MOLECULAR DOCKING STUDY OF THE MAJOR COMPOUNDS FROM GARCINIA ATROVIRIDIS ON HUMAN SGLT-2 PROTEIN TRANSPORT USING STRUCTURE-BASED DRUG DESIGN METHOD

ASEP KUSWANDI; AGUS RUSDIN; VITA M. TARAWAN; HANNA GOENAWAN; RONNY LESMANA; MUCHTARIDI MUCHTARIDI

doi:10.22159/ijap.2022v14i4.44390

Authors

ASEP KUSWANDI Physiology Division, Department of Biomedical Science, Faculty of Medicine, Universitas Padjadjaran, Jatinangor 45363, Indonesia
AGUS RUSDIN Department of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Jatinangor 45363, Indonesia
VITA M. TARAWAN Physiology Division, Department of Biomedical Science, Faculty of Medicine, Universitas Padjadjaran, Jatinangor 45363, Indonesia
HANNA GOENAWAN Physiology Division, Department of Biomedical Science, Faculty of Medicine, Universitas Padjadjaran, Jatinangor 45363, Indonesia
RONNY LESMANA Physiology Division, Department of Biomedical Science, Faculty of Medicine, Universitas Padjadjaran, Jatinangor 45363, Indonesia
MUCHTARIDI MUCHTARIDI Department of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Jatinangor 45363, Indonesia

DOI:

https://doi.org/10.22159/ijap.2022v14i4.44390

Keywords:

Garcinia atroviridis, SGLT-2, Molecular Docking, Pharmacophore Modeling

Abstract

Objective: The objective of this work was to study the molecular interactions of phytochemicals in Garcinia atroviridis with SGLT-2 protein transport.

Methods: Molecular docking simulation using Autodock 4.2 was performed to explore the binding affinity of phytochemicals in Garcinia atroviridis against SGLT-2 protein transport. The structure-based pharmacophore model was derived using LigandScout 4.4 Advanced to investigate the important chemical interactions of the ligands and protein target. The evaluation was conducted based on the free energy binding and visualization in silico.

Results: From this study, Myricetin is the most effective compound having similarity of interaction with the amino acid residue, 4 of 5 are hydrogen bond interactions between the amino acid; HIS80, ASN75, TRP291, and LYS321 amino acid interacted with the oxygen as the proton acceptor from benzenes of the Myricetin structure, in addition, Myricetin also has the lower binding energy and inhibition constant (-9.54 kcal/mol and 101.93 nM, respectively) as compared to other compounds.

Conclusion: Hence, Myricetin could become the potential compound as an antidiabetic agent in the future with good activity and lower side effects.

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References

American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2009 Mar 24;32Suppl 1:S62-7. doi: 10.2337/dc09-S062, PMID 19118289.

Sone H. Diabetes mellitus. In: Vasan RS, Sawyer DB, editors. Encyclopedia of cardiovascular research and medicine. Oxford: Elsevier; 2018. p. 9-16.

Wilcox G. Insulin and insulin resistance. Clin Biochem Rev. 2005 May 21;26(2):19-39. PMID 16278749.

Thrasher J. Pharmacologic management of type 2 diabetes mellitus: available therapies. Am J Cardiol. 2017 Jul 1;120(1s):S4-s16. doi: 10.1016/j.amjcard.2017.05.009. PMID 28606343.

Bisht R, Linked SG. Cotransporter 2 inhibitor: A new horizon in the treatment of Type-2 diabetes. Asian J Pharm Clin Res. 2021 Jul 03;14(3):45-8. doi: 10.22159/ajpcr.2021.v14i3.39667.

Chinsembu KC. Diabetes mellitus and nature’s pharmacy of putative antidiabetic plants. J Herb Med. 2019 Mar 01;15. doi: 10.1016/j.hermed.2018.09.001, PMID 100230.

Uppal S, Italiya KS, Chitkara D, Mittal A. Nanoparticulate-based drug delivery systems for small molecule anti-diabetic drugs: an emerging paradigm for effective therapy. Acta Biomater. 2018 Nov 01;81:20-42. doi: 10.1016/j.actbio.2018.09.049. PMID 30268916.

Han HS, Kang G, Kim JS, Choi BH, Koo SH. Regulation of glucose metabolism from a liver-centric perspective. Exp Mol Med. 2016 Mar 01;48(3):e218. doi: 10.1038/emm.2015.122, PMID 26964834.

Gupta M, Sharma R, Kumar A. Docking techniques in pharmacology: how much promising? Comput Biol Chem. 2018 Oct 03;76:210-7. doi: 10.1016/j.compbiolchem.2018.06.005. PMID 30067954.

Perozzo R, Kuo M, Sidhu Ab, Valiyaveettil JT, Bittman R, Jacobs WR, Jr., Fidock DA, Sacchettini JC. Structural elucidation of the specificity of the antibacterial agent triclosan for malarial enoyl acyl carrier protein reductase. J Biol Chem. 2002 Apr 12;277(15):13106-14. doi: 10.1074/jbc.M112000200. PMID 11792710.

Asojo OA, Gulnik SV, Afonina E, Yu B, Ellman JA, Haque TS, Silva AM. Novel uncomplexed and complexed structures of plasmepsin II, an aspartic protease from Plasmodium falciparum. J Mol Biol. 2003 Mar 14;327(1):173-81. doi: 10.1016/s0022-2836(03)00036-6, PMID 12614616.

Morris GM, Huey R, Olson AJ. Using AutoDock for ligand-receptor docking. Curr Protoc Bioinformatics. 2008;8:8-14. doi: 10.1002/0471250953.bi0814s24. PMID 19085980.

Parthasarathy S, Eaazhisai K, Balaram H, Balaram P, Murthy MR. Structure of Plasmodium falciparum triose-phosphate isomerase-2-phosphoglycerate complex at 1.1-A resolution. J Biol Chem. 2003 Dec 26;278(52):52461-70. doi: 10.1074/jbc.M308525200. PMID 14563846.

Langer T, Hoffmann RD. Pharmacophore modelling: applications in drug discovery. Expert Opin Drug Discov. 2006 Aug 17;1(3):261-7. doi: 10.1517/17460441.1.3.261, PMID 23495846.

Herat LY, Matthews J, Azzam O, Schlaich MP, Matthews VB. Targeting features of the metabolic syndrome through sympatholytic effects of SGLT2 inhibition. Curr Hypertens Rep. 2022 Mar;24(3):67-74. doi: 10.1007/s11906-022-01170-z, PMID 35235172.

Shao C, Westbrook JD, Lu C, Bhikadiya C, Peisach E, Young JY, Duarte JM, Lowe R, Wang S, Rose Y, Feng Z, Burley SK. Simplified quality assessment for small-molecule ligands in the protein data bank. Structure. 2022 Feb 3;30(2):252-62.e4. doi: 10.1016/j.str.2021.10.003, PMID 35026162.

Niu Y, Liu R, Guan C, Zhang Y, Chen Z, Hoerer S, Nar H, Chen L. Structural basis of inhibition of the human SGLT2-MAP17 glucose transporter. Nature. 2022 Jan 21;601(7892):280-4. doi: 10.1038/s41586-021-04212-9, PMID 34880493.

Chadeve A. A review on pharmacology and therapeutic effects of empagliflozin in patients with type 2 diabetes mellitus. Asian J Pharm Clin Res 2020;13:16-21. doi: 10.22159/ajpcr.2020.v13i5.36838.

Ashoush N. Review on pharmacokinetics of empagliflozin, an inhibitor of the sodium-glucose co-transporter-2 (SGLT-2). Asian J Pharm Clin Res 2017;10(7). doi: 10.22159/ajpcr.2017.v10i7.18067.

Bissantz C, Kuhn B, Stahl M. A medicinal chemist’s guide to molecular interactions. J Med Chem. 2010 Jul 22;53(14):5061-84. doi: 10.1021/jm100112j, PMID 20345171.

Djajadisastra J, Purnama HD, Yanuar A. In silico binding interaction study of mefenamic acid and piroxicam on human albumin. Int J App Pharm 2017;9:56-62. doi: 10.22159/ijap.2017.v9s1.56_62.

Nair AS, Bagchi D, Lehmann TE, Nair S. Chapter 16. Renal sodium-glucose Transporter-2 inhibitors as antidiabetic agents. In: Bagchi D, Nair S. editors. Nutritional and therapeutic interventions for diabetes and metabolic syndrome. 2nd ed. Academic Press; 2018. p. 207-14.

Cournia Z, Allen B, Sherman W. Relative binding free energy calculations in drug discovery: recent advances and practical considerations. J Chem Inf Model. 2017 Dec 26;57(12):2911-37. doi: 10.1021/acs.jcim.7b00564. PMID 29243483.

Luo H, Fokoue Nkoutche A, Singh N, Yang L, Hu J, Zhang P. Molecular docking for prediction and interpretation of adverse drug reactions. Comb Chem High Throughput Screen. 2018;21(5):314-22. doi: 10.2174/1386207321666180524110013, PMID 29792141.

Luo H, Fokoue Nkoutche A, Singh N, Yang L, Hu J, Zhang P. Molecular docking for prediction and interpretation of adverse drug reactions. Comb Chem High Throughput Screen. 2018 May 25;21(5):314-22. doi: 10.2174/ 1386207321666180524110013, PMID 29792141.

Muchtaridi M, Syahidah HN, Subarnas A, Yusuf M, Bryant SD, Langer T. Molecular docking and 3D-pharmacophore modeling to study the interactions of Chalcone derivatives with estrogen receptor alpha. Pharmaceuticals (Basel). 2017 Oct 16;10(4). doi: 10.3390/ph10040081, PMID 29035298.

Bommu UD, Konidala KK, Pabbaraju N, Yeguvapalli S. Ligand-based virtual screening, molecular docking, QSAR and pharmacophore analysis of quercetin-associated potential novel analogs against epidermal growth factor receptor. J Recept Signal Transduct Res. 2017 Dec 03;37(6):600-10. doi: 10.1080/10799893.2017.1377237, PMID 28958213.

CS, SDK, Ragunathan V, Tiwari P, AS, PBD. Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease. J Biomol Struct Dyn. 2022 Sep 08;40(2):585-611. doi: 10.1080/07391102.2020.1815584, PMID 32897178.

Lv PC, Li HQ, Xue JY, Shi L, Zhu HL. Synthesis and biological evaluation of novel luteolin derivatives as antibacterial agents. Eur J Med Chem. 2009 Feb 25;44(2):908-14. doi: 10.1016/j.ejmech.2008.01.013. PMID 18313801.

Mladenovic M, Matic S, Stanic S, Solujic S, Mihailovic V, Stankovic N. Combining molecular docking and 3-D pharmacophore generation to enclose the in vivo antigenotoxic activity of naturally occurring aromatic compounds: myricetin, quercetin, rutin, and rosmarinic acid. Biochem Pharmacol. 2013 Nov 01;86(9):1376-96. doi: 10.1016/j.bcp.2013.08.018, PMID 23973524.

Ravichandran S, Singh N, Donnelly D, Migliore M, Johnson P, Fishwick C, Luke BT, Martin B, Maudsley S, Fugmann SD, Moaddel R. Pharmacophore model of the quercetin binding site of the SIRT6 protein. J Mol Graph Model. 2014;49:38-46. doi: 10.1016/j.jmgm.2014.01.004. PMID 24491483.

Takasawa R, Tao A, Saeki K, Shionozaki N, Tanaka R, Uchiro H, Takahashi S, Yoshimori A, Tanuma S. Discovery of a new type inhibitor of human glyoxalase I by myricetin-based 4-point pharmacophore. Bioorg Med Chem Lett. 2011 Jul 15;21(14):4337-42. doi: 10.1016/j.bmcl.2011.05.046. PMID 21669529.

Seeliger D, de Groot BL. Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aid Mol Des. 2010 May 20;24(5):417-22. doi: 10.1007/s10822-010-9352-6, PMID 20401516.

Shityakov S, Forster C. In silico structure-based screening of versatile P-glycoprotein inhibitors using polynomial empirical scoring functions. Adv Appl Bioinform Chem. 2014 Jan 17;7:1-9. doi: 10.2147/AABC.S56046. PMID 24711707.

Morozov AV, Kortemme T. Potential functions for hydrogen bonds in protein structure prediction and design. Adv Protein Chem. 2005 Apr 04;72:1-38. doi: 10.1016/S0065-3233(05)72001-5, PMID 16581371.

Matta CF, Hernandez Trujillo J, Tang TH, Bader RFW. Hydrogen–hydrogen bonding: A stabilizing interaction in molecules and crystals. Chemistry. 2003 Feb 02;9(9):1940-51. doi: 10.1002/chem.200204626, PMID 12740840.

Kumar S, Khatik GL, Mittal A. In silico molecular docking study to search new SGLT2 inhibitor based on dioxabicyclo[3.2.1] octane scaffold. Curr Comput Aided Drug Des. 2020 Oct 23;16(2):145-54. doi: 10.2174/ 1573409914666181019165821, PMID 30345926.