COMBINATORIAL PHARMACOPHORE MODELING AND ATOM BASED 3D QSAR STUDIES OF BENZOTHIADIAZINES AS HCV-NS5B INHIBITORS

  • Prasanthi Polamreddy Centre for Nanoscience and Nanotechnology, International Research Centre, Sathyabama Institute of Science and Technology, Jeppiaar Nagar, Rajiv Gandhi Salai, Chennai 600119, India Excelra Knowledge Solutions Pvt Ltd, NSL-SEZ, Uppal, Hyderabad 500039, India
  • Vinita Vishwakarma Centre for Nanoscience and Nanotechnology, Sathyabama University, Chennai- 600 119, India
  • Manoj Kumar Mahto Excelra Knowledge Solutions Pvt Ltd, NSL-SEZ, Uppal, Hyderabad – 500039, India

Abstract

Objective: The objective of the current study was to elucidate the 3D pharmacophoric features of benzothiadiazine derivatives that are crucial for inhibiting Hepatitis C virus (HCV) Non-structural protein 5B (NS5B) and quantifying the features by building an atom based 3D quantitative structure-activity relationship (3D QSAR) model.

Methods: Generation of QSAR model was carried out using PHASE 3.3.

Results: A five-point pharmacophore model with two hydrogen bond acceptors, one negative ionization potential and two aromatic rings (AANRR) was found to be common among a maximum number of benzothiadiazine based NS5B inhibitors. A statistically significant 3D QSAR model was obtained from AANRR.6 which had correlation-coefficient (R2) value of 0.924, cross-validated correlation-coefficient (Q2) of 0.774, high Fisher ratio of 138 and low root mean square standard error (RMSE=0.29). There is another parameter, Pearson's R, its value emphasizes correlation between predicted and observed activities of the test set. For the current model, Pearson's R-value is 0.90, hence underlining the good quality of the model. The present study suggests that nitrogen atom of benzothiadiazine sulfamide ring, oxyacetamide group attached to C7 carbon of benzothiadiazine and sulfonamide oxygens are crucial for NS5B inhibitory activity. Prediction of activities of hit drugs generated in earlier research suggests that Aprepitant (Phase predicted activity: 6.9) could be a potential NS5B inhibitor.

Conclusion: This 3D QSAR model developed was statistically good and can be used to predict the activities of newly designed NS5B inhibitors and virtual screening as well. Predict the activities of newly designed NS5B inhibitors and virtual screening as well.

Keywords: Pharmacophore, QSAR, NS5B, HCV, Benzothiadiazine, Inhibitor

Downloads

Download data is not yet available.

References

1. Waheed Y, Bhatti A, Ashraf M. RNA dependent RNA polymerase of HCV: a potential target for the development of antiviral drugs. Infect Genet Evol 2015;14:247–57.
2. Deore RR, Chern JW. NS5B RNA dependent RNA polymerase inhibitors: the promising approach to treat hepatitis C virus infections. Curr Med Chem 2010;17:3806–26.
3. Lee H, Liu Y, Mejia E, Paul AV, Wimmer E. The C-terminal hydrophobic domain of hepatitis C virus RNA polymerase NS5B can be replaced with a heterologous domain of poliovirus protein 3A. J Virol 2006;80:11343–54.
4. Ferrari E, Wright-Minogue J, Fang JWS, Baroudy BM, Lau JYN, Hong Z. Characterization of soluble hepatitis C virus RNA-dependent RNA polymerase expressed in escherichia coli. J Virol 1999;73:1649–54.
5. Ferrari E, He Z, Palermo RE, Huang HC. Hepatitis C virus NS5B polymerase exhibits distinct nucleotide requirements for initiation and elongation. J Biol Chem 2008;283:33893–901.
6. Kim Y, Russell WK, Thomson M, David H, Kao CC, Kim Y, et al. Functional analysis of RNA binding by the hepatitis C virus RNA-dependent RNA polymerase. J Biol Chem 2005;280:38011-9.
7. Choi KH, Rossmann MG. RNA-dependent RNA polymerases from flaviviridae. Curr Opin Struct Biol 2009;19:746–51.
8. Pauwels F, Mostmans W, Quirynen LMM, van der Helm L, Boutton CW, Rueff AS, et al. Binding-site identification and genotypic profiling of hepatitis C virus polymerase inhibitors. J Virol 2007;81:6909–19.
9. Eltahla AA, Luciani F, White PA, Lloyd AR, Bull RA. Inhibitors of the hepatitis C virus polymerase; mode of action and resistance. Viruses 2015;7:5206–24.
10. Kayali Z, Schmidt WN. Finally sofosbuvir: an oral anti-HCV drug with wide performance capability. Pharmgenomics Pers Med 2014;7:387–97.
11. Feld JJ, Foster GR. Review second generation direct-acting antivirals–Do we expect major improvements? J Hepatol 2016;65:S130–42.
12. Guide QS. Think and Do Quick Start Guide. Phase 3.3; 2008.
13. Das D, Hong J, Chen SH, Wang G, Beigelman L, Seiwert SD, et al. Recent advances in drug discovery of benzothiadiazine and related analogs as HCV NS5B polymerase inhibitors. Bioorg Med Chem 2011;19:4690–703.
14. Tedesco R, Chai D, Darcy MG, Dhanak D, Fitch DM, Gates A, et al. Synthesis and biological activity of heteroaryl 3-(1,1-dioxo-2H-(1,2,4)-benzothiadizin-3-yl)-4-hydroxy-2(1H)-quinolinone derivatives as hepatitis C virus NS5B polymerase inhibitors. Bioorg Med Chem Lett 2009;19:4354–8.
15. Shaw AN, Tedesco R, Bambal R, Chai D, Concha NO, Darcy MG, et al. Substituted benzothiazine inhibitors of Hepatitis C virus polymerase. Bioorg Med Chem Lett 2009;19:4350–3.
16. Moro S. Statistical concepts in QSAR 2004;50:1–10.
17. Dixon SL, Smondyrev AM, Rao SN. PHASE: a novel approach to pharmacophore modelling and 3D database searching. Chem Biol Drug Des 2006;67:370–2.
18. Shah Ua, Deokar HS, Kadam SS, Kulkarni VM. Pharmacophore generation and Atom-based 3D-QSAR of novel 2-(4-methylsulfonylphenyl)pyrimidines as COX-2 inhibitors. Mol Divers 2010;14:559–68.
19. Gramatica P. External evaluation of QSAR models, in addition to cross-validation: verification of predictive capability on totally new chemicals. Mol Inform 2014;33:311–4.
20. Tedesco R, Shaw AN, Bambal R, Chai D, Concha NO, Darcy MG, et al. 3-(1,1-dioxo-2H-(1,2,4)-benzothiadiazin-3-yl)-4-hydroxy-2(1H)-quinolinones, potent inhibitors of hepatitis C virus RNA-dependent RNA polymerase. J Med Chem 2006;49:971–83.
21. Gramatica P. Principles of QSAR models validation: internal and external. QSAR Comb Sci 2007;26:694–701.
22. Hawkins DM, Basak SC, Mills D. Assessing model fit by cross-validation. J Chem Inf Comput Sci 2003;43:579–86.
23. Tichy M, Rucki M. Validation of QSAR models for legislative purposes. Interdiscip Toxicol 2009;2:184–6.
24. Thangaraj Sindhu, Sundaraj Rajamanikandan, Dhanapal Durgapriya, Jebamalai Raj Anitha, Selvaraj Akila, Velliyur Kanniyapan Gopalakrishnan. Molecular docking and qsar studies on plant derived bioactive compounds as potent inhibitors of dek oncoprotein. Asian J Pharm Clin Res 2011;4:67–71.
25. Donner PL, Xie Q, Pratt JK, Maring CJ, Kati W, Jiang W, et al. Des-A-ring benzothiadiazines: inhibitors of HCV genotype 1 NS5B RNA-dependent RNA polymerase. Bioorg Med Chem Lett 2008;18:2735–8.
26. Polamreddy P, Vishwakarma V, Gattu N. Discovery of HCV NS5B Palm I allosteric inhibitors using computational techniques-drug repurposing; 2016.
Statistics
393 Views | 880 Downloads
Citations
How to Cite
Polamreddy, P., V. Vishwakarma, and M. K. Mahto. “COMBINATORIAL PHARMACOPHORE MODELING AND ATOM BASED 3D QSAR STUDIES OF BENZOTHIADIAZINES AS HCV-NS5B INHIBITORS”. International Journal of Pharmacy and Pharmaceutical Sciences, Vol. 10, no. 3, Mar. 2018, pp. 43-69, doi:10.22159/ijpps.2018v10i3.23734.
Section
Original Article(s)