HOMOLOGY MODELLING OF α - AMYLASE; ITS MOLECULAR DOCKING BY FLAVONOIDS AS POTENTIAL LIGANDS
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Published
Nov 18, 2020
Page:
47-55
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SK. CHAND BASHA
Department of Zoology and Aquaculture, Acharya Nagarjuna University, Guntur, 522510, Andhra Pradesh, India.
KRS. SAMBASIVA RAO
Mizoram University (A Central University), Aizawal, 796004, Mizoram, India.
T. SAMBASIVA RAO
Department of Zoology, K. B. N. College, Vijayawada, 520001, Andhra Pradesh, India.
P. CHANDRA SAI
Department of Biotechnology, National Institute of Technology, Warangal, 506004, Telangana, India.
Abstract
Bioinformatics, an essential and integrated wing of advanced Life sciences which manages, analyses and manipulates the crucial mammoth data of Bio molecules where in, Molecular Modelling and Molecular Docking are its crucial tools. Considering the Flavonoids role as popular α - Amylase enzyme inhibitors, which in turn had a therapeutic role in Diabetes regulation, the current objective of the work has been designed to test the In silico analysis of the α - Amylase enzyme. Molecular docking was conducted by employing 6 potential flavonoid ligands: (a). Myricetin (b). Quercetin (c). Zinc Luteolin (d). Catechin (e). Cyanidin and (f). Daidzein. Modeller V 9.17 was used for Homology modelling of α - Amylase and iGEMDOCK v 2.1 was used for Molecular docking between α - Amylase enzyme and the ligands. Results suggests that Myricetin found to be the best of the potential flavonoid ligands with binding energy of - 116.234 kcal/mol, where as the binding energy of the remaining ligands in the descending order: Cyanidin: - 98.8208 kcal/mol ; Catechin: - 97.3075 kcal/mol; Zinc Luteolin: - 93.7762 kcal/mol; Quercetin: - 90.1663 kcal/mol and Daidzein: - 85.4134 kcal/mol. From the work, it can be concluded that Myricetin found to be the best of the flavonoid ligands (dry lab analysis), further wet lab analysis at the larger scale has to be put forth to tap its therapeutic potentiality against diabetes treatment.
Keywords:
Modeller V 9.17, iGEMDOCK v 2.1, flavonoids and myricetin.
Article Details
How to Cite
BASHA, S. C., RAO, K. S., RAO, T. S., & SAI, P. C. (2020). HOMOLOGY MODELLING OF α - AMYLASE; ITS MOLECULAR DOCKING BY FLAVONOIDS AS POTENTIAL LIGANDS. UTTAR PRADESH JOURNAL OF ZOOLOGY, 41(17), 47-55. Retrieved from https://mbimph.com/index.php/UPJOZ/article/view/1712
Section
Original Research Article
References
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Hsu KC, Chen YF, Lin SR, Yang JM. iGEMDOCK: A graphical environment of enhancing GEMDOCK using pharmacological interactions and post-screening analysis. BMC Bioinformatics. 2011;12(1):S33.
Yang JM, Chen CC. GEMDOCK: A generic evolutionary method for molecular docking. Proteins: Structure, Function, and Bioinformatics. 2004;55(2):288-304.
Kaladhar Svgk Dowluru, et al. Protein interaction networks in metallo proteins and docking approaches of metallic compounds with TIMP and MMP in control of MAPK pathway. Letters in Drug Design & Discovery. 2013;10:49-55 49.
DeLano WL. Pymol: An open-source molecular graphics tool. CCP4 Newsletter on Protein Crystallography. 2002;40:82- 92.
Bertini I, Cavallaro G. Bioinformatics in bioinorganic chemistry. Metallomics. 2010;2(1):39-51.
Kaladhar Svgk Dowluru, et al. Protein interaction networks in metallo proteins and docking approaches of metallic compounds with TIMP and MMP in control of MAPK pathway. Letters in Drug Design & Discovery. 2013;10:49-55.
McConkey BJ, Sobolev V, Edelman M. The performance of current methods in ligand protein docking. Current Science. 2002;83: 845–855.
Nisha J. In-silico screening of alpha amylase enzyme inhibitors from Siddha formulation Pungampoo Chooranam by molecular docking analysis for the management of type II diabetes mellitus. Int. J. Curr. Res. Med. Sci. 2017;3(10):24-34.
Kandra L. α-Amylases of medical and industrial importance. Journal of Molecular Structure. 2003;666-667:487498.
Sithichoke Tangphatsornruang, Maliwan Naconsie, Chinae Thammarongtham, Jarunya Narangajavana. Isolation and characterization of an α-amylase gene in cassava (Manihot esculenta). Plant Physiology and Biochemistry. 2005;43(9):821-827.
Selvam K, Vishnupriya B, Subhash Chandra Bose V. Screening and quantification of marine actinomycetes producing industrial enzymes amylase, cellulase and lipase from south coast of India. International Journal of Pharmaceutical & Biological Archives. 2011;2(5):1481-1487.
Rahimzadeh M, Jahanshahi S, Moein S, Moein MR. Evaluation ofalpha-amylase inhibition by Urtica dioica and Juglans regia extracts. Iran J Basic Med Sci. 20147;17(6):465-469.
Sang Kim, Chong-Suk Kwon, Kun Ho Son. Inhibition of alpha-glucosidase and amylase by Luteolin, a flavonoid, Biosci. Biotechnol. Biochem. 2000;64(11):2458-2461.
Kenjiro Tadera, Yuji Minami, Kouta Takamatsu, Tomoko Matsuoka. Inhibition of α – Glucosidase and α – Amylase by flavonoids. J Nutr Sci Vitaminol. 2006;52:149-153.
Panche AN, Diwan AD, Chandra SR. Journal of Nutritional Science. 2006;5(e47).
DOI: 10.1017/jns.2016.41
Havsteen B. Flavonoids, a class of natural products of high pharmacological potency. Biochem Pharmacol. 1983;32:1141–1148.
Wulan et al. Bioinformation. 2014;10(4):209-215.
Arumugam Madeswaran, et al. In silico approach for alpha-amylase inhibitory activity of diosmetin and galangin. International Journal of Phytopharmacy. 2014;4(5):124-127.
Reddy ER, Babu RS, Chandrasai PD, Madhuri P. Exploration of the binding modes of L-asparaginase complexed with its amino acid substrates by molecular docking, dynamics and simulation. 3 Biotech. 2016;6(1):105.
Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. Gen Bank. Nucleic acids research, 36(Database issue). 2008;D25.
Johnson M, Zaretskaya I, Raytselis Y, Merezhuk Y, McGinnis S, Madden TL. NCBI BLAST: A better web interface. Nucleic Acids Research. 2008;36 (suppl_2):W5-W9.
Wishart DS, Knox C, Guo AC, Shrivastava S, Hassanali M, Stothard P, Chang Z, Woolsey J. DrugBank: A comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Research. 2006;34(suppl_1):D668-D672.
Irwin JJ, Sterling T, Mysinger MM, Bolstad ES, Coleman RG. ZINC: A free tool to discover chemistry for biology. Journal of Chemical Information and Modelling. 2012;52(7):1757-1768.
Pola M, Durthi CP, Rajulapati SB, Reddy Erva R. Modelling and optimization of L-Asparaginase production from Bacillus stratosphericus. Current Trends in Bio-technology & Pharmacy. 2018;12(4).
Webb B, Sali A. Protein structure modeling with MODELLER. In Functional Genomics. Humana Press, New York, NY. 2017;39-54.
Lovell SC, Davis IW, Arendall III WB, de Bakker PIW, Word JM, Prisant MG, Richardson JS, Richardson DC. Structure validation by Calpha geometry: Phi, psi and Cbeta deviation. Proteins: Structure, Function Genet. 2002;50:437-450.
Sali A, Blundell TL. Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol. 1993;234(3):779–815.
Fiser A, Do RKG, Sali A. Modeling of loops in protein structures. Protein Sci. 2000;9(9):1753–1773.
Brooks BR, et al. CHARMM: The biomolecular simulation program. J Comput Chem. 2009;30(10):1545–1614.
Sali A, Overington JP. Derivation of rules for comparative protein modeling from a database of protein structure alignments. Protein Sci. 1994;3(9):1582–1596.
Shen MY, Sali A. Statistical potential for assessment and prediction of protein structures. Protein Sci. 2006;15(11):2507–2524.
Michael Kaufmann, et al. (Eds.). Functional genomics: Methods and protocols, methods in molecular biology. © Springer Science+Business Media LLC. 2017;1654.
Hsu KC, Chen YF, Lin SR, Yang JM. iGEMDOCK: A graphical environment of enhancing GEMDOCK using pharmacological interactions and post-screening analysis. BMC Bioinformatics. 2011;12(1):S33.
Yang JM, Chen CC. GEMDOCK: A generic evolutionary method for molecular docking. Proteins: Structure, Function, and Bioinformatics. 2004;55(2):288-304.
Kaladhar Svgk Dowluru, et al. Protein interaction networks in metallo proteins and docking approaches of metallic compounds with TIMP and MMP in control of MAPK pathway. Letters in Drug Design & Discovery. 2013;10:49-55 49.
DeLano WL. Pymol: An open-source molecular graphics tool. CCP4 Newsletter on Protein Crystallography. 2002;40:82- 92.