Skip to main content
SpringerLink
Log in

Novel hydrazine derivatives as selective DPP-IV inhibitors: findings from virtual screening and validation through molecular dynamics simulations

  • Original Paper
  • Published:
Journal of Molecular Modeling Aims and scope Submit manuscript

Abstract

The present study demonstrates and validates the discovery of two novel hydrazine derivatives as selective dipeptidyl peptidase-IV (DPP-IV) inhibitors. Virtual screening (VS) of publicly available databases was performed using virtual screening workflow (VSW) of Schrödinger software against DPP-IV and the most promising hits were selected. Selectivity was further assessed by docking the hits against homology modeled structures of DPP8 and DPP9. Two novel hydrazine derivatives were selected for further studies based on their selectivity threshold. To assess their correct binding modes and stability of their complexes with enzyme, molecular dynamic (MD) simulation studies were performed against the DPP-IV protein and the results revealed that they had a better binding affinity towards DPP-IV as compared to DPP 8 and DPP 9. The binding poses were further validated by docking these ligands with different softwares (Glide and Gold). The proposed binding modes of hydrazines were found to be similar to sitagliptine and alogliptine. Thus, the study reveals the potential of hydrazine derivatives as highly selective DPP-IV inhibitors.

Structures of sitagliptine and the novel hydrazine identified by screening

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. http://www.who.int/mediacentre/factsheets/fs312/en/Accessed Accessed 22 February 2012.

  2. Kannel WB, McGee DL (1979) Diabetes and glucose tolerance as risk factors for cardiovascular disease: the Framingham study. Diabetes Care 2:120–126. doi:10.2337/diacare.2.2.120

    Article  CAS  Google Scholar 

  3. Krolewski AS, Kosinski EJ, Warram JH et al (1987) Magnitude and determinants of coronary artery disease in juvenile-onset, insulin-dependent diabetes mellitus. Am J Cardiol 59:750–755

    Article  CAS  Google Scholar 

  4. Mentlein R, Gallwitz B, Schmidt WE (1993) Dipeptidyl-peptidase IV hydrolyses gastric inhibitory polypeptide, glucagon-like peptide-1(7-36) amide, peptide histidine methionine and is responsible for their degradation in human serum. Eur J Biochem 214:829–835

    Article  CAS  Google Scholar 

  5. Drucker DJ (2001) Development of glucagon-like peptide-1-based pharmaceuticals as therapeutic agents for the treatment of diabetes. Curr Pharm Des 7:1399–1412

    Article  CAS  Google Scholar 

  6. Vilsbøll T, Holst JJ (2004) Incretins, insulin secretion and Type 2 diabetes mellitus. Diabetologia 47:357–366. doi:10.1007/s00125-004-1342-6

    Article  CAS  Google Scholar 

  7. D’Alessio DA, Vahl TP (2004) Glucagon-like peptide 1: evolution of an incretin into a treatment for diabetes. Am J Physiol Endocrinol Metab 286:882–890. doi:10.1152/ajpendo.00014.2004

    Article  Google Scholar 

  8. Knudsen LB (2004) Glucagon-like Peptide-1: the basis of a new class of treatment for type 2 diabetes. J Med Chem 47:4128–4134. doi:10.1021/jm030630m

    Article  CAS  Google Scholar 

  9. Holst JJ, Deacon CF (1998) Inhibition of the activity of dipeptidyl-peptidase IV as a treatment for type 2 diabetes. Diabetes 47:1663–1670

    Article  CAS  Google Scholar 

  10. Vilsboll T (2003) Similar elimination rates of glucagon-like peptide-1 in obese type 2 diabetic patients and healthy subjects. J Clin Endocrinol Metab 88:220–224. doi:10.1210/jc.2002-021053

    Article  CAS  Google Scholar 

  11. Ahrén B, Holst JJ, Mårtensson H, Balkan B (2000) Improved glucose tolerance and insulin secretion by inhibition of dipeptidyl peptidase IV in mice. Eur J Pharmacol 404:239–245

    Article  Google Scholar 

  12. Creutzfeldt W (1979) The incretin concept today. Diabetologia 16:75–85. doi:10.1007/BF01225454

    Article  CAS  Google Scholar 

  13. Drucker DJ (2003) Therapeutic potential of dipeptidyl peptidase IV inhibitors for the treatment of type 2 diabetes. Expert Opin Investig Drugs 12:87–100. doi:10.1517/13543784.12.1.87

    Article  CAS  Google Scholar 

  14. Deacon CF, Ahrén B, Holst JJ (2004) Inhibitors of dipeptidyl peptidase IV: a novel approach for the prevention and treatment of Type 2 diabetes? Expert Opin Investig Drugs 13:1091–1102. doi:10.1517/13543784.13.9.1091

    Article  CAS  Google Scholar 

  15. Green BD, Flatt PR, Bailey CJ (2006) Inhibition of dipeptidyl peptidase IV activity as a therapy of Type 2 diabetes. Expert Opin Investig Drugs 11:525–539. doi:10.1517/14728214.11.3.525

    Article  CAS  Google Scholar 

  16. Augustyns K, Bal G, Thonus G et al (1999) The unique properties of dipeptidyl-peptidase IV (DPP IV / CD26) and the therapeutic potential of DPP IV inhibitors. Curr Med Chem 6:311–327

    CAS  Google Scholar 

  17. Weber AE (2004) Dipeptidyl peptidase IV inhibitors for the treatment of diabetes. J Med Chem 47:4135–4141. doi:10.1021/jm030628v

    Article  CAS  Google Scholar 

  18. Kim D, Wang L, Beconi M et al (2005) (2R)-4-oxo-4-[3-(trifluoromethyl)-5,6-dihydro[1,2,4]triazolo[4,3-a]pyrazin-7(8H)-yl]-1-(2,4,5-trifluorophenyl)butan-2-amine: a potent, orally active dipeptidyl peptidase IV inhibitor for the treatment of type 2 diabetes. J Med Chem 48:141–151. doi:10.1021/jm0493156

    Article  CAS  Google Scholar 

  19. Deacon CF (2005) MK-431 (Merck). Curr Opin Investig Drugs 6:419–426

    CAS  Google Scholar 

  20. Villhauer EB, Brinkman JA, Naderi GB et al (2003) 1-[[(3-hydroxy-1-adamantyl)amino]acetyl]-2-cyano-(S)-pyrrolidine: a potent, selective, and orally bioavailable dipeptidyl peptidase IV inhibitor with antihyperglycemic properties. J Med Chem 46:2774–2789

    Google Scholar 

  21. Ahrén B (2006) Vildagliptin: an inhibitor of dipeptidyl peptidase-4 with antidiabetic properties. Expert Opin Investig Drugs 15:431–442

    Article  CAS  Google Scholar 

  22. Augeri DJ, Robl JA, Betebenner DA et al (2005) Discovery and preclinical profile of Saxagliptin (BMS-477118): a highly potent, long-acting, orally active dipeptidyl peptidase IV inhibitor for the treatment of type 2 diabetes. J Med Chem 48:5025–5037

    Article  CAS  Google Scholar 

  23. Simpkins LM, Bolton S, Pi Z et al (2007) Potent non-nitrile dipeptidic dipeptidyl peptidase IV inhibitors. Bioorg Med Chem Lett 17:6476–6480

    Article  CAS  Google Scholar 

  24. Feng J, Zhang Z, Wallace MB et al (2007) Discovery of alogliptin: a potent, selective, bioavailable, and efficacious inhibitor of dipeptidyl peptidase IV. J Med Chem 50:2297–2300

    Article  CAS  Google Scholar 

  25. Taskinen M-RM-R, Rosenstock J, Tamminen I et al (2011) Safety and efficacy of linagliptin as add-on therapy to metformin in patients with type 2 diabetes: a randomized, double-blind, placebo-controlled study. Diabetes Obes Metab 13:65–74. doi:10.1111/j.1463-1326.2010.01326.x

    Article  CAS  Google Scholar 

  26. Lotfy M, Singh J, Kalász H et al (2011) Medicinal chemistry and applications of incretins and dpp-4 inhibitors in the treatment of type 2 diabetes mellitus. Open Med Chem J 5:82–92. doi:10.2174/1874104501105010082

    Article  CAS  Google Scholar 

  27. http://www.ema.europa.eu/docs/en_GB/document_library/Press_release/2010/09/WC500096996.pdf. Accessed 3 March 3013

  28. http://www.cdsco.nic.in/html/drugsbanneded-Drugs Banned in India. Accessed 3 March 3013

  29. Elashoff M, Matveyenko AV, Gier B et al (2011) Pancreatitis, pancreatic, and thyroid cancer with glucagon-like peptide-1-based therapies. Gastroenterology 141:150–156

    Article  CAS  Google Scholar 

  30. Lankas GR, Leiting B, Roy RS et al (2005) Dipeptidyl peptidase IV inhibition for the treatment of type 2 diabetes: potential importance of selectivity over dipeptidyl peptidases 8 and 9. Diabetes 54:2988–2994

    Article  CAS  Google Scholar 

  31. Burkey BF, Hoffmann PK, Hassiepen U et al (2008) Adverse effects of dipeptidyl peptidases 8 and 9 inhibition in rodents revisited. Diabetes Obes Metab 10:1057–1061

    Article  CAS  Google Scholar 

  32. Wu J-J, Tang H-K, Yeh T-K et al (2009) Biochemistry, pharmacokinetics, and toxicology of a potent and selective DPP8/9 inhibitor. Biochem Pharmacol 78:203–210. doi:10.1016/j.bcp.2009.03.032

    Article  CAS  Google Scholar 

  33. Rummey C, Metz G (2007) Homology models of dipeptidyl peptidases 8 and 9 with a focus on loop predictions near the active site. Proteins 66:160–171

    Article  CAS  Google Scholar 

  34. Janardhan S, Padmanabha RY (2011) Homology modeling and molecular docking studies of human DPP8 and DPP9. Int J Pharm Res Dev 2:131–146

    Google Scholar 

  35. Van Goethem S, Matheeussen V, Joossens J et al (2011) Structure-activity relationship studies on isoindoline inhibitors of dipeptidyl peptidases 8 and 9 (DPP8, DPP9): is DPP8-selectivity an attainable goal? J Med Chem 54:5737–5746. doi:10.1021/jm200383j

    Article  CAS  Google Scholar 

  36. Kim D, Kowalchick JE, Edmondson SD et al (2007) Triazolopiperazine-amides as dipeptidyl peptidase IV inhibitors: close analogs of JANUVIA (sitagliptin phosphate). Bioorg Med Chem Lett 17:3373–3377. doi:10.1016/j.bmcl.2007.03.098

    Article  CAS  Google Scholar 

  37. Havale SH, Pal M (2009) Medicinal chemistry approaches to the inhibition of dipeptidyl peptidase-4 for the treatment of type-2 diabetes. Bioorg Med Chem 17:1783–1802

    Article  CAS  Google Scholar 

  38. Abbott CA, McCaughan GW, Gorrell MD (1999) Two highly conserved glutamic acid residues in the predicted beta propeller domain of dipeptidyl peptidase IV are required for its enzyme activity. FEBS Lett 458:278–284

    Article  CAS  Google Scholar 

  39. Nabeno M, Akahoshi F, Kishida H et al (2013) A comparative study of the binding modes of recently launched dipeptidyl peptidase IV inhibitors in the active site. Biochem Biophys Res Commun 434:191–196. doi:10.1016/j.bbrc.2013.03.010

    Article  CAS  Google Scholar 

  40. http://www.drugbank.ca. Accessed 10 March 3013.

  41. Schrödinger Suite 2011 Protein Preparation Wizard; Epik version 2.2, Schrödinger, LLC, New York, NY, 2011; Impact version 5.7, Schrödinger, LLC, New York, NY, 2011; Prime version 3.0, Schrödinger, LLC, New York, NY, 2011.

  42. LigPrep, version 2.5, Schrödinger, LLC, New York, NY, 2011

  43. Glide, version 5.7, Schrödinger, LLC, New York, NY, 2011

  44. Friesner RA, Banks JL, Murphy RB et al (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749

    Article  CAS  Google Scholar 

  45. Eldridge MD, Murray CW, Auton TR et al (1997) Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes. J Comput Aided Mol Des 11:425–445

    Article  CAS  Google Scholar 

  46. Verdonk ML, Cole JC, Hartshorn MJ et al (2003) Improved protein-ligand docking using GOLD. Proteins 52:609–623

    Article  CAS  Google Scholar 

  47. Liebeschuetz J, Cole J, Korb O (2012) Pose prediction and virtual screening performance of GOLD scoring functions in a standardized test. J Comput Aided Mol Des 26:737–748. doi:10.1007/s10822-012-9551-4

    Article  CAS  Google Scholar 

  48. Suite 2011: Desmond Molecular Dynamics System, version 3.0, D. E. Shaw Research, New York, NY, 2011. Maestro-Desmond Interoperability Tools, version 3.0, Schrödinger, New York, NY, 2011

  49. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 23:3–25. doi:10.1016/S0169-409X(96)00423-1

    Article  CAS  Google Scholar 

  50. Dror RO, Dirks RM, Grossman JP et al (2012) Biomolecular simulation: a computational microscope for molecular biology. Annu Rev Biophys 41:429–452. doi:10.1146/annurev-biophys-042910-155245

    Article  CAS  Google Scholar 

  51. Lee EH, Hsin J, Sotomayor M et al (2009) Discovery through the computational microscope. Structure 17:1295–1306. doi:10.1016/j.str.2009.09.001

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors wish to express their gratitude to Department of Science and Technology (DST), New Delhi (SERC/LS-295/2011) for providing financial assistance for the present study and Department of Biotechnology (DBT), New Delhi for providing Bioinformatics Infrastructure Facility.

Author information

Authors and Affiliations

  1. Drug Design and Medicinal Chemistry Lab, Department of Pharmaceutical Chemistry, Faculty of Pharmacy and Bioinformatics Infrastructure Facility (BIF), Jamia Hamdard, New Delhi, 110062, India

    Omprakash Tanwar, Gautam Kumar, Md. Mumtaz Alam, Md. Shaquiquzzaman & Mymoona Akhter

  2. Dr. Reddy’s Institute of Life Sciences, University of Hyderabad Campus, Gachibowli, Hyderabad, 500046, India

    Girdhar Singh Deora

  3. The University of Queensland, School of Pharmacy, Brisbane, Qld, 4072, Australia

    Girdhar Singh Deora

  4. School of Biochemistry, Khandwa Road, DAVV, Indore, 452001, India

    Lalima Tanwar

  5. Raghavendra Institute of Pharmaceutical Education and Research (RIPER), Anantapur, 515721, Andhra Pradesh, India

    Sridhara Janardhan

Authors
  1. Omprakash Tanwar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Girdhar Singh Deora
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lalima Tanwar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gautam Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sridhara Janardhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Md. Mumtaz Alam
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Md. Shaquiquzzaman
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Mymoona Akhter
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mymoona Akhter.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOC 5666 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tanwar, O., Deora, G.S., Tanwar, L. et al. Novel hydrazine derivatives as selective DPP-IV inhibitors: findings from virtual screening and validation through molecular dynamics simulations. J Mol Model 20, 2118 (2014). https://doi.org/10.1007/s00894-014-2118-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00894-014-2118-7

Keywords

Search

Navigation