In silico evaluation of the antidiabetic potentials of some quercetin derivatives

Authors

  • Olorunfemi A. Eseyin Department of Pharmaceutical and Medicinal Chemistry Faculty of Pharmacy, University of Uyo, Nigeria
  • Charles G. Etiemana Department of Pharmaceutical and Medicinal Chemistry Faculty of Pharmacy, University of Uyo, Nigeria
  • Edet E. Asanga Department of Biochemistry, Arthur Jarvis University, Akpabuyo, Cross River State, Nigeria
  • Paschal C. Anthony
  • Aniekan S. Ebong Department of Pharmaceutical and Medicinal Chemistry Faculty of Pharmacy, University of Uyo, Nigeria
  • Sunday S. Udobre Department of Pharmaceutical and Medicinal Chemistry Faculty of Pharmacy, University of Uyo, Nigeria
  • Emmanuel Attih Department of Pharmaceutical and Medicinal Chemistry Faculty of Pharmacy, University of Uyo, Nigeria
  • Arnold C. Igboasoiyi
  • Emmanuel I. Etim Department of Pharmaceutical and Medicinal Chemistry Faculty of Pharmacy, University of Uyo, Nigeria
  • Ekarika Johnson Department of Pharmaceutical and Medicinal Chemistry Faculty of Pharmacy, University of Uyo, Nigeria
  • Akaniyene O. Daniel Department of Pharmaceutical and Medicinal Chemistry Faculty of Pharmacy, University of Uyo, Nigeria

Keywords:

Autodock, diabetes, quercetin, in silico

Abstract

Background: Quercetin is known to exhibit antidiabetic activity in Type 2 Diabetes mellitus due to its antioxidant property. This study was aimed at designing some derivatives of quercetin and evaluating their binding affinities to target proteins implicated in diabetes mellitus.

Method: Derivatives of quercetin were designed with ChemDraw. The targets: α-amylase (AA), Dipeptidyl peptidase (DPP4); Peroxisome proliferator-activated receptor gamma (PPARG); Glycogen synthase kinases 3β (GSK3); Fructose-1,6-diphosphatase (F16DP); α-glucosidase (AG); Protein Tyrosine Phosphatase 1B (PTP1B); Glucokinase (GK) were downloaded from the Protein data bank. Ligands and targets were converted to pdbqt format using PyRx. Molecular docking of the ligands with each of the target proteins was done using Autodock Vina.  Discovery Studio was used to analyse ligand-protein binding interactions. Calculated molecular and pharmacokinetic properties were obtained from molinspiration and pKCM websites, respectively.

Results: Ligands with the best binding affinity on the various targets are AA (ligand 63: -9.2; quercetin: -8.8), AG (ligand 39: -7.9; quercetin: -7.5), DPP4 (ligand 15: -8.8; quercetin: -9.1),  PPARG (ligand 23 and 31: -10.3; ligand 15: -10.1; quercetin: -8.8), F16DP (ligand 2, 34, and 47: -6.6; quercetin: -6.2); GSK3 (ligand 15: -8.1; quercetin: -7.9), PTP1B (ligand 26: -9.3; quercetin: -8.9), GK (ligand 37: -9.7; quercetin: -8.7). Ligands that had good binding activity on more than one target are: Ligand 15 (AA, PPARG, and DPP4), Ligand 39 (AA and DPP4), Ligands 25 and 31 (PPARG and PTB1B).

Conclusion: Some of the derivatives had better binding affinity than quercetin on various targets are potential candidates for the treatment of diabetes.

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References

Oubre AY, Carlson TJ, King SR, and Reaven EM. From plants to patient, an ethnomedical approach to the identification of a new drug for the treatment of non-insulin-dependent diabetes mellitus. Diabetologia 1970, 40(5): 614-617

. King H and Roewers M. Global estimates for the prevalence of diabetes mellitus and impaired glucose tolerance in adults. Diabetes Care 1993, 16:157-77

Sun C, Zhao C, Guven EC, et al. Dietary polyphenols as antidiabetic agents. Food Frontiers 2020, 1:18–44.

Gopalakrishnan AM and Kumar N. Antimalarial Action of Artesunate Involves DNA Damage Mediated by Reactive Oxygen Species. Antimicrobial Agents and Chemotherapy 2014, 59, 317 - 325.

Tundis R, Loizzo MR and Menichini F. Natural Products as α-Amylase and α-Glucosidase Inhibitors and their hypoglycaemic Potential in the Treatment of Diabetes: An Update. Mini-Reviews in Medicinal Chemistry 2010, 10, 315-331

Wei Shen and Yan-Hua Lu. Molecular docking of citrus flavonoids with some targets related to Diabetes. Bangladesh J Pharmacol 2013; 8: 156-170.

Trott O and Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading, Journal of Computational Chemistry 2010, 31: 455-461

Abu-Hamdah R, Rabiee A, Meneilly GS, Shannon RP, Andersen DK, Elahi D. The extra-pancreatic effects of glucagon-like peptide-1 and related peptides. J Clin Endocrinol Metab. 2009, 94: 1843-52.

Nolte RT, Wisely GB, Westin S, Cobb JE, Lambert MH, Kurokawa R, Rosenfeld MG, Wilson TM, Glass CK, Milburn MV. Ligand binding and co-activator assembly of the peroxisome proliferator-activated receptor-γ. Nature 1998, 16: 137-143.

Choi JH, Banks AS, Kamenecka TM et al. Antidiabetic actions of a non-agonist PPARγ ligand blocking Cdk5-mediated phosphorylation. Nature 2011; 477: 477-81.

Maltarollo VG, Honório KM. Ligand- and structure-based drug design strategies and PPARδ/α selectivity. Chem Biol Drug Design. 2012, 80: 533-44.

David J. Timson. Fructose 1,6-bisphosphatase: getting the message across. Bioscience Reports 2019, 39BSR20190124. https://doi.org/10.1042/BSR20190124).

Johnson JL, Rupasinghe SG, Stefani, F, Schuler MA, Gonzalez de Mejia E. Citrus flavonoids luteolin, apigenin, and quercetin inhibit glycogen synthase kinase-3β enzymatic activity by lowering the interaction energy within the binding cavity. J Med Food 2011, 14: 325-33.

Osolodkin DI, Palyulin VA, Zefirov NS. Structure-based virtual screening of glycogen synthase kinase 3β inhibitors: analysis of scoring functions applied to large true actives and decoy sets. Chem Biol Drug Des. 2011, 78: 378-90.

Akhtar M, Bharatam PV. 3D-QSAR and molecular docking studies on 3-anilino-4-arylmaleimide derivatives as glycogen synthase kinase-3β inhibitors. Chem Biol Drug Design. 2012; 79: 560-71.

Xie L, Lee SY, Andersen JN, Waters S, Shen K, Guo XL, Moller NP, Olefsky JM, Lawrence DS, Zhang ZY. Cellular effects of small molecule PTP1B inhibitors on insulin signalling. Biochemistry. 2003, 42(44):12792-804. doi: 10.1021/bi035238p. PMID: 14596593.

Balamurugan R, Stalin A, Ignacimuthu S. Molecular docking of γ-sitosterol with some targets related to diabetes. Eur J Med Chem. 2012, 47: 38-43.

Diabetes. Bangladesh J Pharmacol 2013; 8: 156-170.

Xie L, Lee SY, Andersen JN, Waters S, Shen K, Guo XL, Moller NP, Olefsky JM, Lawrence DS, Zhang ZY. Cellular effects of small molecule PTP1B inhibitors on insulin signalling. Biochemistry. 2003 Nov 11;42(44):12792-804. doi: 10.1021/bi035238p. PMID: 14596593.

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Published

2022-06-27 — Updated on 2022-06-27

How to Cite

A. Eseyin, O. ., G. Etiemana, C. ., E. Asanga, E. . ., C. Anthony, P. ., S. Ebong, A., S. Udobre, S., Attih, E. ., C. Igboasoiyi, A. ., I. Etim, E. ., Johnson, E., & O. Daniel, A. . (2022). In silico evaluation of the antidiabetic potentials of some quercetin derivatives . Journal of Drug Discovery and Research, 1(1), 1–15. Retrieved from https://www.ddrg.net/index.php/ddrg/article/view/1

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