3D-QSAR-Based Pharmacophore Determination and Design of Novel DPP-4 Inhibitors

  • Sanja Rogić Regulatory, Medical and Clinical Affairs, Hemofarm d.o.o. Banja Luka, Banja Luka, Bosnia and Herzegovina
  • Žarko Gagić
DOI: https://doi.org/10.5937/scriptamed53-40866
Keywords: Diabetes, Gliptins, Quantitative structure-activity relationship, Pharmacophore, Molecular design

Abstract


Background/Aim: Therapy of diabetes mellitus type 2 includes drugs that act as inhibitors of dipeptidyl peptidase 4 (DPP-4) enzyme. Several DPP-4 inhibitors are marketed today and although they have favourable safety profile and tolerability, they show moderate activity in controlling glycaemia. The 3D quantitative structure-activity relationship (3D-QSAR) methodology was employed in order to find pharmacophore responsible for good DPP-4 inhibitory activity and designed new compounds with enhanced activity.

Methods: For 3D-QSAR model development, 48 compounds structurally related to sitagliptin were collected from ChEMBL database. Structures of all compounds were optimised in order to find the best 3D conformations prior to QSAR modelling. To establish correlation between structure and biological activity Partial Least Squares (PLS) regression method integrated in Pentacle software was used.

Results: Parameters of internal and external validation (R2 = 0.80, Q2 = 0.64 and R2pred = 0.610) confirmed reliability of developed QSAR model. Analysis of obtained structural descriptors enabled identification of key structural characteristics that influenced DPP-4 inhibitory activity. Based on that information, new compounds were designed, of which 35 compounds had a better predicted activity, compared to sitagliptin.

Conclusion: This QSAR model can be used for DPP-4 inhibitory activity prediction of structurally related compounds and resulting pharmacophore contains information useful for optimisation and design of new DPP-4 inhibitors. Finally, authors propose designed compounds for further synthesis, in vitro and in vivo testing, as new potential DPP-4 inhibitors.

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1.   1. DeFronzo RA, Ferrannini E, Groop L, Henry RR, Herman WH, Holst JJ, et al. Type 2 diabetes mellitus. Nat Rev Dis Primers 2015;1:15019. doi: 10.1038/nrdp.2015.19.

2.     Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9(th) edition. Diabetes Res Clin Pract 2019;157:107843. doi: 10.1016/j.diabres.2019.107843.

3.     Ko SH, Hur KY, Rhee SY, Kim NH, Moon MK, Park SO, et al. Antihyperglycemic agent therapy for adult patients with type 2 diabetes mellitus 2017: a position statement of the Korean Diabetes Association. Korean J Intern Med 2017;32(6):947-58.

4.     Yin R, Xu Y, Wang X, Yang L, Zhao D. Role of dipeptidyl peptidase 4 inhibitors in antidiabetic treatment. Molecules 2022;27(10):3055. doi: 10.3390/molecules27103055.

5.     Ahren B. DPP-4 Inhibition and the path to clinical proof. Front Endocrinol 2019;10:376. doi: 10.3389/fendo.2019.00376.

6.     Fadini GP, Avogaro A. Cardiovascular effects of DPP-4 inhibition: beyond GLP-1. Vascul Pharmacol 2011;55(1-3):10-6.

7.     Tomovic K, Lazarevic J, Kocic G, Deljanin-Ilic M anderluh M, Smelcerovic A. Mechanisms and pathways of anti-inflammatory activity of DPP-4 inhibitors in cardiovascular and renal protection. Med Res Rev 2019;39(1):404-22.

8.     Kirino Y, Sato Y, Kamimoto T, Kawazoe K, Minakuchi K. Altered dipeptidyl peptidase-4 activity during the progression of hyperinsulinemic obesity and islet atrophy in spontaneously late-stage type 2 diabetic rats. Am J Physiol Endocrinol Metab 2011;300(2):E372-9.

9.     Shibasaki I, Nakajima T, Fukuda T, Hasegawa T, Ogawa H, Tsuchiya G, et al. Serum and adipose dipeptidyl peptidase 4 in cardiovascular surgery patients: influence of dipeptidyl peptidase 4 inhibitors. J Clin Med 2022;11(15):4333. doi: 10.3390/jcm11154333.

10.  Daza-Arnedo R, Rico-Fontalvo JE, Pajaro-Galvis N, Leal-Martinez V, Abuabara-Franco E, Raad-Sarabia M, et al. Dipeptidyl peptidase-4 inhibitors and diabetic kidney disease: a narrative review. Kidney Med 2021;3(6):1065-73.

11.  Makrilakis K. The role of DPP-4 Inhibitors in the treatment algorithm of type 2 diabetes mellitus: when to select, what to expect. Int J Environ Res Public Health 2019;16(15):2720. doi: 10.3390/ijerph16152720.

12.  Nauck MA, Meier JJ. The incretin effect in healthy individuals and those with type 2 diabetes: physiology, pathophysiology and response to therapeutic interventions. Lancet Diabetes Endocrinol 2016;4(6):525-36.

13.  Tan Q, Akindehin SE, Orsso CE, Waldner RC, DiMarchi RD, Muller TD, et al. Recent advances in incretin-based pharmacotherapies for the treatment of obesity and diabetes. Front Endocrinol 2022;13:838410. doi: 10.3389/fendo.2022.838410.

14.  Drucker DJ, Nauck MA. The incretin system: glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors in type 2 diabetes. The Lancet 2006;368(9548):1696-705.

15.  Davis JA, Kumar PS, Singh S, Surender A, Roy S, Khanna V, et al. Biological evaluation of RBx-0128, a potent and selective dipeptidyl peptidase-IV inhibitor in type 2 diabetes genetic model. Indian J Pharmacol 2012;44(6):759-64.

16.  Kalhotra P, Chittepu V, Osorio-Revilla G, Gallardo-Velazquez T. Structure-activity relationship and molecular docking of natural product library reveal chrysin as a novel dipeptidyl peptidase-4 (DPP-4) inhibitor: an integrated in silico and in vitro study. Molecules 2018;23(6):1368. doi: 10.3390/molecules23061368.

17.  Gao Y, Zhang Y, Zhu J, Li B, Li Z, Zhu W, et al. Recent progress in natural products as DPP-4 inhibitors. Future Med Chem 2015;7(8):1079-89.

18.  Rogic S, Nukic M, Gagic Z. Quantitative structure-activity relationship study of DPP-4 enzyme inhibitors as drugs in therapy of type 2 diabetes mellitus.  In: Badnjevic A, Gurbeta Pokvić L, editors. CMBEBIH 2021: IFMBE Proceedings; 2021 Apr 21-24; Mostar, Bosnia and Herzegovina. Cham: Springer; 2021. p. 481-8.

19.  Veselovsky AV, Ivanov AS. Strategy of computer-aided drug design. Curr Drug Targets Infect Disord 2003;3(1):33-40.

20.  Javed MR. CADD and molecular dynamic simulations: potential impacts to conventional medicines. Comb Chem High Throughput Screen 2022;25(4):658-9.

21.  Sabe VT, Ntombela T, Jhamba LA, Maguire GEM, Govender T, Naicker T, et al. Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review. Eur J Med Chem 2021;224:113705. doi: 10.1016/j.ejmech.2021.113705.

22.  Stewart JJP. Optimization of parameters for semiempirical methods I. Method. J Comput Chem 1989;10(2):209-20.

23.  Frisch M, Trucks G, Schlegel H, Scuseria G, Robb M, Cheeseman J, et al. Gaussian 98, revision a. 7, Gaussian. Inc, Pittsburgh, PA. 1998;12.

24.  Pastor M, Cruciani G, McLay I, Pickett S, Clementi S. GRid-INdependent descriptors (GRIND): a novel class of alignment-independent three-dimensional molecular descriptors. J Med Chem 2000;43(17):3233-43.

25.  Gramatica P. On the development and validation of QSAR models. Methods Mol Biol 2013;930:499-526.

26.  Tropsha A. Best practices for QSAR model development, validation and exploitation. Mol Inform 2010;29(6-7):476-88.

27.  Roy PP, Roy K. On some aspects of variable selection for partial least squares regression models. QSAR Comb Sci 2008;27(3):302-13.

28.  Ojha PK, Mitra I, Das RN, Roy K. Further exploring rm2 metrics for validation of QSPR models. Chemometr Intell Lab Syst 2011;107(1):194-205.

 

29.  Pratim Roy P, Paul S, Mitra I, Roy K. On two novel parameters for validation of predictive QSAR models. Molecules 2009;14(5):1660-701.

 

Published
2022/12/28
Issue
Vol. 53 No. 4 (2022): Q4/December
Section
Original article
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