Abstract
A novel class of therapeutic agents, the sodium-glucose co-transporter 2 (SGLT2) inhibitors, is emerging as a promising avenue for type 2 diabetes management. A dataset comprising 1807 SGLT2 inhibitors was subjected to a quantitative structure-activity relationship (QSAR) investigation using the AutoQSAR module of Schrodinger Maestro 12.8. Of these compounds, 1355 were designated as the training set for model development, followed by comprehensive evaluation through a battery of internal and external cross-validation techniques. Subsequently, a subset of 452 compounds served as an independent test set for external validation. The resultant QSAR model exhibited promising statistical performance, as evidenced by the calculated predicted R2 and Q2 values, at 0.873 and 0.781, respectively. Furthermore, the predictive correlation coefficient attained a commendable value of 0.84. Notably, this model demonstrates its efficacy in forecasting inhibitory activity and furnishes valuable insights that can be harnessed for the design of novel SGLT2 inhibitors in future endeavors.
REFERENCES
Saini, K., Sharma, S., and Khan, Y., DPP-4 inhibitors for treating T2DM–hype or hope? An analysis based on the current literature, Front. Mol. Biosci., 2023, vol. 10, pp. 1–19. https://doi.org/10.3389/fmolb.2023.1130625
Manu, Type 2 Diabetes Mellitus. https://commons.wikimedia.org/wiki/File:Type_2_Diabetes_Mellitus.jpg. Cited January 27, 2024.
Alzahrani, A.S., Price, M.J., Greenfield, S.M., and Paudyal, V., Global prevalence and types of complementary and alternative medicines use amongst adults with diabetes : Systematic review and meta-analysis, Eur. J. Clin. Pharmacol., 2021, vol. 77, pp. 1259–1274. https://doi.org/10.1007/s00228-021-03097-x
Khan, M.A.B., Hashim, M.J., King, J.K., Govender, R.D., Mustafa, H., and Al Kaabi, J., Epidemiology of type 2 diabetes–global burden of disease and forecasted trends, J. Epidemiol. Global Health, 2020, vol. 10, no. 1, pp. 107–111. https://doi.org/10.2991/jegh.k.191028.001
Davegårdh, C., Säll, J., Benrick, A., Broholm, C., Volkov, P., Perfilyev, A., Henriksen, T.I., Wu, Y., Hjort, L., Brøns, C., Hansson, O., Pedersen, M., Würthner, J.U., Pfeffer, K., Nilsson, E., Vaag, A., Stener-Victorin, E., Pircs, K., Scheele, C., and Ling, C., VPS39-deficiency observed in type 2 diabetes impairs muscle stem cell differentiation via altered autophagy and epigenetics, Nat. Commun., 2021, vol. 12, no. 1, article no. 2431, pp. 1–20. https://doi.org/10.1038/s41467-021-22068-5
Shirai, Y., Imai, T., Sezaki, A., Miyamoto, K., Kawase, F., Abe, C., Sanada, M., Inden, A., Kato, T., Suzuki, N., and Shimokata, H., Trends in age-standardised prevalence of type 2 diabetes mellitus according to country from 1990 to 2017 and their association with socioeconomic, lifestyle and health indicators: An ecological study, J. Global Health, 2021, vol. 11, pp. 1–7. https://doi.org/10.7189/jogh.11.04005
Zhou B., et al., Worldwide trends in diabetes since 1980: A pooled analysis of 751 population-based studies with 4.4 million participants, Lancet, 2016, vol. 387, pp. 1513–1530. https://doi.org/10.1016/S0140-6736(16)00618-8
Wilkens, W.S., Prevalence of Diabetes by Percent of Country Population (2014) Gradient Map. https://commons.wikimedia.org/wiki/File:Prevalence_ of_Diabetes_by_Percent_of_Country_Populat ion_ (2014)_Gradient_Map.png, 2014. Cited January 27, 2024.
Saini, K., Sharma, S., Bhatia, V., Khan, Y., and Etters, L., Dietary polyphenolics : Mechanistic role in control management of diabetes and metabolic syndrome, Chem. Biol. Lett., 2023, vol. 10, no. 3, pp. 1–16.
Saini, K. and Sharma, S., Use of tyrosine kinase inhibitors for treating type 2 diabetes mellitus: An appraisal, Chem. Biol. Lett., 2022, vol. 9, no. 3, pp. 1–12. https://pubs.thesciencein.org/cbl. Cited January 27, 2024. https://www.elibrary.ru/item.asp?id=48989682. Cited January 27, 2024.
Belete, T.M., A recent achievement in the discovery and development of novel targets for the treatment of type-2 diabetes mellitus, J. Exp. Pharmacol., 2020, vol. 12, pp. 1–15. https://doi.org/10.2147/JEP.S226113
Brown, S.A., Kovatchev, B.P., Raghinaru, D., Lurn, K.W., Buckingham, B.A., Kudva, Y.C., Laffel, L.M., Levy, C.J., Pinsker, J.E., Wadwa, R.P., Dassau, E., Doyle III, F.J., Anderson, S.M., Church, M.M., Dadlani, V., Ekhlaspour, L., Forlenza, G.P., Isganaitis, E., Lam, D.W., Kollman, C., and Beck, R.W., Six-month randomized, multicenter trial of closed-loop control in type 1 diabetes, N. Engl. J. Med., 2019, vol. 381, no. 18, pp. 1707–1717.https://doi.org/10.1056/nejmoa1907863
Petrelli, F.,Cangelosi, G., Scuri, S., Pantanetti, P., Lavorgna, F., Faldetta, F., De Carolis, C., Rocchi, R., Debernardi, G., Florescu, A., Nittari, G., Sagaro, G.G., Garda, G., Nguyen, C.T.T., and Grappasonni, I., Diabetes and technology: A pilot study on the management of patients with insulin pumps during the COVID-19 pandemic, Diabetes Res. Clin. Pract., 2020, vol. 169, article no. 108481, pp. 1–7. https://doi.org/10.1016/j.diabres.2020.108481
Morrato, E.H., Hill, J.O., Wyatt, H.R., Ghushchyan, V., and Sullivan, P.W., Physical activity in U.S. adults with diabetes and at risk for developing diabetes, 2003, Diabetes Care, 2007, vol. 30, no. 2, pp. 203–209. https://doi.org/10.2337/dc06-1128
Mishra, V., Nayak, P., Sharma, M., Albutti, A., Alwashmi, A.S.S., Aljasir, M.A., Alsowayeh, N., and Tambuwala, M.M., Emerging treatment strategies for diabetes mellitus and associated complications: An update, Pharmaceutics, 2021, vol. 13, no. 10, article no. 1568, pp. 1–33. https://doi.org/10.3390/pharmaceutics13101568
Saini, K., Khan, Y., and Sharma, S., How effective are gliflozins as DPP-4 inhibitors? A computational study, Theor. Found. Chem. Eng., 2023, vol. 57, no. 3, pp. 403–410. https://doi.org/10.1134/S0040579523030168
Dong, L., Feng, R., Bi, J., Shen, S., Lu, H., and 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, vol. 24, no. 4, article no. 86, pp. 1–16. https://doi.org/10.1007/s00894-018-3582-2
Neves, B.J., Braga, R.C., Melo-Filho, C.C., Moreira-Filho, J.T., Muratov, E.N., and Andrade, C.H., QSAR-based virtual screening: Advances and applications in drug discovery, Front. Pharmacol., 2018, vol. 9, article no. 1275, pp. 1–7, https://doi.org/10.3389/fphar.2018.01275
Roy K. and Mitra, I., On various metrics used for validation of predictive QSAR models with applications in virtual screening and focused library design, Comb. Chem. High Throughput Screening, 2011, vol. 14, no. 6, pp. 450–474. https://doi.org/10.2174/138620711795767893
Sharma S. and Bhatia, V., Recent trends in QSAR in modelling of drug–protein and protein–protein interactions, Comb. Chem. High Throughput Screening, 2020, vol. 24, no. 7, pp. 1031–1041. https://doi.org/10.2174/1386207323666201209093537
Arba, M., Ruslin, Kalsum, W.U., Alroem, A., Muzakkar, M.Z., Usman, I., and Tjahjono, D.H., QSAR, molecular docking and dynamics studies of quinazoline derivatives as inhibitor of phosphatidylinositol 3-kinase, J. Appl. Pharm. Sci., 2018, vol. 8, no. 5, pp. 1–9. https://doi.org/10.7324/JAPS.2018.8501
Karaman Mayack, B., Alayoubi, M.M., and Gezginci, M.H., Fingerprint-based QSAR model generation to identify structural determinants of HCV NS5B inhibition, J. Res. Pharm., 2023, vol. 27, no. 4, pp. 1421–1430. https://doi.org/10.29228/jrp.429
Deokar, H., Deokar, M., Wang, W., Zhang, R., and Buolamwini, J.K., QSAR studies of new pyrido[3,4-b]indole derivatives as inhibitors of colon and pancreatic cancer cell proliferation, Med. Chem. Res., 2018, vol. 27, no. 11, pp. 2466–2481. https://doi.org/10.1007/s00044-018-2250-5
Funding
This work was supported by ongoing institutional funding. No additional grants to carry out or direct this particular research were obtained.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
The authors of this work declare that they have no conflicts of interest.
Additional information
Publisher’s Note.
Pleiades Publishing remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Kunika Saini, Smriti Sharma QSAR Studies of Sodium/Glucose Co-Transporter 2 Inhibitors as Potent Anti-Diabetic Drug Agents. Theor Found Chem Eng 57 (Suppl 1), S51–S56 (2023). https://doi.org/10.1134/S004057952307014X
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S004057952307014X