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Medicinal Chemistry

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ISSN (Print): 1573-4064
ISSN (Online): 1875-6638

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Research Article

Ligand-Based and Structure-Based Virtual Screening of New Sodium Glucose Cotransporter Type 2 Inhibitors

Author(s): Ana Karen Estrada, Domingo Mendez-Alvarez, Alfredo Juarez-Saldivar, Edgar E. Lara-Ramirez, Ana Veronica Martinez-Vazquez, Juan Carlos Villalobos-Rocha, Isidro Palos, Eyra Ortiz-Perez and Gildardo Rivera*

Volume 19, Issue 10, 2023

Published on: 09 August, 2023

Page: [1049 - 1060] Pages: 12

DOI: 10.2174/1573406419666230803122020

Price: $65

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Abstract

Background: Diabetes mellitus is a metabolic disease that causes multiple complications and common comorbidities, which decreases the quality of life for people affected by the disease. Sodium glucose cotransporter type 2 (SGLT2) participates in the reabsorption of 90% of glucose in the kidneys; therefore, it is an attractive drug target for controlling blood glucose levels.

Objective: The aim in this work was to obtain new potential SGLT2 inhibitors.

Methods: A ligand-based virtual screening (LBVS) from the ZINC15, PubChem and ChemSpider databases using the maximum common substructure (MCS) scaffold was performed.

Result: A total of 341 compounds were obtained and analyzed by molecular docking on the active site of SGLT2. Subsequently, 15 compounds were selected for molecular dynamics (MD) simulation analysis. The compounds derived of spiroketal Sa1, Sa4, and Sa9 (≤ 3.5 Å) in complex with the receptor SGLT2 showed good stability during 120 ns of MD.

Conclusion: These compounds are proposed as potential SGLT2 inhibitors.

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[1]
Artasensi, A.; Pedretti, A.; Vistoli, G.; Fumagalli, L. Type 2 diabetes mellitus: A review of multi-target drugs. Molecules, 2020, 25(8), 1987.
[http://dx.doi.org/10.3390/molecules25081987] [PMID: 32340373]
[2]
FID. International diabetes federation., https://www.idf.org/news/169:diabetes-atlas-reports-463-million-with-diabetes.html
[3]
Reed, J.; Bain, S.; Kanamarlapudi, V. A review of current trends with type 2 diabetes epidemiology, aetiology, pathogenesis, treatments and future perspectives. Diabetes Metab. Syndr. Obes., 2021, 14, 3567-3602.
[http://dx.doi.org/10.2147/DMSO.S319895] [PMID: 34413662]
[4]
Łukasiewicz, A.; Cichoń, E.; Kostecka, B.; Kiejna, A.; Jodko- Modlińska, A.; Obrębski, M.; Kokoszka, A. Association of higher rates of type 2 diabetes (T2DM) complications with psychological and demographic variables: Results of a cross-sectional study. Diabetes Metab. Syndr. Obes., 2022, 15, 3303-3317.
[http://dx.doi.org/10.2147/DMSO.S369809] [PMID: 36329807]
[5]
Goyal, R.; Jialal, I. Diabetes Mellitus Type 2; StatPearls: Treasure Island, FL, 2022.
[6]
Chaudhury, A.; Duvoor, C.; Reddy Dendi, V.S.; Kraleti, S.; Chada, A.; Ravilla, R.; Marco, A.; Shekhawat, N.S.; Montales, M.T.; Kuriakose, K.; Sasapu, A.; Beebe, A.; Patil, N.; Musham, C.K.; Lohani, G.P.; Mirza, W. Clinical review of antidiabetic drugs: Implications for type 2 diabetes mellitus management. Front. Endocrinol., 2017, 8, 6.
[http://dx.doi.org/10.3389/fendo.2017.00006] [PMID: 28167928]
[7]
López-Hernández, M.A. Inhibidores del cotransportador de sodio y glucosa tipo 2 (SGLT2), el riñón como objetivo en el control glucémico de la diabetes mellitus tipo 2. Med. Interna Mex, 2017, 33(3), 363-371.
[8]
Shakil, S. Molecular interaction of anti-diabetic drugs with acetylcholinesterase and sodium glucose co-transporter 2. J. Cell. Biochem., 2017, 118(11), 3855-3865.
[http://dx.doi.org/10.1002/jcb.26036] [PMID: 28387957]
[9]
Poulsen, S.B.; Fenton, R.A.; Rieg, T. Sodium-glucose cotransport. Curr. Opin. Nephrol. Hypertens., 2015, 24(5), 463-469.
[http://dx.doi.org/10.1097/MNH.0000000000000152] [PMID: 26125647]
[10]
Pereira-Moreira, R.; Muscelli, E. Effect of insulin on proximal tubules handling of glucose: A systematic review. J. Diabetes Res., 2020, 2020, 1-17.
[http://dx.doi.org/10.1155/2020/8492467] [PMID: 32377524]
[11]
Rahmoune, H.; Thompson, P.W.; Ward, J.M.; Smith, C.D.; Hong, G.; Brown, J. Glucose transporters in human renal proximal tubular cells isolated from the urine of patients with non-insulin-dependent diabetes. Diabetes, 2005, 54(12), 3427-3434.
[http://dx.doi.org/10.2337/diabetes.54.12.3427] [PMID: 16306358]
[12]
Padda, I.S.; Mahtani, A.U.; Parmar, M. Sodium-Glucose Transport Protein 2 (SGLT2); Inhibitors. StatPearls: Treasure Island, FL, 2022.
[13]
DeFronzo, R.A.; Norton, L.; Abdul-Ghani, M. Renal, metabolic and cardiovascular considerations of SGLT2 inhibition. Nat. Rev. Nephrol., 2017, 13(1), 11-26.
[http://dx.doi.org/10.1038/nrneph.2016.170] [PMID: 27941935]
[14]
Gerich, J.E. Role of the kidney in normal glucose homeostasis and in the hyperglycaemia of diabetes mellitus: Therapeutic implications. Diabet. Med., 2010, 27(2), 136-142.
[http://dx.doi.org/10.1111/j.1464-5491.2009.02894.x] [PMID: 20546255]
[15]
Lim, V.G.; Bell, R.M.; Arjun, S.; Kolatsi-Joannou, M.; Long, D.A.; Yellon, D.M. SGLT2 inhibitor, canagliflozin, attenuates myocardial infarction in the diabetic and nondiabetic heart. JACC Basic Transl. Sci., 2019, 4(1), 15-26.
[http://dx.doi.org/10.1016/j.jacbts.2018.10.002] [PMID: 30847415]
[16]
Tsai, K.F.; Chen, Y.L.; Chiou, T.T.Y.; Chu, T.H.; Li, L.C.; Ng, H.Y.; Lee, W.C.; Lee, C.T. Emergence of SGLT2 inhibitors as powerful antioxidants in human diseases. Antioxidants, 2021, 10(8), 1166.
[http://dx.doi.org/10.3390/antiox10081166] [PMID: 34439414]
[17]
Chawla, G.; Chaudhary, K.K. A complete review of empagliflozin: Most specific and potent SGLT2 inhibitor used for the treatment of type 2 diabetes mellitus. Diabetes Metab. Syndr., 2019, 13(3), 2001-2008.
[http://dx.doi.org/10.1016/j.dsx.2019.04.035] [PMID: 31235127]
[18]
Dong, L.; Feng, R.; Bi, J.; Shen, S.; Lu, H.; Zhang, J. Insight into the interaction mechanism of human SGLT2 with its inhibitors: 3D-QSAR studies, homology modeling, and molecular docking and molecular dynamics simulations. J. Mol. Model., 2018, 24(4), 86.
[http://dx.doi.org/10.1007/s00894-018-3582-2] [PMID: 29511885]
[19]
Feng, R.; Dong, L.; Wang, L.; Xu, Y.; Lu, H.; Zhang, J. Development of sodium glucose co-transporter 2 (SGLT2) inhibitors with novel structure by molecular docking and dynamics simulation. J. Mol. Model., 2019, 25(6), 175.
[http://dx.doi.org/10.1007/s00894-019-4067-7] [PMID: 31154518]
[20]
Bhattacharya, S.; Asati, V.; Mishra, M.; Das, R.; Kashaw, V.; Kashaw, S.K. Integrated computational approach on sodium-glucose co-transporter 2 (SGLT2) Inhibitors for the development of novel antidiabetic agents. J. Mol. Struct., 2021, 1227, 129511.
[http://dx.doi.org/10.1016/j.molstruc.2020.129511]
[21]
Bhattacharya, D.; Nowotny, J.; Cao, R.; Cheng, J. 3Drefine: An interactive web server for efficient protein structure refinement. Nucleic Acids Res., 2016, 44(W1), W406-W409.
[http://dx.doi.org/10.1093/nar/gkw336] [PMID: 27131371]
[22]
DeLano, W.L. An open-source molecular graphics tool. CCP4 Newsl Protein Crystallogr., 2002, 40(1), 82-92.
[23]
a) Kunzmann, P.; Hamacher, K. Biotite: A unifying open source computational biology framework in Python. BMC Bioinformatics, 2018, 19(1), 346.
[http://dx.doi.org/10.1186/s12859-018-2367-z] [PMID: 30285630];
b) Pettersen, E.F.; Goddard, T.D.; Huang, C.C.; Couch, G.S.; Greenblatt, D.M.; Meng, E.C.; Ferrin, T.E. UCSF Chimera?A visualization system for exploratory research and analysis. J. Comput. Chem., 2004, 25(13), 1605-1612.
[http://dx.doi.org/10.1002/jcc.20084] [PMID: 15264254]
[24]
Liu, T.; Lin, Y.; Wen, X.; Jorissen, R.N.; Gilson, M.K.; Binding, D.B. A web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res., 2007, 35(1), D198-D201.
[http://dx.doi.org/10.1093/nar/gkl999] [PMID: 17145705]
[25]
O’Boyle, N.M.; Banck, M.; James, C.A.; Morley, C.; Vandermeersch, T.; Hutchison, G.R. Open Babel: An open chemical toolbox. J. Cheminform., 2011, 3(1), 33.
[26]
Adasme, M.F.; Linnemann, K.L.; Bolz, S.N.; Kaiser, F.; Salentin, S.; Haupt, V.J.; Schroeder, V.M. PLIP 2021: Expanding the scope of the protein–ligand interaction profiler to DNA and RNA. Nucleic Acids Res., 2021, 49(W1), W530-W4.
[PMID: 33950214]
[27]
RDKit. RDKit. RDKit: Open-Source Cheminformatics Software. 2018. Available from: https://www.rdkit.org/
[28]
Banerjee, P.; Eckert, A.O.; Schrey, A.K.; Preissner, R. ProTox-II: A webserver for the prediction of toxicity of chemicals. Nucleic Acids Res., 2018, 46(W1), W257-W63.
[29]
Abraham, M.J.; Murtola, T.; Schulz, R.; Páll, S.; Smith, J.C.; Hess, B.; Lindahl, E. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 2015, 1-2, 19-25.
[http://dx.doi.org/10.1016/j.softx.2015.06.001]
[30]
Lemkul, J. From proteins to perturbed Hamiltonians: A suite of tutorials for the GROMACS-2018 molecular simulation package. LiveCoMS., 2018, 1(1), 5068. [article v1. 0
[31]
Da Silva, A.W.S.; Vranken, W.F. ACPYPE-Antechamber python parser interface. BMC Res. Notes, 2012, 5(1), 1-8.
[32]
Kumari, R.; Kumar, R.; Lynn, A.; Lynn, A. g_mmpbsa: A GROMACS tool for high-throughput MM-PBSA calculations. J. Chem. Inf. Model., 2014, 54(7), 1951-1962.
[http://dx.doi.org/10.1021/ci500020m] [PMID: 24850022]
[33]
Ng, W.L.; Li, H.C.; Lau, K.M.; Chan, A.K.N.; Lau, C.B.S.; Shing, T.K.M. Concise and stereodivergent synthesis of carbasugars reveals unexpected structure-activity relationship (SAR) of SGLT2 inhibition. Sci. Rep., 2017, 7(1), 5581.
[http://dx.doi.org/10.1038/s41598-017-05895-9] [PMID: 28717146]
[34]
Ng, W.L.; Shing, T.K.M. Synthetic and biological studies of carbasugar SGLT2 inhibitors. J. Synth. Org. Chem. Jpn., 2018, 76(11), 1215-1222.
[http://dx.doi.org/10.5059/yukigoseikyokaishi.76.1215]
[35]
Salentin, S.; Haupt, V.J.; Daminelli, S.; Schroeder, M. Polypharmacology rescored: Protein–ligand interaction profiles for remote binding site similarity assessment. Prog. Biophys. Mol. Biol., 2014, 116(2-3), 174-186.
[http://dx.doi.org/10.1016/j.pbiomolbio.2014.05.006] [PMID: 24923864]
[36]
Pearce, R.; Zhang, Y. Toward the solution of the protein structure prediction problem. J. Biol. Chem., 2021, 297(1), 100870.
[http://dx.doi.org/10.1016/j.jbc.2021.100870] [PMID: 34119522]
[37]
Victoria-Muñoz, F.; Sánchez-Cruz, N.; Medina-Franco, J.L.; Lopez-Vallejo, F. Cheminformatics analysis of molecular datasets of transcription factors associated with quorum sensing in Pseudomonas aeruginosa. RSC Advances, 2022, 12(11), 6783-6790.
[http://dx.doi.org/10.1039/D1RA08352J] [PMID: 35424595]
[38]
Ohtake, Y.; Emura, T.; Nishimoto, M.; Takano, K.; Yamamoto, K.; Tsuchiya, S.; Yeu, S.Y.; Kito, Y.; Kimura, N.; Takeda, S.; Tsukazaki, M.; Murakata, M.; Sato, T. Development of a scalable synthesis of tofogliflozin. J. Org. Chem., 2016, 81(5), 2148-2153.
[http://dx.doi.org/10.1021/acs.joc.5b02734] [PMID: 26871504]
[39]
Suzuki, M.; Takeda, M.; Kito, A.; Fukazawa, M.; Yata, T.; Yamamoto, M.; Nagata, T.; Fukuzawa, T.; Yamane, M.; Honda, K.; Suzuki, Y.; Kawabe, Y. Tofogliflozin, a sodium/glucose cotransporter 2 inhibitor, attenuates body weight gain and fat accumulation in diabetic and obese animal models. Nutr. Diabetes, 2014, 4(7), e125.
[http://dx.doi.org/10.1038/nutd.2014.20] [PMID: 25000147]
[40]
Kuwahara, K.S.U. Effect of tofogliflozin on uacr compared to metformin hydrochloride in diabetic kidney disease (TRUTHDKD) (TRUTH-DKD). Available from: https://clinicaltrials.gov/ct2/show/NCT05469659 (Access May 05, 2023)

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