In Silico Computations of Selective Phytochemicals as Potential Inhibitors Against Major Biological Targets of Diabetes Mellitus

Author(s): Ammara Akhtar, Anam Amir, Waqar Hussain, Abdul Ghaffar, Nouman Rasool*

Journal Name: Current Computer-Aided Drug Design

Volume 15 , Issue 5 , 2019

Become EABM
Become Reviewer

Graphical Abstract:


Abstract:

Background: In the past few years, several developments have been made to understand and control the complications and harmful side-effects associated with the disorder diabetes mellitus (DM). Many new steps have been taken in a better understanding of the pathophysiology of the disease. With the advancement in the field of medical sciences, various novel therapies have been developed to efficiently control the pathological effects of diabetes mellitus. Recently, phytochemicals possessing various medicinal properties have opened up a new vast range of opportunities to design novel therapeutic drugs against diabetes mellitus.

Objective: The present study aims to identify and screen phytochemicals as potent and novel inhibitors against diabetes mellitus.

Methods: Three major biological targets of diabetes mellitus named Cytochrome P450, glycogen synthase kinase and PPARγ are targeted using phytochemicals by performing pharmacological properties prediction, molecular docking and density functional theory studies.

Results: Out of 108 phytochemicals, 20, 12 and 3 phytochemicals showed higher binding affinity values as compared to chemically synthesized drugs against cytochrome P450, glycogen synthase kinase and PPARγ, respectively.

Conclusion: The screened phytochemicals have strong inhibitory potential against diabetes mellitus and in future, these compounds, holding immense potential, can be considered as candidate drugs for treating diabetes mellitus.

Keywords: Diabetes mellitus, receptors, phytochemicals, ADMET, molecular docking, DFT.

[1]
Tiwari, A.K.; Rao, J.M. Diabetes mellitus and multiple therapeutic approaches of phytochemicals: Present status and future prospects. Curr. Sci., 2002, 83(1), 30-38.
[2]
Mathers, C.D.; Loncar, D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med., 2006, 3(11), 2011-2030.
[3]
Sarwar, N.; Gao, P.; Seshasai, S.; Gobin, R.; Kaptoge, S.; Di Angelantonio, E.; Ingelsson, E.; Lawlor, D.; Selvin, E. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: A collaborative meta-analysis of 102 prospective studies. The Lancet, 2010, 375(973), 2215-2222.
[4]
Bourne, R.R.; Stevens, G.A.; White, R.A.; Smith, J.L.; Flaxman, S.R.; Price, H.; Jonas, J.B.; Keeffe, J.; Leasher, J.; Naidoo, K. Causes of vision loss worldwide, 1990-2010: A systematic analysis. The Lancet Global. Health, 2013, 1(6), 339-349.
[5]
Selvaraj, G.; Gurudeeban, S.; Kaliamurthi, S.; Satyavani, K.; Çakmak, Z.E.; Zeynep, E.Ç.; Çakmak, T.; Turgay, Ç. In silico validation of microalgal metabolites against Diabetes mellitus. Diabetes Mellitus, 2017, 20(4), 301-307.
[6]
Tanaka, T.; Tong, H-H. XU, Y.-M.; Ishimaru, K.; Nonaka, G.-i.; Nishioka, I., Tannins and related compounds. CXVII. Isolation and characterization of three new ellagitannins, lagerstannins A, B and C, having a gluconic acid core, from Lagerstroemia speciosa (L.) Pers. Chem. Pharm. Bulletin., 1992, 40(11), 2975-2980.
[7]
Ceriello, A. New insights on oxidative stress and diabetic complications may lead to a “causal” antioxidant therapy. Diabetes care, 2003, 26(5), 1589-1596.
[8]
Kusirisin, W.; Jaikang, C.; Chaiyasut, C.; Narongchai, P. Effect of polyphenolic compounds from Solanum torvum on plasma lipid peroxidation, superoxide anion and cytochrome P450 2E1 In human liver microsomes. Med. Chem., 2009, 5(6), 583-588.
[9]
Pitchai, D.; Manikkam, R.; Rajendran, S.R.; Pitchai, G. Database on pharmacophore analysis of active principles, from medicinal plants. Bioinformation, 2010, 5(2), 43.
[10]
Kavitha, E.; Sundaraganesan, N.; Sebastian, S. Molecular structure, vibrational spectroscopic and HOMO, LUMO studies of 4-nitroaniline by density functional method. Indian J. Pure App. Phy., 2010, 48(1), 20-30.
[11]
Qin, P.; Zhu, H.; Edvinsson, T.; Boschloo, G.; Hagfeldt, A.; Sun, L. Design of an organic chromophore for p-type dye-sensitized solar cells. J. Am. Chem. Soc., 2008, 130(27), 8570-8571.
[12]
Sathyanarayanmoorthi, V.; Karunathan, R.; Kannappan, V. Molecular modeling and spectroscopic studies of Benzothiazole. J. Chem., 2013, 2013, 14.
[13]
Middleton, E.; Kandaswami, C.; Theoharides, T.C. The effects of plant flavonoids on mammalian cells: implications for inflammation, heart disease, and cancer. Pharmacol. Rev., 2000, 52(4), 673-751.
[14]
Olefsky, J.M. Prospects for research in diabetes mellitus. Jama, 2001, 285(5), 628-632.
[15]
Bailey, C.J. Potential new treatments for type 2 diabetes. Trends in Pharma. Sci., 2000, 21(7), 259-265.
[16]
Matysiak, J. Evaluation of electronic, lipophilic and membrane affinity effects on antiproliferative activity of 5-substituted-2-(2, 4-dihydroxyphenyl)-1, 3, 4-thiadiazoles against various human cancer cells. Eur. J. Med. Chem., 2007, 42(7), 940-947.
[17]
Zhan, C-G.; Nichols, J.A.; Dixon, D.A. Ionization potential, electron affinity, electronegativity, hardness, and electron excitation energy: Molecular properties from density functional theory orbital energies. J. Phys. Chem. A, 2003, 107(20), 4184-4195.
[18]
Zheng, Y.; Zheng, M.; Ling, X.; Liu, Y.; Xue, Y.; An, L.; Gu, N.; Jin, M. Design, synthesis, quantum chemical studies and biological activity evaluation of pyrazole–benzimidazole derivatives as potent Aurora A/B kinase inhibitors. Bioorg. Med. Chem. Lett., 2013, 23(12), 3523-3530.
[19]
Gogoi, D.; Baruah, V.J.; Chaliha, A.K.; Kakoti, B.B.; Sarma, D.; Buragohain, A.K. Identification of novel human renin inhibitors through a combined approach of pharmacophore modelling, molecular DFT analysis and in silico screening. Comput. Biol. Chem., 2017, 69, 28-40.
[20]
Kohn, W.; Becke, A.D.; Parr, R.G. Density functional theory of electronic structure. J. Phys. Chem., 1996, 100(31), 12974-12980.
[21]
Dong, J.; Wang, N-N.; Yao, Z-J.; Zhang, L.; Cheng, Y.; Ouyang, D.; Lu, A-P.; Cao, D-S. ADMETlab: A platform for systematic ADMET evaluation based on a comprehensively collected ADMET database. J. Cheminform., 2018, 10(1), 29.
[22]
Mondal, S.I.; Mahmud, Z.; Elahi, M.; Akter, A.; Jewel, N.A.; Islam, M.M.; Ferdous, S.; Kikuchi, T. Study of intra-inter species protein-protein interactions for potential drug targets identification and subsequent drug design for Escherichia coli O104: H4 C277-11. In silico Pharmacology., 2017, 5(1), 1.


Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 15
ISSUE: 5
Year: 2019
Page: [401 - 408]
Pages: 8
DOI: 10.2174/1573409915666190130164923
Price: $65

Article Metrics

PDF: 51
HTML: 5