Biological evaluation of 9-(1H-Indol-3-yl) xanthen-4-(9H)-ones derivatives as noncompetitive α-glucosidase inhibitors: kinetics and molecular mechanisms

  • Maryam Nourisefat
  • Najmeh Salehi
  • Saeed Yousefinejad
  • Farhad Panahi
  • Kowsar Bagherzadeh
  • Massoud Amanlou
  • Ali Khalafi-Nezhad
  • Mohammad Hossein Karimi-JafariEmail author
  • Nader Sheibani
  • Ali Akbar Moosavi-MovahediEmail author
Original Research


The α-Glucosidase plays a key role in attenuation of postprandial hyperglycemia in diabetic patients. In this study, a class of 9-(1H-Indol-3-yl) xanthen-4-(9H)-ones derivatives (M1-M20) were evaluated for their α-Glucosidase inhibitory activity. The inhibitory activities of these compounds were evaluated via inhibition kinetics, molecular dynamic (MD) simulations, ensemble docking, and linear quantitative structure–activity relationship (QSAR) models. The results from the serial kinetic studies demonstrated that most of the ligands could directly inactivate enzyme activity in a dose-dependent manner. A typical non-competitive type of inhibition was observed, with compound M15 showing the highest inhibitory activity among the ligands tested. Also, MD simulations and ensemble docking studies on α-glucosidase homology model confirmed the non-competitive inhibition mechanism. The best binding mode for these inhibitors and efficacy of hydrogen bonds and hydrophobic interactions on inhibitory activities of synthetic ligands were also disclosed. The QSAR studies showed that the electronegative and oxygen-containing functional groups of indolyl-xanthone structures play a significant role in low-to-moderate inhibitory properties of these potentially anti-diabetic drugs against α-Glucosidase enzyme. Thus, our studies provide important molecular mechanisms delineating α-Glucosidase inhibition, which could aid in development of new drugs for type 2 diabetes mellitus treatment.


α-Glucosidase Inhibition kinetics Non-competitive inhibition Molecular dynamics simulation Ensemble docking OSAR 



This research was supported by the University of Tehran, Iran National Science Foundation (INSF), Iran National Elites Foundation (INEF), UNESCO Chair on Interdisciplinary Research in Diabetes at University of Tehran, Iran Society of Biophysical Society and Research Councils of Shiraz University are gratefully acknowledged.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

11224_2018_1218_MOESM1_ESM.docx (3.4 mb)
ESM 1 (DOCX 3458 kb)


  1. 1.
    Ceriello A (2005) Postprandial hyperglycemia and diabetes complications. Diabetes 54(1):1–7CrossRefPubMedGoogle Scholar
  2. 2.
    Ceriello A (1997) Acute hyperglycaemia and oxidative stress generation. Diabet Med 14(S3):45–49CrossRefGoogle Scholar
  3. 3.
    Standl E, Schnell O (2012) Alpha-glucosidase inhibitors 2012–cardiovascular considerations and trial evaluation. Diabetes Vasc Dis Res 9(3):163–169CrossRefGoogle Scholar
  4. 4.
    Bruni C, Sica V, Auricchio F, Covelli I (1970) Further kinetic and structural characterization of the lysosomal α-D-glucoside glucohydrolase from cattle liver. Biochim Biophys Acta 212(3):470–477CrossRefPubMedGoogle Scholar
  5. 5.
    Gruters RA, Neefjes JJ, Tersmette M, de Goede RE, Tulp A, Huisman HG, Miedema F, Ploegh HL (1987) Interference with HIV-induced syncytium formation and viral infectivity by inhibitors of trimming glucosidase. Nature 330(6143):74–77CrossRefPubMedGoogle Scholar
  6. 6.
    Dennis JW, Laferte S, Waghorne C, Breitman ML, Kerbel RS (1987) 1-6 branching of Asn-linked oligosaccharides is directly associated with metastasis. Science 236(4801):582–585CrossRefPubMedGoogle Scholar
  7. 7.
    Tomich C, Da Silva P, Carvalho I, Taft C (2005) Homology modeling and molecular interaction field studies of α-glucosidases as a guide to structure-based design of novel proposed anti-HIV inhibitors. J Compu Aided Mol Des 19(2):83–92CrossRefGoogle Scholar
  8. 8.
    Asano N (2009) Sugar-mimicking glycosidase inhibitors: bioactivity and application. Cell Mol Life Sci 66(9):1479–1492CrossRefPubMedGoogle Scholar
  9. 9.
    Shahidpour S, Panahi F, Yousefi R, Nourisefat M, Nabipoor M, Khalafi-Nezhad A (2015) Design and synthesis of new antidiabetic α-glucosidase and α-amylase inhibitors based on pyrimidine-fused heterocycles. Med Chem Res 24(7):3086–3096CrossRefGoogle Scholar
  10. 10.
    Toobaei Z, Yousefi R, Panahi F, Shahidpour S, Nourisefat M, Doroodmand MM, Khalafi-Nezhad A (2015) Synthesis of novel poly-hydroxyl functionalized acridine derivatives as inhibitors of α-Glucosidase and α-Amylase. Carbohydr Res 411:22–32CrossRefPubMedGoogle Scholar
  11. 11.
    Pinto M, Sousa M, Nascimento M (2005) Xanthone derivatives: new insights in biological activities. Curr Med Chem 12(21):2517–2538CrossRefPubMedGoogle Scholar
  12. 12.
    Ghani U (2015) Re-exploring promising α-glucosidase inhibitors for potential development into oral anti-diabetic drugs: finding needle in the haystack. Eur J Med Chem 103:133–162CrossRefPubMedGoogle Scholar
  13. 13.
    Gopalakrishnan C, Shankaranarayanan D, Nazimudeen S, Viswanathan S, Kameswaran L (1980) Anti-inflammatory and CNS depressant activities of xanthones from Calophyllum inophyllum and Mesua ferrea. Indian J Pharmacol 12(3):181–191Google Scholar
  14. 14.
    Pfister JR, Ferraresi RW, Harrison IT, Rooks WH, Fried JH (1978) Synthesis and antiallergic activity of some mono-and disubstituted xanthone-2-carboxylic acids. J Med Chem 21(7):669–672CrossRefPubMedGoogle Scholar
  15. 15.
    Zheng HH, Luo CT, Chen H, Lin JN, Ye CL, Mao SS, Li YL (2014) Xanthones from Swertia mussotii as multitarget-directed antidiabetic agents. ChemMedChem 9(7):1374–1377CrossRefPubMedGoogle Scholar
  16. 16.
    Abdel-Rahman A, Keshk E, Hanna M, El-Bady SM (2004) Synthesis and evaluation of some new spiro indoline-based heterocycles as potentially active antimicrobial agents. Biorg. Med. Chem 12(9):2483–2488CrossRefGoogle Scholar
  17. 17.
    Aderogba MA, Ndhlala AR, Rengasamy KR, Van Staden J (2013) Antimicrobial and selected in vitro enzyme inhibitory effects of leaf extracts, flavonols and indole alkaloids isolated from Croton menyharthii. Molecules 18(10):12633–12644CrossRefPubMedGoogle Scholar
  18. 18.
    Taha M, Ismail NH, Javaid K, Imran S, Wadood A, Ali M, Khan KM, Saad SM, Rahim F, Choudhary MI (2015) Evaluation of 2-indolcarbohydrazones as potent α-glucosidase inhibitors, in silico studies and DFT based stereochemical predictions. Bioorg Chem 63:24–35CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Ramirez A, García-Rubio S (2003) Current progress in the chemistry and pharmacology of akuammiline alkaloids. Curr Med Chem 10(18):1891–1915CrossRefPubMedGoogle Scholar
  20. 20.
    Han Y-F, Xia M (2010) Multicomponent synthesis of cyclic frameworks on Knoevenagel-initiated domino reactions. Curr Org Chem 14(4):379–413CrossRefGoogle Scholar
  21. 21.
    Masesane IB, Desta ZY (2012) Reactions of salicylaldehyde and enolates or their equivalents: versatile synthetic routes to chromane derivatives. Beilstein J Org Chem 8:2166CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Toure BB, Hall DG (2009) Natural product synthesis using multicomponent reaction strategies. Chem Rev 109(9):4439–4486CrossRefGoogle Scholar
  23. 23.
    Zhu J (2003) Recent developments in the Isonitrile-based multicomponent synthesis of heterocycles. Eur J Org Chem 2003(7):1133–1144CrossRefGoogle Scholar
  24. 24.
    Dangolani SK, Panahi F, Nourisefat M, Khalafi-Nezhad A (2016) 4-Dialkylaminopyridine modified magnetic nanoparticles: as an efficient nano-organocatalyst for one-pot synthesis of 2-amino-4 H-chromene-3-carbonitrile derivatives in water. RSC Adv 6(95):92316–92324CrossRefGoogle Scholar
  25. 25.
    Khalafi-Nezhad A, Nourisefat M, Panahi F (2014) L-proline-modified magnetic nanoparticles (LPMNP): a novel magnetically separable organocatalyst. RSC Adv 4(43):22497–22500CrossRefGoogle Scholar
  26. 26.
    Khalafi-Nezhad A, Nourisefat M, Panahi F (2015) L-cysteine functionalized magnetic nanoparticles (LCMNP): a novel magnetically separable organocatalyst for one-pot synthesis of 2-amino-4 H-chromene-3-carbonitriles in water. Org Biomol Chem 13(28):7772–7779CrossRefPubMedGoogle Scholar
  27. 27.
    Nourisefat M, Panahi F, Khalafi-Nezhad A (2014) Carbohydrates as a reagent in multicomponent reactions: one-pot access to a new library of hydrophilic substituted pyrimidine-fused heterocycles. Org. Biomol. Chem 12(46):9419–9426CrossRefPubMedGoogle Scholar
  28. 28.
    Nourisefat M, Panahi F, Nabipour M, Heidari S, Khalafi-Nezhad A (2016) L-cysteine-functionalized magnetic nanoparticles (LCMNP): as a magnetic reusable organocatalyst for one-pot synthesis of 9-(1H-indol-3-yl) xanthen-4-(9H)-ones. JICS 13(10):1853–1865CrossRefGoogle Scholar
  29. 29.
    Khalafi-Nezhad A, Nourisefat M, Panahi F (2014) Trimethylsilyl iodide as a multifunctional agent in the one-pot synthesis of 9-(1H-Indol-3-yl) xanthen-4-(9H)-ones from O-methyl protected Salicylaldehydes, indoles, and β-Dicarbonyl compounds. Synthesis 46(15):2071–2078CrossRefGoogle Scholar
  30. 30.
    Ganguly NC, Roy S, Mondal P, Saha R (2012) An efficient one-pot organocatalytic synthesis of 9-(1H-indol-3-yl)-xanthen-4-(9H)-ones under mild aqueous micellar conditions. Tetrahedron Lett 53(52):7067–7071CrossRefGoogle Scholar
  31. 31.
    Ganihigama DU, Sureram S, Sangher S, Hongmanee P, Aree T, Mahidol C, Ruchirawat S, Kittakoop P (2015) Antimycobacterial activity of natural products and synthetic agents: pyrrolodiquinolines and vermelhotin as anti-tubercular leads against clinical multidrug resistant isolates of Mycobacterium tuberculosis. Eur J Med Chem 89:1–12CrossRefPubMedGoogle Scholar
  32. 32.
    Kasralikar HM, Jadhavar SC, Bhusare SR (2015) Synthesis and molecular docking studies of oxochromenyl xanthenone and indolyl xanthenone derivatives as anti-HIV-1 RT inhibitors. Biorg Med Chem Lett 25(18):3882–3886CrossRefGoogle Scholar
  33. 33.
    Li M, Zhang B, Gu Y (2012) Facile construction of densely functionalized 4 H-chromenes via three-component reactions catalyzed by l-proline. Green Chem 14(9):2421–2428CrossRefGoogle Scholar
  34. 34.
    Guerreiro LR, Carreiro EP, Fernandes L, Cardote TA, Moreira R, Caldeira AT, Guedes RC, Burke A (2013) Five-membered iminocyclitol α-glucosidase inhibitors: synthetic, biological screening and in silico studies. Biorg Med Chem 21(7):1911–1917CrossRefGoogle Scholar
  35. 35.
    MacKerell Jr AD, Bashford D, Bellott M, Dunbrack Jr RL, Evanseck JD, Field MJ, Fischer S, Gao J, Guo H, Ha S (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins†. J Phys Chem B 102 (18):3586–3616Google Scholar
  36. 36.
    Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kale L, Schulten K (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26(16):1781–1802CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Berendsen HJ, Postma JV, van Gunsteren WF, DiNola A, Haak J (1984) Molecular dynamics with coupling to an external bath. J Chem Phys 81(8):3684–3690CrossRefGoogle Scholar
  38. 38.
    Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31(2):455–461PubMedCentralPubMedGoogle Scholar
  39. 39.
    Todeschini R, Consonni V (2009) Molecular descriptors for chemoinformatics, volume 41 (2 volume set), vol 41. John Wiley & SonsGoogle Scholar
  40. 40.
    Ferreira SB, Sodero AC, Cardoso MF, Lima ES, Kaiser CR, Silva Jr FP, Ferreira VF (2010) Synthesis, biological activity, and molecular modeling studies of 1 h-1, 2, 3-triazole derivatives of carbohydrates as α-glucosidases inhibitors. J Med Chem 53 (6):2364–2375Google Scholar
  41. 41.
    Segel IH (1975) Enzyme kinetics, vol 957. Wiley, New YorkGoogle Scholar
  42. 42.
    Bakan A, Bahar I (2009) The intrinsic dynamics of enzymes plays a dominant role in determining the structural changes induced upon inhibitor binding. PNAS 106(34):14349–14354CrossRefPubMedGoogle Scholar
  43. 43.
    Chovancova E, Pavelka A, Benes P, Strnad O, Brezovsky J, Kozlikova B, Gora A, Sustr V, Klvana M, Medek P (2012) CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures. PLoS Comp Biol 8(10):e1002708CrossRefGoogle Scholar
  44. 44.
    Trapp S, Haider S, Jones P, Sansom MS, Ashcroft FM (2003) Identification of residues contributing to the ATP binding site of Kir6. 2. EMBO J 22(12):2903–2912CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Cer RZ, Mudunuri U, Stephens R, Lebeda FJ (2009) IC 50-to-K i: a web-based tool for converting IC 50 to K i values for inhibitors of enzyme activity and ligand binding. Nucleic Acids Res 37(suppl_2):W441–W445CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Yung-Chi C, Prusoff WH (1973) Relationship between the inhibition constant (Ki) and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an enzymatic reaction. Biochem Pharmacol 22(23):3099–3108CrossRefGoogle Scholar
  47. 47.
    Nicolotti O, Convertino M, Leonetti F, Catto M, Cellamare S, Carotti A (2012) Estimation of the binding free energy by linear interaction energy models. Mini Rev Med Chem 12(6):551–561CrossRefPubMedGoogle Scholar
  48. 48.
    Wells MM, Tillman TS, Mowrey DD, Sun T, Xu Y, Tang P (2015) Ensemble-based virtual screening for cannabinoid-like potentiators of the human glycine receptor α1 for the treatment of pain. J Med Chem 58(7):2958–2966CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Weng Y-Z, Chang DT-H, Huang Y-F, Lin C-W (2011) A study on the flexibility of enzyme active sites. BMC Bioinformatics 12(1):S32CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Alhindi T, Zhang Z, Ruelens P, Coenen H, Degroote H, Iraci N, Geuten K (2017) Protein interaction evolution from promiscuity to specificity with reduced flexibility in an increasingly complex network. Sci Rep 7:44948CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Vogt AD, Pozzi N, Chen Z, Di Cera E (2014) Essential role of conformational selection in ligand binding. Biophys Chem 186:13–21CrossRefPubMedGoogle Scholar
  52. 52.
    Tauler R, Walczak B, Brown SD (2009) Comprehensive chemometrics: chemical and biochemical data analysis. ElsevierGoogle Scholar
  53. 53.
    Craney TA, Surles JG (2002) Model-dependent variance inflation factor cutoff values. Qual Eng 14(3):391–403CrossRefGoogle Scholar
  54. 54.
    Eriksson L, Jaworska J, Worth AP, Cronin MT, McDowell RM, Gramatica P (2003) Methods for reliability and uncertainty assessment and for applicability evaluations of classification-and regression-based QSARs. Environ Health Perspect 111(10):1361CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Maryam Nourisefat
    • 1
  • Najmeh Salehi
    • 1
  • Saeed Yousefinejad
    • 2
  • Farhad Panahi
    • 3
  • Kowsar Bagherzadeh
    • 4
  • Massoud Amanlou
    • 5
  • Ali Khalafi-Nezhad
    • 6
  • Mohammad Hossein Karimi-Jafari
    • 1
    Email author
  • Nader Sheibani
    • 7
  • Ali Akbar Moosavi-Movahedi
    • 1
    • 8
    Email author
  1. 1.Institute of Biochemistry and BiophysicsUniversity of TehranTehranIran
  2. 2.Research Center for Health Sciences, Institute of Health, Department of Occupational Health Engineering, School of HealthShiraz University of Medical SciencesShirazIran
  3. 3.Department of Polymer Engineering and Color TechnologyAmirkabir University of TechnologyTehranIran
  4. 4.Razi Drug Research Center, Iran University of Medical SciencesTehranIran
  5. 5.Department of Medicinal Chemistry, Faculty of Drug Design and Development Research CenterTehran University of Medical SciencesTehranIran
  6. 6.Department of Chemistry, College of SciencesShiraz UniversityShirazIran
  7. 7.Departments of Ophthalmology and Visual Sciences, Cell and Regenerative Biology, and Biomedical EngineeringUniversity of Wisconsin School of Medicine and Public HealthMadisonUSA
  8. 8.UNESCO Chair on Interdisciplinary Research in DiabetesUniversity of TehranTehranIran

Personalised recommendations