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2000
Volume 25, Issue 4
  • ISSN: 1871-5303
  • E-ISSN: 2212-3873

Abstract

Background

Type 2 Diabetes Mellitus (T2DM) represents a significant and pressing worldwide health concern, necessitating the quest for enhanced antidiabetic pharmaceuticals. Guanidine derivatives, notably metformin and buformin, have emerged as pivotal therapeutic agents for T2DM management.

Aims

The present study introduces an efficient one-pot synthesis method for the production of symmetrical guanidine compounds and subsequently, their evaluation as potential T2DM agents.

Methods

This synthesis involves the reaction of isothiocyanates with secondary amines, employing an environmentally friendly and recyclable reagent, tetrabutylphosphonium tribromide (TBPTB). In order to understand the mechanics of ligand-protein interaction, ADME/Toxicity, and drug-likeliness aspects, in silico studies were incorporated.

Results

An efficient and easy method for synthesis of guanidine compounds has been devised. Comprehensive assessment of the biological activity of the synthesized guanidine compounds, specifically in the context of T2DM, has been rigorously conducted.

Conclusion

Computational analyses have unveiled their substantial potential as promising antidiabetic agents. Results highlight the relevance of these compounds in the ongoing pursuit of novel therapeutic solutions for T2DM.

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References

  1. WHO. Diabetes.2023Available From: https://www.who.int/news-room/fact-sheets/detail/diabetes
  2. KosasayamaA. WatanabeY. HigashiK. IshikawaF. Cyclic guanidines. III. Synthesis of hypoglycemic 2-benzhydrylimino-1,3-diazacycloalkanes.Chem. Pharm. Bull. (Tokyo)197927483184010.1248/cpb.27.831 476860
    [Google Scholar]
  3. KosasayamaA. KonnoT. HigashiK. IshikawaF. Cyclic guanidines. IV. Synthesis of hypoglycemic N-benzhydryl bicyclic guanidines.Chem. Pharm. Bull. (Tokyo)197927484184710.1248/cpb.27.841 476861
    [Google Scholar]
  4. KosasayamaA. HigashiK. Cyclic Guanidines. VI. synthesis of hypoglycemic tricyclic guanidines.Chem. Pharm. Bull. (Tokyo)1979274880892
    [Google Scholar]
  5. ZubairS. BadshahA. PatujoJ. KhanM. RaheelA. AsgharF. ImtiazS. New ferrocene integrated amphiphilic guanidines: Synthesis, spectroscopic elucidation, DFT calculation and in vitro α-amylase and α-glucosidase inhibition combined with molecular docking approach.Heliyon202394e1491910.1016/j.heliyon.2023.e14919 37064477
    [Google Scholar]
  6. RamadoriG.P. From synthalin to metformin: Is a century cycle of biguanides as oral antidiabetic drugs now closed?Preprints202310.20944/preprints202307.1299.v1
    [Google Scholar]
  7. CaoY. LiangN. LiuT. FangJ. ZhangX. Effect of SGLT2 inhibitors and metformin on inflammatory and prognostic biomarkers in type 2 diabetes patients.Endocr. Metab. Immune Disord. Drug Targets202323453054710.2174/1871530322666220827150054 36043731
    [Google Scholar]
  8. KathuriaD. RaulA.D. WanjariP. BharatamP.V. Biguanides: Species with versatile therapeutic applications.Eur. J. Med. Chem.202121911337810.1016/j.ejmech.2021.113378 33857729
    [Google Scholar]
  9. PernicovaI. KorbonitsM. Metformin—mode of action and clinical implications for diabetes and cancer.Nat. Rev. Endocrinol.201410314315610.1038/nrendo.2013.256 24393785
    [Google Scholar]
  10. ArodaV.R. RatnerR.E. Metformin and Type 2 Diabetes prevention.Diabetes Spectr.201831433634210.2337/ds18‑0020 30510389
    [Google Scholar]
  11. HaunerH. The mode of action of thiazolidinediones.Diabetes Metab. Res. Rev.200218S2Suppl. 2S10S1510.1002/dmrr.249 11921433
    [Google Scholar]
  12. DesouzaC.V. ShivaswamyV. Pioglitazone in the treatment of type 2 diabetes: Safety and efficacy review.Clin. Med. Insights Endocrinol. Diabetes20103CMED.S537210.4137/CMED.S5372 22879786
    [Google Scholar]
  13. FuhlendorffJ. RorsmanP. KofodH. BrandC.L. RolinB. MacKayP. ShymkoR. CarrR.D. Stimulation of insulin release by repaglinide and glibenclamide involves both common and distinct processes.Diabetes199847334535110.2337/diabetes.47.3.345 9519738
    [Google Scholar]
  14. MosesR.G. GomisR. FrandsenK.B. SchliengerJ.L. DedovI. Flexible meal-related dosing with repaglinide facilitates glycemic control in therapy-naive type 2 diabetes.Diabetes Care2001241111510.2337/diacare.24.1.11 11194214
    [Google Scholar]
  15. PulsW. Pharmacology of glucosidase inhibitors.Oral Antidiab1996199649753410.1007/978‑3‑662‑09127‑2_17
    [Google Scholar]
  16. HanefeldM. Cardiovascular benefits and safety profile of acarbose therapy in prediabetes and established type 2 diabetes.Cardiovasc. Diabetol.200761203010.1186/1475‑2840‑6‑20 17697384
    [Google Scholar]
  17. WrightE.M. TurkE. The sodium/glucose cotransport family SLC5.Pflugers Arch.2004447581381510.1007/s00424‑003‑1202‑0 12748858
    [Google Scholar]
  18. KaragiannisT. BekiariE. TsapasA. Canagliflozin in the treatment of type 2 diabetes: An evidence-based review of its place in therapy.Core Evid.20171211010.2147/CE.S109654 28352212
    [Google Scholar]
  19. JamirL. KhatunN. PatelB.K. The oxidative cleavage of an anti-Hugerschoff product: A mild environmentally benign one pot synthesis of ureas from isothiocyanates.RSC Adv.20111344745110.1039/c1ra00278c
    [Google Scholar]
  20. KuotsuV. NakroV. YangerI. LothaT.N. TzudirK. SinhaU.B. JamirL. An environmentally benign synthesis of Tetrabutylphosphonium tribromide (TBPTB) – a versatile and efficient phase transfer reagent for organic transformations.Green Chem. Lett. Rev.202114242543410.1080/17518253.2021.1929511
    [Google Scholar]
  21. YellaR. MurruS. AliA.R. PatelB.K. Arylthioureas with bromine or its equivalents gives no ‘Hugerschoff’ reaction product.Org. Biomol. Chem.20108153389339310.1039/c003892j 20552143
    [Google Scholar]
  22. HuynhT.N.T. NguyenK.T. SukwattanasinittM. WacharasindhuS. Electrochemical NaI-mediated one-pot synthesis of guanidines from isothiocyanates via tandem addition-guanylation.Org. Biomol. Chem.202321438667867410.1039/D3OB01113E 37672208
    [Google Scholar]
  23. JiangW. WangB. SongC. LiuJ. Electrocatalytic desulfurizative amination of thioureas to guanidines.J. Org. Chem.20238820146011460910.1021/acs.joc.3c01612 37788335
    [Google Scholar]
  24. WacharasindhuS. AnnuurR.M. SaetanT. SukwattanasinittM. Metal-free synthesis of guanidines from thioureas in water reactions mediated by visible light.Synthesis202355142166217610.1055/a‑2050‑3720
    [Google Scholar]
  25. LongkumerN. RichaK. KarmakerR. KuotsuV. SupongA. JamirL. BharaliP. BoraS.U. Green synthesis of bromo organic molecules and investigations on their antibacterial properties: An experimental and computational approach.Acta Chim. Slov.201966227628310.17344/acsi.2018.4580 33855504
    [Google Scholar]
  26. Al-MansoubM.A. AlzahraniA.M. Al-JenoobiF.I. RaishM. In vitro and in vivo studies of antidiabetic activity of metformin and metformin-loaded PLGA microspheres.J. Drug Deliv. Technol202161102229
    [Google Scholar]
  27. Russell-JonesD. ChertokL. BlondeL. Oral semaglutide: A review of the efficacy and safety profile of the first oral glucagon-like peptide-1 receptor agonist in patients with type 2 diabetes.Diabetes Obes. Metab.2020227972981
    [Google Scholar]
  28. DeaconC.F. Physiology and Pharmacology of DPP-4 in glucose homeostasis and the treatment of type 2 diabetes.Front. Endocrinol. (Lausanne)2019108010.3389/fendo.2019.00080 30828317
    [Google Scholar]
  29. GopenG.D. SwanJ.A. The science of scientific writing.Am. Sci.1990786550558
    [Google Scholar]
  30. PathakD. ChadhaN. SilakariO. Identification of non-resistant ROS-1 inhibitors using structure based pharmacophore analysis.J. Mol. Graph. Model.201670859310.1016/j.jmgm.2016.09.013 27693947
    [Google Scholar]
  31. PeitzikaS.C. PontikiE. A review on recent approaches on molecular docking studies of novel compounds targeting acetylcholinesterase in alzheimer disease.Molecules2023283108410.3390/molecules28031084 36770750
    [Google Scholar]
  32. LothaT.N. RichaK. Environmentally benign synthesis of unsymmetrical ureas and their evaluation as potential HIV-1 protease inhibitors via a computational approach.Mol. Divers.202428274976310.1007/s11030‑023‑10615‑9
    [Google Scholar]
  33. SanderT. FreyssJ. KorffM.V. RufenerC. DataWarrior: Kimya İçin Veri Görselleştirme ve Analizini Destekleyen Açık Kaynaklı Bir Program.J. Chem. Inf. Model.20155546047310.1021/ci500588j 25558886
    [Google Scholar]
  34. ChengF. LiW. ZhouY. ShenJ. WuZ. LiuG. LeeP.W. TangY. admetSAR: A comprehensive source and free tool for assessment of chemical ADMET properties.J. Chem. Inf. Model.201252113099310510.1021/ci300367a 23092397
    [Google Scholar]
  35. El-SaadiM.W. Williams-HartT. SalvatoreB.A. MahdavianE. Use of in-silico assays to characterize the ADMET profile and identify potential therapeutic targets of fusarochromanone, a novel anti-cancer agent.In Silico Pharmacol.201531610.1186/s40203‑015‑0010‑5 26820891
    [Google Scholar]
  36. ButinaD. SegallM.D. FrankcombeK. Predicting ADME properties in silico: Methods and models.Drug Discov. Today2002711S83S8810.1016/S1359‑6446(02)02288‑2 12047885
    [Google Scholar]
  37. TianS. WangJ. LiY. LiD. XuL. HouT. The application of in silico drug-likeness predictions in pharmaceutical research.Adv. Drug Deliv. Rev.20158621010.1016/j.addr.2015.01.009 25666163
    [Google Scholar]
  38. ShenJ. ChengF. XuY. LiW. TangY. Estimation of ADME properties with substructure pattern recognition.J. Chem. Inf. Model.20105061034104110.1021/ci100104j 20578727
    [Google Scholar]
  39. SanderT. FreyssJ. von KorffM. RufenerC. DataWarrior: An open-source program for chemistry aware data visualization and analysis.J. Chem. Inf. Model.201555246047310.1021/ci500588j 25558886
    [Google Scholar]
  40. GuanL. YangH. CaiY. SunL. DiP. LiW. LiuG. TangY. ADMET-score – a comprehensive scoring function for evaluation of chemical drug-likeness.MedChemComm201910114815710.1039/C8MD00472B 30774861
    [Google Scholar]
  41. XuX. ZhangW. HuangC. LiY. YuH. WangY. DuanJ. LingY. A novel chemometric method for the prediction of human oral bioavailability.Int. J. Mol. Sci.20121366964698210.3390/ijms13066964 22837674
    [Google Scholar]
  42. LipinskiC.A. LombardoF. DominyB.W. FeeneyP.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings.Adv. Drug Deliv. Rev.2001461-332610.1016/S0169‑409X(00)00129‑0 11259830
    [Google Scholar]
  43. RoyS. KumarA. BaigM.H. MasaříkM. ProvazníkI. Virtual screening, ADMET profiling, molecular docking and dynamics approaches to search for potent selective natural molecules based inhibitors against metallothionein-III to study Alzheimer’s disease.Methods20158310511010.1016/j.ymeth.2015.04.021 25920949
    [Google Scholar]
  44. LajinessM.S. ViethM. EricksonJ. Molecular properties that influence oral drug-like behavior.Curr. Opin. Drug Discov. Devel.200474470477 15338956
    [Google Scholar]
  45. OukilO. TchouarN. BelaidiS. SalahT. CinarM. Structural investigation, drug likeness scoring and structure activity/property relationships applied on 1,2,3-thiadiazole derivatives, with kinase inhibitors activity.Rev. Roum. Chim.2017628192
    [Google Scholar]
  46. AlimirzaeiF. KieslichC.A. Machine learning models for predicting membranolytic anticancer peptides.Computer-Aided Chem. Eng.2023522691269610.1016/B978‑0‑443‑15274‑0.50428‑5
    [Google Scholar]
  47. TabakhiS. SuvonM.N.I. AhadianP. LuH. Multimodal learning for multi-omics: A survey.World Sci. Ann. Rev. Arti. Intell.20231225000410.1142/S2811032322500047
    [Google Scholar]
  48. MaghsoudiS. Taghavi ShahrakiB. RamehF. NazarabiM. FatahiY. AkhavanO. RabieeM. MostafaviE. LimaE.C. SaebM.R. RabieeN. A review on computer‐aided chemogenomics and drug repositioning for rational COVID ‐19 drug discovery.Chem. Biol. Drug Des.2022100569972110.1111/cbdd.14136 36002440
    [Google Scholar]
  49. RadM. EbrahimipourG. BandehpourM. AkhavanO. YarianF. SOEing PCR/Docking optimization of protein A-G/scFv-Fc-Bioconjugated Au Nanoparticles for interaction with Meningitidis bacterial antigen.Catalysts202313579080010.3390/catal13050790
    [Google Scholar]
  50. SethiA. JoshiK. SasikalaK. AlvalaM. Molecular docking in modern drug discovery: Principles and recent applications.Drug Discovery and Development - New AdvancesInTechOpen: London2018
    [Google Scholar]
  51. FangQ. YuL. LiP. A new insulin-glucose metabolic model of type 1 diabetes mellitus: An in silico study.Comput. Methods Programs Biomed.20151201162610.1016/j.cmpb.2015.03.009 25896293
    [Google Scholar]
  52. AlamF. Asiful IslamM. Ibrahim KhalilM. Hua GanS. Metabolic control of type 2 diabetes by targeting the GLUT4 glucose transporter: Intervention approaches.Curr. Pharm. Des.201622203034304910.2174/1381612822666160307145801 26951104
    [Google Scholar]
  53. OikonomakosN. Glycogen phosphorylase as a molecular target for type 2 diabetes therapy.Curr. Protein Pept. Sci.20023656158610.2174/1389203023380422 12470212
    [Google Scholar]
  54. MuralidaranS. RoyA. The role of PPAR agonists in diabetes mellitus.J. Pharm. Sci. Res.201688864866
    [Google Scholar]
  55. AkdadM. AmezianeR. KhalloukiF. BakriY. Antidiabetic phytocompounds acting as glucose transport stimulators.Endocr. Metab. Immune Disord. Drug Targets202323214716810.2174/1871530322666220510093720
    [Google Scholar]
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