Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

In silico design of tubulin-targeted antimitotic peptides

Abstract

Microtubules are polymeric structures formed by the self-assembly of tubulin dimers. The growth and shrinkage of these dynamic arrays have a key role during the cell-proliferation process. This makes tubulin the molecular target of many anticancer drugs currently in use or under clinical trial. Their impressive success is limited by the onset of resistant tumour cells during the treatment, so new resistance-proof molecules need to be developed. Here we use molecular dynamics and free-energy calculations to study the network of interactions that allow microtubule formation. Modelling the protein–protein interface allows us to identify the amino acids responsible for tubulin–tubulin binding and thus to design peptides, which correspond to tubulin subsequences, that interfere with microtubule formation. We show that the application of molecular modelling techniques leads to the identification of peptides that exhibit antitubulin activity both in vitro and in cultured cells.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: PPIs in tubulin dimers.
Figure 2: Structural modifications that occur in two tubulin subsequences.
Figure 3: Comparison of alanine scanning of residues that correspond to the three peptides selected at the interface.
Figure 4: The influence of peptides on tubulin assembly in vitro.
Figure 5: Microtubule organization in human lung carcinoma cell line A549 exposed for 24 hours to different treatments.

Similar content being viewed by others

References

  1. Jordan, M. A. & Wilson, L. Microtubules as a target for anticancer drugs. Nature Rev. Cancer 4, 253–265 (2004).

    Article  CAS  Google Scholar 

  2. Nogales, E. A structural view of microtubule dynamics. Cell. Mol. Life Sci. 56, 133–142 (1999).

    Article  CAS  Google Scholar 

  3. Manfredi, J. J., Parness J. & Horwitz, S. B. Taxol binds to cellular microtubules. J. Cell. Biol. 94, 688–696 (1982).

    Article  CAS  Google Scholar 

  4. Hastie, S. B. Interactions of colchicine with tubulin. Pharmacol. Ther. 512, 377–401 (1991).

    Article  Google Scholar 

  5. Duflos, A., Kruczynski, A. & Barret, J. M. Novel aspects of natural and modified vinca alkaloids. Curr. Med. Chem. Anticancer Agents 2, 55–70 (2002).

    Article  CAS  Google Scholar 

  6. Hamel, E. Antimitotic natural products and their interactions with tubulin. Med. Res. Rev. 16, 207–231 (1996).

    Article  CAS  Google Scholar 

  7. Torin Huzil, J., Chen, K., Kurgan, L. & Tuszynski, J. A. The role of β-tubulin mutations and isotype expression in acquired drug resistance. Cancer Inf. 3, 159–181 (2007).

    Google Scholar 

  8. Orr, G. A., Verdier-Pinard, P., McDaid, H. & Horwits, S. A. Mechanisms of taxol resistance related to microtubules. Oncogene 22, 7280–7295 (2003).

    Article  CAS  Google Scholar 

  9. Wells, J. A. & McClendon, C. L. Reaching for high-hanging fruit in drug discovery at protein–protein interfaces. Nature 450, 1001–1009 (2007).

    Article  CAS  Google Scholar 

  10. Lo Conte, L., Chothia, C. & Janin, J. The atomic structure of protein–protein recognition sites. J. Mol. Biol. 285, 2177–2198 (1999).

    Article  CAS  Google Scholar 

  11. Chène, P. Drugs targeting protein–protein interactions. ChemMedChem 1, 400–411 (2006).

    Article  Google Scholar 

  12. Arkin, M. R. & Wells, J. A. Small-molecule inhibitors of protein–protein interactions: progressing towards the dream. Nature Rev. Drug Disc. 3, 301–317 (2004).

    Article  CAS  Google Scholar 

  13. Janin, Y. L. Peptides with anticancer use or potential. Amino Acids 25, 1–40 (2003).

    Article  CAS  Google Scholar 

  14. Berg, T. Modulation of protein–protein interactions with small organic molecules. Angew. Chem. Int. Ed. 42, 2462–2481 (2003).

    Article  CAS  Google Scholar 

  15. Lowman, H. B. Bacteriophage display and discovery of peptide leads for drug development. Annu. Rev. Biophys. Biomol. Struct. 26, 401–424 (1997)

    Article  CAS  Google Scholar 

  16. Sidhu, S. S., Fairbrothe, W. J. & Deshayes, K. Exploring protein–protein interactions with phage display. ChemBioChem 4, 14–25 (2003).

    Article  CAS  Google Scholar 

  17. Sattler, M. et al. Structure of Bcl–XL–Bak peptide complex: recognition between regulators of apoptosis. Science 275, 983–986 (1997).

    Article  CAS  Google Scholar 

  18. Kussie, P.H et al. Structure of the MDM2 oncoprotein bound to the p53 tumor suppressor transactivation domain. Science 274, 948–953 (1996).

    Article  CAS  Google Scholar 

  19. Villacañas O. & Rubio-Martinez, J. Reducing CDK4/6-p16INK4a interface: computational alanine scanning of a peptide bound to CDK6 protein. Proteins 63, 797–810 (2006).

    Article  Google Scholar 

  20. Zhong, H. & Carlson H. A. Computational studies and peptidomimetic design for the human p53–MDM2 complex. Proteins 58, 222–234 (2005).

    Article  CAS  Google Scholar 

  21. Massova, I. & Kollman, P. A. Combined molecular mechanical and continuum solvent approach (MM-PBSA/GBSA) to predict ligand binding. Persp. Drug Disc. Des. 18, 113–135 (2000).

    Article  CAS  Google Scholar 

  22. Massova, I. & Kollman, P. A. Computational alanine scanning to probe protein–protein interactions: a novel approach to evaluate binding free energies. J. Am. Chem. Soc. 121, 8133–8143 (1999).

    Article  CAS  Google Scholar 

  23. Moreira, I. S., Fernandes, P. A. & Ramos, M. J. Unravelling the importance of protein–protein interactions: application of a computational alanine scanning mutagenesis to the study of the IgG1 streptococcal protein G (C2 fragment) complex. J. Phys. Chem. B 110, 10962–10969 (2006).

    Article  CAS  Google Scholar 

  24. Moreira, I. S., Fernandes, P. A. & Ramos, M. J. Unravelling hot spots: a comprehensive computational mutagenesis study. Theor. Chem. Acc. 117, 99–113 (2007).

    Article  CAS  Google Scholar 

  25. Nogales, E. A structural view of microtubule dynamics. Cell. Mol. Life Sci. 56, 133–142 (1999).

    Article  CAS  Google Scholar 

  26. Wordeman, L. & Mitchison, T. J. in Microtubules (eds Hyams, J. S. & Lloyd, C. W.) 287–302 (Wiley-Liss, 1994).

    Google Scholar 

  27. McIntosh, J. R. in Microtubules (eds Hyams, J. S. & Lloyd, C. W.) 413–434 (Wiley-Liss, 1994).

    Google Scholar 

  28. Waterman-Storer, C. & Salmon, E. D. Microtubule dynamics: treadmilling comes around again. Curr. Biol. 7, 369–372 (1997).

    Article  Google Scholar 

  29. Nogales, E., Whittaker, M., Milligan, R. A. & Downing, K. H. High-resolution model of the microtubule. Cell 96, 79–88 (1999).

    Article  CAS  Google Scholar 

  30. Löwe, J., Li, H., Downing, K. H. & Nogales, E. Refined structure of αβ-tubulin at 3.5 Å resolution. J. Mol. Biol. 313, 1045–1057 (2001).

    Article  Google Scholar 

  31. Richards, K. L. et al. Structure–function relationship in yeast tubulins. Mol. Biol. Cell 11, 1887–1903 (2000).

    Article  CAS  Google Scholar 

  32. Reijo, R. A., Cooper, E. M., Beagle, G. J. & Huffaker, T. C. Systematic mutational analysis of the yeast beta-tubulin gene. Mol. Biol. Cell 5, 29–43 (1994).

    Article  CAS  Google Scholar 

  33. Anders, K. R. & Botstein, D. Dominant-lethal α-tubulin mutants defective in microtubule depolymerization in yeast. Mol. Biol. Cell 12, 3973–3986 (2001).

    Article  CAS  Google Scholar 

  34. Humphrey, W., Dalke, A. & Schulten, K. VMD – Visual Molecular Dynamics. J. Mol. Graphics 14, 33–38 (1996).

    Article  CAS  Google Scholar 

  35. Johnson, K. A. & Borisy, G. G. Kinetic analysis of microtubule self-assembly in vitro. J. Mol. Biol. 117, 1–31 (1977).

  36. Nogales, E., Wolf, S. G. & Downing, K. H. Structure of the alpha beta tubulin dimer by electron crystallography. Nature 391, 199–203 (1998).

    Article  CAS  Google Scholar 

  37. Case, D. A., et al. AMBER 9 (University of California, San Francisco, 2006).

  38. Duan, Y., et al. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J. Comput. Chem. 24, 1999–2012 (2003).

    Article  CAS  Google Scholar 

  39. Jorgensen, W. L., Chandrasekhar, J., Madura, J. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983).

    Article  CAS  Google Scholar 

  40. Ryckaert, J. P., Ciccotti, G. & Berendsen, H. J. C. Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J. Comput. Phys. 23, 327–341 (1977).

    Article  CAS  Google Scholar 

  41. Mita, A. & Sept, D. Localization of the antimitotic peptide and depsipeptide binding site on β tubulin. Biochemistry 43, 13955–13962 (2004).

    Article  Google Scholar 

  42. Zoete, V. & Michielin, O. Comparison between computational alanine scanning and per-residue binding free energy decomposition for protein–protein association using MM-GBSA: application to the TCR-p-MHC complex. Proteins 67, 1026–1047 (2007).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

S. Rendine is acknowledged for useful discussions.

Author information

Authors and Affiliations

Authors

Contributions

S.P. and M.S. conceived and designed the research project; G.Sa. G.C., D.C., P.F., G.Sp. and P.M. performed the experiments; S.P., G.Sa., G.C. and M.S. analysed the data and co-wrote the paper. All authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Maurizio Sironi.

Supplementary information

Supplementary information

Supplementary information (PDF 843 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pieraccini, S., Saladino, G., Cappelletti, G. et al. In silico design of tubulin-targeted antimitotic peptides. Nature Chem 1, 642–648 (2009). https://doi.org/10.1038/nchem.401

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nchem.401

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing