767 (2013).
    • 22. Ottanà R, Maccari R, Ciurleo R et al. 5-Arylidene-2-phenylimino-4-thiazolidinones as PTP1B and LMW-PTP inhibitors. Bioorg. Med. Chem. 17(5), 1928–1937 (2009).
    • 23. Nofal ZM, Soliman EA, Abd El-Karim SS et al. Synthesis of some new benzimidazole-thiazole derivatives as anticancer agents. J. Heterocycl. Chem. 51(6), 1797–1806 (2014).
    • 24. Taslimi P, Osmanova S, Gulçin İ et al. Discovery of potent carbonic anhydrase, acetylcholinesterase, and butyrylcholinesterase enzymes inhibitors: the new amides and thiazolin-4-ones synthesized on an acetophenone base. J. Biochem. Mol. Toxicol. 31(9), e21931 (2017).
    • 25. Raza R, Saeed A, Arif M et al. Synthesis and biological evaluation of 3-thiazolocoumarinyl schiff-base derivatives as cholinesterase inhibitors. Chem. Biol. Drug Des. 80(4), 605–615 (2012).
    • 26. Shi J, Zhou Y, Wang K et al. Design, synthesis and biological evaluation of Schiff base derivatives as multifunctional agents for the treatment of Alzheimer’s disease. Med. Chem. Res. 30, 624–634 (2021).
    • 27. Abedi-Jazini Z, Safari J, Zarnegar Z, Sadeghi M. A simple and efficient method for the synthesis of 2-aminothiazoles under mild conditions. Polycycl. Aromat. Compd 38(3), 231–235 (2018). • Articles mentioning synthetic protocol of aminothiazole, Schiff bases and thiazolin-4-one scaffold.
    • 28. Rahim F, Javed MT, Ullah H et al. Synthesis, molecular docking, acetylcholinesterase and butyrylcholinesterase inhibitory potential of thiazole analogs as new inhibitors for Alzheimer disease. Bioorg. Chem. 62, 106–116 (2015).
    • 29. Hoan DQ. Reaction of Schiff bases with thioglycolic acid: synthesis of thiazepine-1(2H)-one and thiazolin-4-one compounds. Hue Univer. J. Sci. Nat. Sci. 127(1A), 5–14 (2018).
    • 30. Sharma D, Kumar S, Narasimhan B et al. 4-(4-Bromophenyl)-thiazol-2-amine derivatives: synthesis, biological activity and molecular docking study with ADME profile. BMC Chem. 13(1), 60 (2019).
    • 31. Dingova D, Leroy J, Check A, Garaj V, Krejci E, Hrabovska A. Optimal detection of cholinesterase activity in biological samples: modifications to the standard Ellman’s assay. Anal. Biochem. 462, 67–75 (2014).
    • 32. Magalhães LM, Segundo MA, Reis S, Lima JL. Automatic method for determination of total antioxidant capacity using 2,2-diphenyl-1-picrylhydrazyl assay. Anal. Chim. Acta 558(1–2), 310–318 (2006).
    • 33. Elmastaş M, Gülçin I, Beydemir Ş, İrfan Küfrevioğlu Ö, Aboul-Enein HY. A study on the in vitro antioxidant activity of juniper (Juniperus communis L.) fruit extracts. Anal. Lett. 39(1), 47–65 (2006).
    • 34. Gupta VK, Singh AK, Kumawat LK. Thiazole Schiff base turn-on fluorescent chemosensor for Al3+ ion. Sens. Actuat. B Chem. 195, 98–108 (2014).
    • 35. Schrödinger Release 2018-3: Glide. Schrödinger, LLC, NY, USA (2018).
    • 36. Friesner RA, Murphy RB, Repasky MP et al. Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein–ligand complexes. J. Med. Chem. 49(21), 6177–6196 (2006).
    • 37. Schrödinger Release 2018-3: LigPrep. Schrödinger, LLC, NY, USA (2018).
    • 38. Wang Y, Xing J, Xu Y et al. In silico ADME/T modelling for rational drug design. Q. Rev. Biophys. 48(4), 488–515 (2015).
    • 39. Clark DE. Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 1. Prediction of intestinal absorption. J. Pharm. Sci. 88(8), 807–814 (1999).
    • 40. Kelder J, Grootenhuis PD, Bayada DM, Delbressine LP, Ploemen JP. Polar molecular surface as a dominating determinant for oral absorption and brain penetration of drugs. Pharm. Res. 16, 1514–1519 (1999).
    • 41. Almeida H, Vieira AC, Teixeira J et al. Cell-based intestinal in vitro models for drug absorption screening. Drug Discovery and Evaluation: Safety and Pharmacokinetic Assays. Springer International Publishing, Cham, 1–22 (2022).
    • 42. Irvine JD, Takahashi L, Lockhart K et al. MDCK (Madin-Darby canine kidney) cells: a tool for membrane permeability screening. J. Pharm. Sci. 88(1), 28–33 (1999).
    • 43. Ma XL, Chen C, Yang J. Predictive model of blood–brain barrier penetration of organic compounds. Acta Pharmacol. Sin. 26(4), 500–512 (2005).
    • 44. Bekker H, Berendsen HJ, Dijkstra EJ et al. GROMACS–a parallel computer for molecular-dynamics simulations. Presented at: 4th International Conference on Computational Physics (PC 92). World Scientific Publishing, 252–256, 24–28 August (1992). • Articles discussing significance of molecular dynamic simulation.
    • 45. Ganesan A, Coote ML, Barakat K. Molecular dynamics-driven drug discovery: leaping forward with confidence. Drug Discov. Today 22(2), 249–269 (2017).
    • 46. Schmid N, Eichenberger AP, Choutko A et al. Definition and testing of the GROMOS force-field versions 54A7 and 54B7. Eur. Biophys. J. 40, 843–856 (2011).
    • 47. Van Aalten DM, Bywater R, Findlay JB, Hendlich M, Hooft RW, Vriend G. PRODRG, a program for generating molecular topologies and unique molecular descriptors from coordinates of small molecules. J. Comput. Aided Mol. Des. 10, 255–262 (1996).
    • 48. Mark P, Nilsson L. Structure and dynamics of the TIP3P, SPC, and SPC/E water models at 298 K. J. Phys Chem. A 105(43), 9954–9960 (2001).
    • 49. Van Gunsteren WF, Berendsen HJ. A leap-frog algorithm for stochastic dynamics. Mol. Simul. 1(3), 173–185 (1988).
    • 50. Berendsen HJ, van der Spoel D, van Drunen R. GROMACS: a message-passing parallel molecular dynamics implementation. Comput. Phys Commun. 91(1–3), 43–56 (1995).
    • 51. Hess B, Bekker H, Berendsen HJ, Fraaije JG. LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 18(12), 1463–1472 (1997).
    • 52. Di Pierro M, Elber R, Leimkuhler B. A stochastic algorithm for the isobaric-isothermal ensemble with Ewald summations for all long range forces. J. Chem. Theory Comput. 11(12), 5624–5637 (2015).
    • 53. Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. J. Mol. Graph. 14(1), 33–38 (1996).
    • 54. Rawat R, Kant K, Kumar A, Bhati K, Verma SM. HeroMDAnalysis: an automagical tool for GROMACS-based molecular dynamics simulation analysis. Future Med. Chem. 13(05), 447–456 (2021).
    • 55. Vaught A. Graphing with Gnuplot and Xmgr: two graphing packages available under linux. Linux J. (28es), 7es (1996).