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Identification and evaluation of natural organosulfur compounds as potential dual inhibitors of α-amylase and α-glucosidase activity: an in-silico and in-vitro approach

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Abstract

We aimed to identify and evaluate natural organosulfur compounds (OSCs) from the genus Allium as potent dual inhibitors of α-amylase and α-glucosidase via a set of molecular simulations and in-vitro analysis. We reported that all OSCs fall under the acceptable scores of Lipinski’s rules and desirable ADME parameters. In-silico screening revealed that OSCs strongly interacted with α-amylase and α-glucosidase crystal structures. Our in-vitro studies with four OSCs having best ΔG-scores demonstrated that alliin, S-allyl-L-cysteine (SAC), N-acetylcysteine (NAC), and S-ethyl-L-cysteine (SEC) exhibit a marked in-vitro inhibition of α-amylase activity, whereas, γ-glutamylcysteine (GGC), SEC, alliin, and SAC potentially inhibited the in-vitro α-glucosidase activity. Our enzyme kinetics studies depicted that the selected OSCs competitively inhibited the α-amylase and α-glucosidase activity. In conclusion, this initial in-silico and the in-vitro report demonstrates the drug-likeness and ADME indices of OSCs and identifies alliin, SAC, NAC, SEC, and GGC as potential dual inhibitors of α-amylase and α-glucosidase.

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References

  1. Nabi R, Alvi SS, Saeed M, Ahmad S, Khan MS. Glycation and HMG-CoA reductase inhibitors: implication in diabetes and associated complications. Curr Diabetes Rev. 2019;15:213–23. https://doi.org/10.2174/1573399814666180924113442

    Article  CAS  PubMed  Google Scholar 

  2. Nabi R, Alvi SS, Shah A, Chaturvedi CP, Faisal M, Alatar AA, et al. Ezetimibe attenuates experimental diabetes and renal pathologies via targeting the advanced glycation, oxidative stress and AGE-RAGE signalling in rats. Arch Physiol Biochem. 2021. https://doi.org/10.1080/13813455.2021.1874996. [Online fisrt article]

    Article  PubMed  Google Scholar 

  3. Standl E, Khunti K, Hansen TB, Schnell O. The global epidemics of diabetes in the 21st century: current situation and perspectives. Eur J Prev Cardiol. 2019;26:7–14. https://doi.org/10.1177/2047487319881021

    Article  PubMed  Google Scholar 

  4. Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pr. 2019;157:107843 https://doi.org/10.1016/j.diabres.2019.107843

    Article  Google Scholar 

  5. Hashim A, Alvi SS, Ansari IA, Khan MS. Phyllanthus virgatus forst extract and it’s partially purified fraction ameliorates oxidative stress and retino-nephropathic architecture in streptozotocin-induced diabetic rats. Pak J Pharm Sci. 2019;32:2697–708. https://doi.org/10.36721/PJPS.2019.32.6.REG.2697-2708.1

    Article  CAS  PubMed  Google Scholar 

  6. Akhter F, Alvi SS, Ahmad P, Iqbal D, Alshehri BM, Khan MS. Therapeutic efficacy of Boerhaavia diffusa (Linn.) root methanolic extract in attenuating streptozotocin-induced diabetes, diabetes-linked hyperlipidemia and oxidative-stress in rats. Biomed Res Ther. 2019;6:3293–306. https://doi.org/10.15419/bmrat.v6i7.556

    Article  Google Scholar 

  7. Nabi R, Alvi SS, Shah A, Chaturvedi CP, Iqbal D, Ahmad S, et al. Modulatory role of HMG-CoA reductase inhibitors and ezetimibe on LDL-AGEs-induced ROS generation and RAGE-associated signalling in HEK-293 Cells. Life Sci. 2019;235:116823 https://doi.org/10.1016/j.lfs.2019.116823

    Article  CAS  PubMed  Google Scholar 

  8. Nabi R, Alvi SS, Khan RH, Ahmad S, Ahmad S, Khan MS. Antiglycation study of HMG-R inhibitors and tocotrienol against glycated BSA and LDL: A comparative study. Int J Biol Macromol. 2018;116:983–92. https://doi.org/10.1016/j.ijbiomac.2018.05.115

    Article  CAS  PubMed  Google Scholar 

  9. Nabi R, Alvi SS, Shah MS, Ahmad S, Faisal M, Alatar AA, et al. A biochemical & biophysical study on in-vitro anti-glycating potential of iridin against D-Ribose modified BSA. Arch Biochem Biophys. 2020;686:108373 https://doi.org/10.1016/j.abb.2020.108373

    Article  CAS  PubMed  Google Scholar 

  10. Nabi R, Alvi SS, Alouffi S, Khan S, Ahmad A, Khan M, et al. Amelioration of neuropilin-1 and rage/matrix metalloproteinase-2 pathway-induced renal injury in diabetic rats by rosuvastatin. Arch Biol Sci. 2021;73:265–78. https://doi.org/10.2298/abs210316021n

    Article  Google Scholar 

  11. Bhatia A, Singh B, Arora R, Arora S. In vitro evaluation of the α-glucosidase inhibitory potential of methanolic extracts of traditionally used antidiabetic plants. BMC Complement Alter Med. 2019;19:74 https://doi.org/10.1186/s12906-019-2482-z

    Article  Google Scholar 

  12. Hashim A, Khan MS, Khan MS, Baig MH, Ahmad S. Antioxidant and αmylase inhibitory property of phyllanthus virgatus L.: An in vitro and molecular interaction study. Biomed Res Int. 2013;2013:729393 https://doi.org/10.1155/2013/729393

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Hess A, Kress S, Rakete S, Muench G, Kornhuber J, Pischetsrieder M, et al. Influence of the fat/carbohydrate component of snack food on energy intake pattern and reinforcing properties in rodents. Behav Brain Res. 2019;364:328–33. https://doi.org/10.1016/j.bbr.2019.02.041

    Article  CAS  PubMed  Google Scholar 

  14. Chaudhury A, Duvoor C, Reddy Dendi VS, Kraleti S, Chada A, Ravilla R, et al. Clinical Review of Antidiabetic Drugs: implications for Type 2 Diabetes Mellitus Management. Front Endocrinol (Lausanne). 2017;8:6 https://doi.org/10.3389/fendo.2017.00006

    Article  Google Scholar 

  15. Alvi SS, Ahmad P, Ishrat M, Iqbal D, Khan MS. Secondary Metabolites from Rosemary (Rosmarinus officinalis L.): Structure, Biochemistry and Therapeutic Implications Against Neurodegenerative Diseases. In: Swamy M, Akhtar M, editors. Nat Bio-active Compd. Singapore: Springer; 2019. p. 1–24. 10.1007/978-981-13-7205-6_1

    Google Scholar 

  16. Ahmad P, Alvi SS, Iqbal D, Khan MS. Insights into pharmacological mechanisms of polydatin in targeting risk factors-mediated atherosclerosis. Life Sci. 2020;254:117756 https://doi.org/10.1016/j.lfs.2020.117756

    Article  CAS  PubMed  Google Scholar 

  17. Kim S, Lee S, Shin D, Yoo M. Change in organosulfur compounds in onion (Allium cepa L.) during heat treatment. Food Sci Biotechnol. 2016;25:115–9. https://doi.org/10.1007/s10068-016-0017-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Chekki R, Najjaa H. Detection of Organo-Sulphur Volatiles in Allium sativum by Factorial Design. Nat Prod Chem Res. 2016;4:1000211 https://doi.org/10.4172/2329-6836.1000211

    Article  CAS  Google Scholar 

  19. Ahmad P, Alvi SS, Khan MS. Functioning of organosulfur compounds from garlic (allium sativum linn) in targeting risk factor-mediated atherosclerosis: a cross talk between alternative and modern medicine. In: Natural Bio-active Compounds: Volume 1: Production and Applications. Springer, Singapore; 2019; p. 561–85. https://doi.org/10.1007/978-981-13-7154-7_20.

  20. Shang A, Cao SY, Xu XY, Gan RY, Tang GY, Corke H, et al. Bioactive compounds and biological functions of garlic (allium sativum L.). Foods. 2019;8:246 https://doi.org/10.3390/foods8070246

    Article  CAS  PubMed Central  Google Scholar 

  21. De Greef D, Barton EM, Sandberg EN, Croley CR, Pumarol J, Wong TL, et al. Anticancer potential of garlic and its bioactive constituents: a systematic and comprehensive review. Semin Cancer Biol. 2021;73:219–64. https://doi.org/10.1016/j.semcancer.2020.11.020

    Article  CAS  PubMed  Google Scholar 

  22. Batiha GES, Beshbishy AM, Wasef LG, Elewa YHA, Al-Sagan AA, El-Hack MEA, et al. Chemical constituents and pharmacological activities of garlic (Allium sativum L.): a review. Nutrients. 2020;12:872 https://doi.org/10.3390/nu12030872

    Article  CAS  Google Scholar 

  23. Ruhee RT, Roberts LA, Ma S, Suzuki K. Organosulfur Compounds: a Review of Their Anti-inflammatory Effects in Human Health. Front Nutr. 2020;7:64 https://doi.org/10.3389/fnut.2020.00064

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Schneider P, Walters WP, Plowright AT, Sieroka N, Listgarten J, Goodnow RA, et al. Rethinking drug design in the artificial intelligence era. Nat Rev Drug Discov. 2020;19:353–64. https://doi.org/10.1038/s41573-019-0050-3

    Article  CAS  PubMed  Google Scholar 

  25. Hessler G, Baringhaus K-H. Artificial Intelligence in Drug Design. Molecules. 2018;23:2520 https://doi.org/10.3390/molecules23102520

    Article  CAS  PubMed Central  Google Scholar 

  26. Pajouhesh H, Lenz GR. Medicinal chemical properties of successful central nervous system drugs. NeuroRx. 2005;2:541–53. https://doi.org/10.1602/neurorx.2.4.541

    Article  PubMed  PubMed Central  Google Scholar 

  27. Hitchcock SA, Pennington LD. Structure-brain exposure relationships. J Med Chem. 2006;49:7559–83. https://doi.org/10.1021/jm060642i

    Article  CAS  PubMed  Google Scholar 

  28. Prasanna S, Doerksen R. Topological Polar Surface Area: A Useful Descriptor in 2D-QSAR. Curr Med Chem. 2008;16:21–41. https://doi.org/10.2174/092986709787002817

    Article  Google Scholar 

  29. Ma XL, Chen C, Yang J. Predictive model of blood-brain barrier penetration of organic compounds. Acta Pharm Sin. 2005;26:500–12. https://doi.org/10.1111/j.1745-7254.2005.00068.x

    Article  CAS  Google Scholar 

  30. Leão RP, Cruz JV, da Costa GV, Cruz JN, Ferreira EFB, Silva RC, et al. Identification of new rofecoxib-based cyclooxygenase-2 inhibitors: a bioinformatics approach. Pharmaceuticals. 2020;13:209 https://doi.org/10.3390/ph13090209

    Article  CAS  PubMed Central  Google Scholar 

  31. Bittermann K, Goss K-U. Predicting apparent passive permeability of Caco-2 and MDCK cell-monolayers: a mechanistic model. PLoS ONE. 2017;12:e0190319 https://doi.org/10.1371/journal.pone.0190319

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Volpe DA. Variability in caco-2 and MDCK cell-based intestinal permeability assays. J Pharm Sci. 2008;97:712–25. https://doi.org/10.1002/jps.21010

    Article  CAS  PubMed  Google Scholar 

  33. Yamashita S, Furubayashi T, Kataoka M, Sakane T, Sezaki H, Tokuda H. Optimized conditions for prediction of intestinal drug permeability using Caco-2 cells. Eur J Pharm Sci. 2000;10:195–204. https://doi.org/10.1016/S0928-0987(00)00076-2

    Article  CAS  PubMed  Google Scholar 

  34. Lundborg M, Wennberg CL, Narangifard A, Lindahl E, Norlén L. Predicting drug permeability through skin using molecular dynamics simulation. J Control Release. 2018;283:269–79. https://doi.org/10.1016/j.jconrel.2018.05.026

    Article  CAS  PubMed  Google Scholar 

  35. Chen C-P, Chen C-C, Huang C-W, Chang Y-C. Evaluating Molecular Properties Involved in Transport of Small Molecules in Stratum Corneum: a Quantitative Structure-Activity Relationship for Skin Permeability. Molecules. 2018;23:911 https://doi.org/10.3390/molecules23040911

    Article  CAS  PubMed Central  Google Scholar 

  36. Roberts JA, Pea F, Lipman J. The clinical relevance of plasma protein binding changes. Clin Pharmacokinet. 2013;52:1–8. https://doi.org/10.1007/s40262-012-0018-5

    Article  CAS  PubMed  Google Scholar 

  37. Gurevich KG. Effect of blood protein concentrations on drug-dosing regimes: practical guidance. Theor Biol Med Model. 2013;10:20 https://doi.org/10.1186/1742-4682-10-20

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Zhao YH, Le J, Abraham MH, Hersey A, Eddershaw PJ, Luscombe CN, et al. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure - Activity relationship (QSAR) with the Abraham descriptors. J Pharm Sci. 2001;90:749–84. https://doi.org/10.1002/jps.1031

    Article  CAS  PubMed  Google Scholar 

  39. Alvi SS, Ansari IA, Khan MS. Pleiotropic role of lycopene in protecting various risk factors mediated atherosclerosis. Ann Phytomedicine. 2015;4:54–60.

    CAS  Google Scholar 

  40. Wang B, Yang LP, Zhang XZ, Huang SQ, Bartlam M, Zhou SF. New insights into the structural characteristics and functional relevance of the human cytochrome P450 2D6 enzyme. Drug Metab Rev 2009;41:573–643. https://doi.org/10.1080/03602530903118729

    Article  CAS  PubMed  Google Scholar 

  41. Zanger UM, Schwab M. Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation. Pharmacol Ther. 2013;138:103–41. https://doi.org/10.1016/j.pharmthera.2012.12.007

    Article  CAS  PubMed  Google Scholar 

  42. Teh LK, Bertilsson L. Pharmacogenomics of CYP2D6: Molecular genetics, interethnic differences and clinical importance. Drug Metab Pharmacokinet. 2012;27:55–67. https://doi.org/10.2133/dmpk.DMPK-11-RV-121

    Article  CAS  PubMed  Google Scholar 

  43. Walko CM, McLeod H. Use of CYP2D6 genotyping in practice: Tamoxifen dose adjustment. Pharmacogenomics. 2012;13:691–7. https://doi.org/10.2217/pgs.12.27

    Article  CAS  PubMed  Google Scholar 

  44. Neves Cruz J, Santana De Oliveira M, Gomes Silva S, Pedro Da Silva Souza Filho A, Santiago Pereira D, Lima E Lima AH, et al. Insight into the Interaction Mechanism of Nicotine, NNK, and NNN with Cytochrome P450 2A13 Based on Molecular Dynamics Simulation. J Chem Inf Model. 2020;60:766–76. https://doi.org/10.1021/acs.jcim.9b00741

    Article  CAS  PubMed  Google Scholar 

  45. Meena SN, Kumar U, Naik MM, Ghadi SC, Tilve SG. α-Glucosidase inhibition activity and in silico study of 2-(benzo[d][1,3]dioxol-5-yl)-4H-chromen-4-one, a synthetic derivative of flavone. Bioorg Med Chem. 2019;27:2340–4. https://doi.org/10.1016/j.bmc.2018.12.021

    Article  CAS  PubMed  Google Scholar 

  46. Mugaranja KP, Kulal A. Alpha glucosidase inhibition activity of phenolic fraction from Simarouba glauca: An in-vitro, in-silico and kinetic study. Heliyon. 2020;6:e04392 https://doi.org/10.1016/j.heliyon.2020.e04392

    Article  PubMed  PubMed Central  Google Scholar 

  47. Dubey S, Ganeshpurkar A, Ganeshpurkar A, Bansal D, Dubey N. Glycolytic enzyme inhibitory and antiglycation potential of rutin. Futur J Pharm Sci. 2017;3:158–62. https://doi.org/10.1016/j.fjps.2017.05.005

    Article  Google Scholar 

  48. Alvi SS, Iqbal D, Ahmad S, Khan MS. Molecular rationale delineating the role of lycopene as a potent HMG-CoA reductase inhibitor: in vitro and in silico study. Nat Prod Res. 2016;30:2111–4. https://doi.org/10.1080/14786419.2015.1108977

    Article  CAS  PubMed  Google Scholar 

  49. Arvindekar A, Ghadyale V, Takalikar S, Haldavnekar V. Effective control of postprandial glucose level through inhibition of intestinal alpha glucosidase by Cymbopogon martinii (Roxb.). Evid-based Complement Alter Med. 2012;2012:372909 https://doi.org/10.1155/2012/372909

    Article  Google Scholar 

  50. Zhang H, Wang G, Beta T, Dong J. Inhibitory properties of aqueous ethanol extracts of propolis on alpha-glucosidase. Evid-based Complement Alter Med. 2015;2015:587383 https://doi.org/10.1155/2015/587383

    Article  Google Scholar 

  51. Sadeghi M, Moradi M, Madanchi H, Johari B. In silico study of garlic (Allium sativum L.)-derived compounds molecular interactions with α-glucosidase. Silico Pharm. 2021;9:11 https://doi.org/10.1007/s40203-020-00072-9

    Article  Google Scholar 

  52. Hyeong-U S, Eun-Kyeong Y, Chi-Yeol Y, Chul-Hong P, Myung-Ae B, Tae-Ho K, et al. Effects of synergistic inhibition on α-glucosidase by phytoalexins in soybeans. Biomolecules. 2019;9:828 https://doi.org/10.3390/biom9120828

    Article  CAS  Google Scholar 

  53. Ge J, Wang Z, Cheng Y, Ren J, Wu B, Li W, et al. Computational study of novel natural inhibitors targeting aminopeptidase N(CD13). Aging (Albany NY). 2020;12:8523–35. https://doi.org/10.18632/aging.103155

    Article  CAS  Google Scholar 

  54. 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;7:42717 https://doi.org/10.1038/srep42717

    Article  PubMed  PubMed Central  Google Scholar 

  55. Alvi SS, Ansari IA, Khan I, Iqbal J, Khan MS. Potential role of lycopene in targeting proprotein convertase subtilisin/kexin type-9 to combat hypercholesterolemia. Free Radic Biol Med. 2017;108:394–403. https://doi.org/10.1016/j.freeradbiomed.2017.04.012

    Article  CAS  Google Scholar 

  56. Jiménez J, Doerr S, Martínez-Rosell G, Rose AS, De Fabritiis G. DeepSite: Protein-binding site predictor using 3D-convolutional neural networks. Bioinformatics. 2017;33:3036–42. https://doi.org/10.1093/bioinformatics/btx350

    Article  CAS  PubMed  Google Scholar 

  57. Wang G, Liu Z, Li M, Li Y, Alvi SS, Ansari IA, et al. Ginkgolide B Mediated Alleviation of Inflammatory Cascades and Altered Lipid Metabolism in HUVECs via Targeting PCSK-9 Expression and Functionality. Biomed Res Int. 2019;2019:7284767 https://doi.org/10.1155/2019/7284767

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Alvi SS, Ansari IA, Ahmad MK, Iqbal J, Khan MS. Lycopene amends LPS induced oxidative stress and hypertriglyceridemia via modulating PCSK-9 expression and Apo-CIII mediated lipoprotein lipase activity. Biomed Pharmacother. 2017;96:1082–93. https://doi.org/10.1016/j.biopha.2017.11.116

    Article  CAS  PubMed  Google Scholar 

  59. Du X, Li Y, Xia YL, Ai SM, Liang J, Sang P, et al. Insights into protein–ligand interactions: Mechanisms, models, and methods. Int J Mol Sci. 2016;17:144 https://doi.org/10.3390/ijms17020144

    Article  CAS  PubMed Central  Google Scholar 

  60. Gurung AB, Ali MA, Lee J, Farah MA, Al-Anazi KM. Unravelling lead antiviral phytochemicals for the inhibition of SARS-CoV-2 Mpro enzyme through in silico approach. Life Sci. 2020;255:117831 https://doi.org/10.1016/j.lfs.2020.117831

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors are highly indebted to the Department of Health Research (DHR), Ministry of Health & Family Welfare (MoHFW), Govt. of India, for providing the Young Scientist Grant (YSS Project No. 12014/13/2019-HR) for the smooth conduction of this work. The authors are also thankful to Integral University for providing laboratory for the smooth completion of this work. This paper has Integral University manuscript communication no. IU/R&D/2021-MCN0001155.

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Author contributionsInterventional hypothesis: MSK; In-silico and biochemical measurements: PA & SSA; Data analysis: SSA & PA; Paper writing and Figure preparation: PA, & SSA; Statistical analysis: PA & SSA; Revision, English editing & approval of the final paper: JI, MSK & SSA.

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Correspondence to M. Salman Khan.

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Ahmad, P., Alvi, S.S., Iqbal, J. et al. Identification and evaluation of natural organosulfur compounds as potential dual inhibitors of α-amylase and α-glucosidase activity: an in-silico and in-vitro approach. Med Chem Res 30, 2184–2202 (2021). https://doi.org/10.1007/s00044-021-02799-2

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