Skip to main content
Log in

Computer based screening for novel inhibitors against Vibrio cholerae using NCI diversity set-II: An alternative approach by targeting transcriptional activator ToxT

  • Original Articles
  • Published:
Interdisciplinary Sciences: Computational Life Sciences Aims and scope Submit manuscript

Abstract

Cholera is a severe diarrheal disease caused by Vibrio cholerae and remains as a major health risk in developing countries. The emergence and spread of multi-drug resistant V. cholerae strains during the past two decades is now a major problem in the treatment of cholera and have created the urgent need for the development of novel therapeutic agents. Targeting transcriptional factor is now a novel approach to tackle the development of multi-drug resistant strain. In the recent year virtual high throughput screening has emerged as a widely accepted powerful technology in the identification of novel and diverse lead. This study provides new insight to the search for new potent and selective inhibitors that still remains necessary to avoid the risk of possible resistance and reduce toxicity and side effects of currently available cholera drugs. The publications of high resolution X-ray structure of V. cholerae ToxT has open the way to the structure based virtual screening to identify new small molecular inhibitors which still remain necessary to avoid the risk of possible resistance and reduce toxicity and side effects of currently available cholera drugs. In this study we have performed structure based virtual screening approach using NCI diversity set-II to look for novel inhibitor of ToxT and proposed eight candidate compounds with high scoring function. Thus from complex scoring and binding ability it is elucidated that these compounds could be the promising inhibitors or could be developed as novel lead compounds for drug design against cholera.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Anne, E.C., Emily, P., Deborah, T.H. 2007. Targeting virulence: a new paradigm for antimicrobial therapy. Nature Chemical Biology 3, 541–548.

    Article  Google Scholar 

  2. Athanasios, G.P. 1998. Transcription-factormodulating agents: precision and selectivity in drug design. Molecular Medicine Today (Review) 8, 358–66.

    Google Scholar 

  3. Baell, J.B., Holloway, G.A. 2010. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J Med Chem. 53, 2719–2740.

    Article  CAS  PubMed  Google Scholar 

  4. Barua. D. 1972. The global epidemiology of cholera in recent years. Proc R Soc Med. 65, 423–428.

    CAS  PubMed Central  PubMed  Google Scholar 

  5. Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H. 2000. “The protein data bank.” Nucleic Acids Res 28, 235–242.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  6. Blum, L.C., Reymond, J.L. 2009. 970 million drug like small molecules for virtual screening in the chemical universe database GDB-13. J Am Chem Soc 131, 8732–8733.

    Article  CAS  PubMed  Google Scholar 

  7. Brandon, M.C., Xiao H.C., Gregor, G.W., Borries, D., Harts, P.J., Karl, E.K. 2011. N-terminal Residues of the Vibrio cholerae Virulence Regulatory Protein ToxT Involved in Dimerization and Modulation by Fatty Acids. J Biol Chem 286, 28644–28655.

    Article  Google Scholar 

  8. Butler, D. 2010. Cholera tightens grip on Haiti. Nature 468, 483–484.

    Article  CAS  PubMed  Google Scholar 

  9. Chakraborty, S., Garg, P., Ramamurthy, T., Thungapathra, M., Gautam, J.K., Kumar, C., Maiti, S., Yamasaki, S., Shimada, T., Takeda, Y., Ghosh, A., Nair G.B. 2001. Comparison of antibiogram, virulence genes, ribotypes and DNA fingerprints of Vibrio cholerae of matching serogroups isolated from hospitalized diarrhoea cases and from the environment during 1997–1998 in Calcutta, India. J Med Microbiol 50, 879–88.

    CAS  PubMed  Google Scholar 

  10. Champion, G.A., Neely, M.N., Brennan, M.A., DiRita, V.J. 1997. A branch in the ToxR regulatory cascade of Vibrio cholerae revealed by characterization of toxT mutant strains. Mol Microbiol 23, 323–331.

    Article  CAS  PubMed  Google Scholar 

  11. Chatterjee, S., Asakura, M., Chowdhury, N., Neogi, S.B., Sugimoto, N., Haldar, S., Awasthi, S.P., Hinenoya, A., Aoki, S., Yamasaki, S. 2011. Capsaicin, a potential inhibitor of cholerae toxin production in Vibrio cholerae. FEMS Microbiol Lett 306, 54–60.

    Article  Google Scholar 

  12. Das, S., Saha, R., Kaur, I.R. 2008. Trend of antibiotic resistance of Vibrio cholerae strains from East Delhi. Indian J Med Res 127, 478–82.

    PubMed  Google Scholar 

  13. David, A.R, Vanessa, S. 2010. Anti-virulence strategies to combat bacteria-mediated disease. Nature Reviews Drug Discovery 9, 117–128.

    Article  Google Scholar 

  14. DeLano, W.L. 2002. The PyMOL Molecular Graphics System. San Carlos, CA, USA: DeLano Scientific. http://www.pymol.org.

    Google Scholar 

  15. DiRita, V. J., Parsot, C., Jander, G., Mekalanos, J.J. 1991. Regulatory cascade controls virulence in Vibrio cholerae. Proc Natl Acad Sci 88, 5403–5407.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  16. DiRita, V. J., Neely, M., Taylor, R. K., Bruss, P. M. 1996. Differential expression of the ToxR regulon in classical and E1 Tor biotypes of Vibrio cholerae is due to biotype-specific control over toxT expression. Proc Natl Acad Sci 93, 7991–7995.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  17. Duan, Y., Wu, C., Chowdhury S., Lee, M.C., Xiong, G., Zhang, W., Yang, R., Cieplak, P., Luo, R., Lee, T., Caldwell, J., Wang, J., Kollman, P. 2003. A pointcharge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J Comput Chem 24, 1999–2012.

    Article  CAS  PubMed  Google Scholar 

  18. Dundas, J., Ouyang, Z., Tseng, J., Binkowski, A., Turpaz, Y., Liang, J. 2006. CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Res 34, W116–W118.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  19. Ekins, S., Boulanger, B., Swaan, P.W., Hupsey, M.A. 2002. Towards a new age of virtual ADME/TOX and multidimensional drug discovery. Jol Computer aided mol dsgn 16, 381–401.

    Article  CAS  Google Scholar 

  20. Faruque, A.S., Alam, K., Malek, M.A., Khan, M.G.., Ahmed, S., Saha, D., Khan, W.A., Nair, G. B., Salam, M.A., Luby, S.P. & Sack, D.A. 2007. Emergence of Multidrug-resistant Strain of Vibrio cholerae spp O1 in Bangladesh and Reversal of Their Susceptibility to Tetracycline After Two Years. J Health Popul Nutr 25, 241–243.

    PubMed Central  PubMed  Google Scholar 

  21. Fersht, A.R., Shi, J.P., Knill-Jones, J., Lowe, D.M., Wilkinson, A.J., Blow, D.M., Brick, P., Carter, P., Waye, M.M., Winter, G. 1985. Hydrogen bonding and biological specificity analyzed by protein engineering. Nature 314, 235–238.

    Article  CAS  PubMed  Google Scholar 

  22. Friesner, R. A., Banks, J. L., Murphy, R. B., Halgren, T.A., Klicic, J. J., Mainz, D. T., Repasky, M.P., Knoll, E.H., Shaw, D.E., Shelley, M., Perry, J.K., Francis, P., Shenkin, P. S. 2004. Glide: a new approach for rapid, accurate docking and scoring method and assessment of docking accuracy. J Med Chem 47, 1739–49.

    Article  CAS  PubMed  Google Scholar 

  23. Garber K. 2006. Intellectual property. Decision on NFkappaB patent could have broad implications for biotech. Science 312, 827.

    Article  CAS  PubMed  Google Scholar 

  24. Heberlé, G., de Azevedo, W.F. 2011. Bio-Inspired Algorithms Applied to Molecular Docking Simulations. Current Medicinal Chemistry 18, 1339–1352.

    Article  PubMed  Google Scholar 

  25. Herrington, D.A., Hall, R.H., Losonsky, G., Mekalanos, J.J., Taylor, R.K., Levine, M.M. 1988. Toxin, toxin-coregulated pili, and the toxR regulon are essential for Vibrio cholerae pathogenesis in humans. J Exp Med 168, 1487–1492.

    Article  CAS  PubMed  Google Scholar 

  26. Higgins, D.E. and DiRita, V.J. 1994. Transcriptional control of toxT, a regulatory gene in the ToxR regulon of Vibrio cholerae. Mol Microbiol 14, 17–29.

    Article  CAS  PubMed  Google Scholar 

  27. Humphrey, W., Dalke, A. and Schulten, K. 1996. “VMD — Visual Molecular Dynamics”, J Molec Graphics 14, 33–38.

    Article  CAS  Google Scholar 

  28. Hung, D.T., Shakhnovich, E.A., Pierson, E., Mekalanos, J.J. 2005. Small-molecule inhibitor of Vibrio cholerae virulence and intestinal colonization. Science 310, 670–674.

    Article  CAS  PubMed  Google Scholar 

  29. Kapetanovic, I.M. 2008. Computer-aided Drug Discovery and Development (CADDD): in silico-chemicobiological approach. Chem Biol Interact 171, 165–176.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  30. Karamouzis, M.V., Gorgoulis, V.G., Papavassiliou, A.G. 2000. Transcription Factors and Neoplasia: Vistas in Novel Drug Design. Clin Cancer Res 8, 949–61.

    Google Scholar 

  31. Katie, J. Simmons., Chopra, I., Fishwick, C.W.G. 2010. Structure-based discovery of antibacterial drugs. Nature Reviews Microbiology 8, 501–510.

    Article  Google Scholar 

  32. Kitaoka, M., Miyata, S.T., Unterweger, D., Pukatzki, S. 2011. Antibiotic resistance mechanisms of Vibrio cholerae. J Med Microbiol 60, 397–407.

    Article  PubMed  Google Scholar 

  33. Konstantinopoulos, P.A., Papavassiliou, A.G. 2011. Seeing the Future of Cancer-Associated Transcription Factor Drug Targets. JAM 305, 2349–2350.

    Article  CAS  Google Scholar 

  34. Lagorce, D., Maupetit, J., Baell, J., Sperandio, O., Tuff’ery P., Miteva, M.A., Galons, H., Villoutreix, B.O. 2011. The FAF-Drugs2 server: a multistep engine to prepare electronic chemical compound collections. Bioinformatics. 27, 2018–2020.

    Article  CAS  PubMed  Google Scholar 

  35. Lipinski, C.A., Lombardo F., Dominy, B.W., Feeney, P.J. 2001. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46, 3–26.

    Article  CAS  PubMed  Google Scholar 

  36. Lowden, M.J., Skorpupski, K., Pellegrini, M., Chiorazzo, M.G., Taylor, R.K., Kull, F.J. 2010. Structure of Vibrio cholerae ToxT reveals a mechanism for Fatty acid regulation of virulence genes. Proc Natl Acad Sci 107, 2860–2865.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  37. Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., Olson, A. J. 2009. Autodock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 16, 2785–2791.

    Article  Google Scholar 

  38. Natsumi, B & Akaho, E. 2011. VSDK: Virtual screening of small molecules using Autodock Vina on Windows platform. Bioinformation 6, 387–388.

    Article  Google Scholar 

  39. Perola, E., Walters, W.P, Charifson, P.S. 2004. A detailed comparison of current docking and scoring methods on system of pharmaceutical relevance. Proteins 56, 235–249.

    Article  CAS  PubMed  Google Scholar 

  40. Petsko, G. A. 2010. When failure should be the option. BMC Biology 8, 61.

    Article  PubMed Central  PubMed  Google Scholar 

  41. Pierce N. F., Banwell, J. G., Mitra, R. C., Caranasos, G. J., Keimowitz, R. I.., Thomas, J., Mondal, A. 1968. Controlled comparison of tetracycline and furazolidone in Cholera. BMJ 3, 277–280.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Pollitzer, R. Cholera. 1959. World Health Organization, Geneva, Switzerland 58, 1001–1019.

    CAS  Google Scholar 

  43. Rappe, A.K., Casewit, C.J., Colwell, K.S., Goddard, W. A. III., Skiff, W. M. 1992. UFF, a Full Periodic Table Force Field for Molecular Mechanics and Molecular Dynamics Simulations, J A Chem Soc 114, 10024–10035.

    Article  CAS  Google Scholar 

  44. Romano T.K. 2007. Structure-Based Drug Design: Docking and Scoring. Current Protein and Peptide Science 8, 312–328.

    Article  Google Scholar 

  45. Ruvinsky, A.M., Kozintsev, A.V. 2006. Novel statistical-thermodynamic methods to predict proteinligand binding positions using probability distribution functions. PROTEINS: Structure function and bioinformatics 62, 202–208.

    Article  CAS  Google Scholar 

  46. Skorupski, K., Taylor R. K. 1997. Control of the ToxR virulence regulon in Vibrio cholerae by enviromental stimuli. Mol Microbiol. 25, 1003–1009.

    Article  CAS  PubMed  Google Scholar 

  47. Souse, S.F., Fernandes, P.A., Ramos, M.J. 2006. Protein-ligand docking: current status and future challenges. Protein 65, 15–26.

    Article  Google Scholar 

  48. Szileigyl, G. 1984. Arzneimittel Forshung -Drug Research 35, 1260.

    Google Scholar 

  49. Walters, W.P., Stahl, M.T. and Murcko, M.A. 1998. Virtual screening — an overview. Drug Discov Today. 3: 160–178.

    Article  CAS  Google Scholar 

  50. Waszkowycz, B., Perkins, T. D. J., Sykes, R.A. J. 2001. Large-scale virtual screening for discovering leads in the post-genomic era. IBM systems journal-Deep computing for the life sciences 40, 360–376.

    Google Scholar 

  51. Xu, D., Lin, S.L., Nussinov, R. 1997a. Protein binding versus protein folding: the role of hydrophilic bridges in protein associations. J Mol Biol 265, 68–84.

    Article  CAS  PubMed  Google Scholar 

  52. Xu, D., Tsai, C.J., Nussinov, R. 1997b. Hydrogen bonds and salt bridges across protein-protein interfaces. Protein Engineering 10, 999–1012.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shakhinur Islam Mondal.

Additional information

Equal contribution to the work.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mondal, S.I., Khadka, B., Akter, A. et al. Computer based screening for novel inhibitors against Vibrio cholerae using NCI diversity set-II: An alternative approach by targeting transcriptional activator ToxT. Interdiscip Sci Comput Life Sci 6, 108–117 (2014). https://doi.org/10.1007/s12539-012-0046-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12539-012-0046-8

Key words

Navigation