IN SILICO ANALYSIS OF ACTIVE CONSTITUENTS OF SILYMARIN AS ΑLPHA-GLUCOSIDASE ENZYME INHIBITORS IN TYPE 2 DIABETES MELLITUS
Objective: Type 2 diabetes mellitus (T2DM) is an acute metabolic disorder, in which the vogue is increasing persistently globally. The maltase-glucoamylase/alpha-glucosidase inhibitor is an oral antidiabetic drug collectively, which is utilizing for regulating carbohydrates that ordinarily transformed into simple sugars and absorbed by the intestine. Researchers need to constantly explore alternative therapeutic strategies for the clinical management of DM due to the increased adverse event caused by conservative antidiabetic agents. The present study proposes a substitute drug to examine the seven bioactive phytocomponents of Silybum marianum (milk thistle) that can regulate the hyperglycemia by downregulating alpha-glucosidase and its activity.
Methods: Different integrated web-based in silico tools and techniques were used to model the enzyme (receptor) as well as to determine the druggability of different active constituents of silymarin and their pharmacokinetics were predicted. Further, the active site of the enzyme was predicted followed by molecular docking method.
Results: The results show silychristin A and silydianin having less carcinogenicity and strong interaction to the target protein (alpha-glucosidase) compare to the reference drugs (acarbose and miglitol) and these two molecules can be used for the best drug molecules in T2DM.
Conclusion: In the proposed study, the in silico analysis helps researchers to utilize these compounds for clinical applications. The conclusion also suggests that synthetically and semi-synthetically, nucleus and peripheral modifications, either in the form of skeletal rearrangements or partial degradations as well as functional group addition and replacement of the active molecules present in silymarin giving access to new structural motifs, which can be used in future as a lead compounds for antagonising the alpha-glucosidase in the treatment of diabetes mellitus.
2. López-Cuenca A, Gómez-Molina M, Flores-Blanco PJ, Sánchez-Martínez M, García-Narbon A, De Las Heras-Gómez I, et al. Comparison between Type-2 and type-1 myocardial infarction: Clinical features, treatment strategies and outcomes. J Geriatr Cardiol 2016;13:15-22.
3. Jain R, Jain P, Jain P. A review on treatment and prevention of diabetes mellitus. Int J Curr Pharm Res 2016;8:16-8.
4. Okur ME, Karantas ID, Siafaka PI. Diabetes mellitus: A review on pathophysiology, current status of oral medications and future perspectives. Acta Pharm Sci 2017;55:61-82.
5. Scheen AJ. Pathophysiology of Type 2 diabetes. Acta Clin Belg 2003;58:335-41.
6. Staiger H, Machicao F, Fritsche A, Häring HU. Pathomechanisms of Type 2 diabetes genes. Endocr Rev 2009;30:557-85.
7. Chen L, Magliano DJ, Zimmet PZ. The worldwide epidemiology of Type 2 diabetes mellitus present and future perspectives. Nat Rev Endocrinol 2011;8:228-36.
8. Olokoba AB, Obateru OA, Olokoba LB. Type 2 diabetes mellitus: A review of current trends. Oman Med J 2012;27:269-73.
9. Nair SS, Kavrekar V, Mishra A. In vitro studies on alpha amylase and alpha glucosidase inhibitory activities of selected plant extracts. Eur J Exp Biol 2013;3:128-32.
10. Peter SJ, Sabina EP. Global current trends in natural products for diabetes management: A review. Int J Pharm Pharm Sci 2016;8:20-8.
11. Yee HS, Fong NT. A review of the safety and efficacy of acarbose in diabetes mellitus. Pharmacotherapy 1996;16:792-805.
12. van de Laar FA. Alpha-glucosidase inhibitors in the early treatment of Type 2 diabetes. Vasc Health Risk Manag 2008;4:1189-95.
13. Moradi M, Mousavi S. Drug use evaluation of diabetes mellitus in non-hospitalized patients. Int J Pharm Pharm Sci 2016;8:337-41.
14. Zonoubi A, Perumal DV, Prasad P, Chandy V, Mafibaniasadi Z. Milk thistle-morphology, chemistry and pharmacological action. Int J Innov Pharm Sci Res 2019;7:14-40.
15. Kitchen DB, Decornez H, Furr JR, Bajorath J. Docking and scoring in virtual screening for drug discovery: Methods and applications. Nat Rev Drug Discov 2004;3:935-49.
16. Gilson MK, Zhou HX. Calculation of protein-ligand binding affinities. Annu Rev Biophys Biomol Struct 2007;36:21-42.
17. Qing X, Lee XY, De Raeymaeker J, Tame JR, Zhang KY, De Maeyer M, et al. Pharmacophore modeling: Advances, limitations, and current utility in drug discovery. J Recept Ligand Channel Res 2014;7:81-92.
18. Yang SY. Pharmacophore modeling and applications in drug discovery: Challenges and recent advances. Drug Discov Today 2010;15:444-50.
19. Mukesh B, Rakesh K. Molecular docking: A review. Int J Res Ayurveda Pharm 2011;2:1746-51.
20. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990;215:403-10.
21. Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Res 1997;25:3389-402.
22. Gibson TJ, Higgins DG. Multiple sequence alignment using ClustalW and ClustalX. Curr Protoc Bioinformatics 2002;Chapter 2:Unit 2.3.
23. Deshpande N, Addess KJ, Bluhm WF, Merino-Ott JC, Townsend-Merino W, Zhang Q, et al. The RCSB protein data bank: A redesigned query system and relational database based on the mmCIF schema. Nucleic Acids Res 2005;33:D233-7.
24. Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: A program to check the stereochemical quality of protein structures. J Appl Crystallogr 1993;26:283-91.
25. Gopalakrishnan K, Sowmiya G, Sheik SS, Sekar K. Ramachandran plot on the web (2.0). Protein Pept Lett 2007;14:669-71.
26. Emsley P, Cowtan K. Coot: Model-building tools for molecular graphics. Acta Crystallogr D Biol Crystallogr 2004;60:2126-32.
27. Krissinel E, Henrick K. Secondary-structure matching (SSM), a new tool for fast protein structure alignment in three dimensions. Acta Crystallogr D Biol Crystallogr 2004;60:2256-68.
28. Tian W, Chen C, Lei X, Zhao J, Liang J. CASTp 3.0: Computed atlas of surface topography of proteins. Nucleic Acids Res 2018;46:W363-7.
29. Edelsbrunner H. Three-dimensional alpha shapes. ACM Trans Graph 1994;13:43-72.
30. Shape ID. The union of balls and its dual shape. Discrete Comput Geom 1995;13:415-40.
31. Edelsbrunner H, Shah NR. Incremental topological flipping works for regular triangulation. Algorithmica 1996;15:223-41.
32. Edelsbrunner H, Liang J, Fu P, Facello M. Measuring Proteins and Voids in Proteins. Vol. 1. Proceedings of the Twenty-Eighth Hawaii International Conference; 1995. p. 256.
33. Edelsbrunner H, Facello M, Liang J. On the definition and the construction of pockets in macromolecules. Discrete Appl Math 1998;88:83-102.
34. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 2001;46:3-26.
35. Cheng F, Li W, Zhou Y, Shen J, Wu Z, Liu G, et al. AdmetSAR: A comprehensive source and free tool for assessment of chemical ADMET properties. J Chem Inf Model 2012;52:3099-105.
36. Ertl P, Rohde B, Selzer P. Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties. J Med Chem 2000;43:3714-7.
37. Veber DF, Johnson SR, Cheng HY, Smith BR, Ward KW, Kopple KD, et al. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem 2002;45:2615-23.
38. Edwards BS, Bologa C, Young SM, Balakin KV, Prossnitz ER, Savchuck NP, et al. Integration of virtual screening with high-throughput flow cytometry to identify novel small molecule formylpeptide receptor antagonists. Mol Pharmacol 2005;68:1301-10.
39. Güner O, Clement O, Kurogi Y. Pharmacophore modeling and three dimensional database searching for drug design using catalyst: Recent advances pharmacophore modeling and three dimensional database searching for drug design using catalyst: Recent advances. Curr Med Chem 2004;11:763-71.
40. Navaneethakrishnan P, Prashantha CN, Boopathi S, Sabitha R, Mathan G. In silico design of Butea monosperma floral derived compounds and its inhibitory effect on ? catenin, gsk-3 ? and apc complex proteins in colorectal cancer. Int J Drug Discov 2013;5:191-7.
This work is licensed under a Creative Commons Attribution 4.0 International License.
The publication is licensed under CC By and is open access. Copyright is with author and allowed to retain publishing rights without restrictions.