Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Theoretical studies on benzimidazole derivatives as E. coli biotin carboxylase inhibitors

  • 278 Accesses

  • 7 Citations

Abstract

Biotin carboxylase (AccC) protein plays an essential role in cell wall biosynthesis in majority of bacterial genera. Inhibition of cell wall biosynthesis might be an ideal way to control the bacterial multiplication in the host system. AccC is one of the promising targets for the antibacterial drugs production. The benzimidazole derivatives are hopeful biotin carboxylase inhibitors, which sensitizes to the Escherichia coli (E. coli) and many other bacterial species too. In steam of developing better benzimidazole derivatives, we describe a quantitative pharmacophore model of benzimidazole derivatives using Phase module of Schrödinger LLC. This model suggested that the following features are essential for ligand binding, i.e., two aromatic rings, two hydrogen bond donors, one hydrogen bond acceptor, and one hydrophobic group. Further, atom-based 3D-QSAR model was constructed using training set of 37 inhibitors. The constructed QSAR model has cross validated co-efficient value of (Q 2) 0.736 and regression co-efficient value of (R 2) 0.937. The external validation indicated that our QSAR model possessed high predicted powers with \( r_{o}^{2} \) value of 0.933, \( r_{\text m}^{2} \) value of 0.876. The best active and least active compounds were docked into the active site of receptor using Glide and hotspots of the active site were analyzed. The QSAR elucidated here for benzimidazole derivatives combined with their binding information will provide an opportunity to explore the chemical space to promote the potency of AccC inhibitors.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  1. Alfonso AJ (2005) Resistance to antibiotics: are we in the post-antibiotic era?. Elsevier, Amsterdam

  2. Almerico AM, Tutone M, Lauria A (2010) 3D-QSAR pharmacophore modeling and in silico screening of new Bcl-xl inhibitors. Eur J Med Chem 450:4774–4782

  3. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28:235–242

  4. Campbell JW, Cronan JE, Acid Bacterial Fatty (2001) Biosynthesis: targets for antibacterial drug discovery. Annu Rev Microbiol 55:305–332

  5. Clark DE (2006) What has computer-aided molecular design ever done for a drug discovery? Expert Opin Drug Discov 1:103–110

  6. Cheng CC, Shipps GW, Yang Z, Sun B, Kawahata N, Soucy KA, Soriano A, Orth P, Xiao P, Mann P, Black T (2009) Discovery and optimization of antibacterial AccC inhibitors. Bioorg Med Chem Lett 19:6507–6514

  7. Glide, version 5.5, Schrödinger, LLC, New York, 2009

  8. Golbraikh A, Tropsha A (2002) Beware of q2!. J Mol Graph Model 20:269–276

  9. Heath RJ, White SW, Rock CO (2001) Lipid biosynthesis as a target for antibacterial agents. Prog Lipid Res 40:467–497

  10. Jalaie M, Erickson JA (2000) Homology model directed alignment selection for comparative molecular field analysis: application to photosystem II inhibitors. J Comput Aided Mol Des 14:181–197

  11. Miller JR, Dunham S, Mochalkin I, Banotai C, Bowman M, Buist S, Dunkle B, Hanna D, Harwood HJ, Huband MD, Karnovsky A, Kuhn M, Limberakis C, Liu JY, Mehrens S, Mueller NL, Ogden A, Ohren J, Prasad JVNV, Shelly JA, Skerlos L, Sulavik M, Thomas VH, VanderRoest S, Wang L, Wang Z, Whitton A, Zhu T, Stover CK (2009) A class of selective antibacterials derived from a protein kinase inhibitor pharmacophore. Proc Natl Acad Sci USA 106:1737–1742

  12. Mochalkin I, Miller JR, Narasimhan L, Thanabal V, Erdman P, Cox PB, Prasad JVNV, Lightle S, Huband MD, Stover CK (2009) Discovery of antibacterial biotin carboxylase inhibitors by virtual screening and fragment-based approaches. ACS Chem Biol 4:473–483

  13. Payne D, Tomasz A (2004) Antimicrobials: the challenge of antibiotic resistant bacterial pathogens: the medical need the market and prospects for new antimicrobial agents. Curr Opin Microbiol 7:435–438

  14. Payne DJ, Warren, Holmes DJ, Ji Y, Lonsdale JT (2001) Bacterial fatty-acid biosynthesis: a genomics-driven target for antibacterial drug discovery. Drug Discov Today 6:537–544

  15. Phase 3.2. Schrödinger, LLC, New York, 2007

  16. Watts KS, Dalal P, Murphy RB, Sherman W, Friesner RA, Shelley JC (2010) ConfGen: a conformational search method for efficient generation of bioactive conformers. J Chem Inf Model 50:534–546

  17. Zhang YM, White SW, Rock CO (2006) Inhibiting bacterial fatty acid synthesis. J Biol Chem 281:17541–17544

Download references

Author information

Correspondence to Karthikeyan Muthusamy.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Nagamani, S., Muthusamy, K., Kirubakaran, P. et al. Theoretical studies on benzimidazole derivatives as E. coli biotin carboxylase inhibitors. Med Chem Res 21, 2169–2180 (2012). https://doi.org/10.1007/s00044-011-9738-6

Download citation

Keywords

  • Biotin carboxylase
  • AccC
  • Escherichia coli
  • Phase
  • 3D-QSAR
  • Docking studies
  • External validation