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.

A linguistic model for the rational design of antimicrobial peptides

Abstract

Antimicrobial peptides (AmPs) are small proteins that are used by the innate immune system to combat bacterial infection in multicellular eukaryotes1. There is mounting evidence that these peptides are less susceptible to bacterial resistance than traditional antibiotics and could form the basis for a new class of therapeutic agents2. Here we report the rational design of new AmPs that show limited homology to naturally occurring proteins but have strong bacteriostatic activity against several species of bacteria, including Staphylococcus aureus and Bacillus anthracis. These peptides were designed using a linguistic model of natural AmPs: we treated the amino-acid sequences of natural AmPs as a formal language and built a set of regular grammars to describe this language. We used this set of grammars to create new, unnatural AmP sequences. Our peptides conform to the formal syntax of natural antimicrobial peptides but populate a previously unexplored region of protein sequence space.

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

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Figure 1: A schematic of the in silico peptide design strategy.

References

  1. Zasloff, M. Antimicrobial peptides of multicellular organisms. Nature 415, 389–395 (2002)

    ADS  CAS  Article  Google Scholar 

  2. Hancock, R. E. & Patrzykat, A. Clinical development of cationic antimicrobial peptides: from natural to novel antibiotics. Curr. Drug Targets Infect. Disord. 2, 79–83 (2002)

    CAS  Article  Google Scholar 

  3. Tiozzo, E., Rocco, G., Tossi, A. & Romeo, D. Wide-spectrum antibiotic activity of synthetic, amphipathic peptides. Biochem. Biophys. Res. Commun. 249, 202–206 (1998)

    CAS  Article  Google Scholar 

  4. Biragyn, A. et al. Toll-like receptor 4-dependent activation of dendritic cells by β-defensin 2. Science 298, 1025–1029 (2002)

    ADS  CAS  Article  Google Scholar 

  5. Ellerby, H. M. et al. Anti-cancer activity of targeted pro-apoptotic peptides. Nature Med. 5, 1032–1038 (1999)

    CAS  Article  Google Scholar 

  6. Giangaspero, A., Sandri, L. & Tossi, A. Amphipathic α helical antimicrobial peptides. Eur. J. Biochem. 268, 5589–5600 (2001)

    CAS  Article  Google Scholar 

  7. Shai, Y. Mode of action of membrane active antimicrobial peptides. Biopolymers 66, 236–248 (2002)

    CAS  Article  Google Scholar 

  8. Jurafsky, D. & Martin, J. H. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (Prentice Hall, Upper Saddle River, New Jersey, 2000)

  9. Searls, D. B. The language of genes. Nature 420, 211–217 (2002)

    ADS  CAS  Article  Google Scholar 

  10. Hofmann, K., Bucher, P., Falquet, L. & Bairoch, A. The PROSITE database, its status in 1999. Nucleic Acids Res. 27, 215–219 (1999)

    CAS  Article  Google Scholar 

  11. Rigoutsos, I. & Floratos, A. Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm. Bioinformatics 14, 55–67 (1998)

    CAS  Article  Google Scholar 

  12. Wang, Z. & Wang, G. APD: the Antimicrobial Peptide Database. Nucleic Acids Res. 32, D590–D592 (2004)

    ADS  CAS  Article  Google Scholar 

  13. Bairoch, A. & Apweiler, R. The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Res. 28, 45–48 (2000)

    CAS  Article  Google Scholar 

  14. Wu, M. & Hancock, R. E. W. Interaction of the cyclic antimicrobial cationic peptide bactenecin with the outer and cytoplasmic membrane. J. Biol. Chem. 274, 29–35 (1999)

    CAS  Article  Google Scholar 

  15. Tossi, A., Sandri, L. & Giangaspero, A. Amphipathic, α-helical antimicrobial peptides. Biopolymers 55, 4–30 (2000)

    CAS  Article  Google Scholar 

  16. Bell, G. & Gouyon, P-H. Arming the enemy: the evolution of resistance to self-proteins. Microbiology 149, 1367–1375 (2003)

    CAS  Article  Google Scholar 

  17. Hilpert, K., Volkmer-Engert, R., Walter, J. & Hancock, R. E. W. High-throughput generation of small antibacterial peptides with improved activity. Nature Biotechnol. 23, 1008–1012 (2005)

    CAS  Article  Google Scholar 

  18. Li, W., Jaroszewski, L. & Godzik, A. Clustering of highly homologous sequences to reduce the size of large protein database. Bioinformatics 17, 282–283 (2001)

    CAS  Article  Google Scholar 

  19. Maizel, J. V. & Lenk, R. P. Enhanced graphic matrix analysis of nucleic acid and protein sequences. Proc. Natl Acad. Sci. USA 78, 7665–7669 (1981)

    ADS  MathSciNet  CAS  Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank M. Zasloff, K. D. Wittrup, R. Berwick, and G. Georgiou for valuable input on the draft manuscript, and J. Moxley for figure preparation. The authors gratefully acknowledge the support of the Singapore-MIT Alliance, the NIH, and the Fannie and John Hertz Foundation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gregory Stephanopoulos.

Ethics declarations

Competing interests

Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests.

Supplementary information

Supplementary Notes

This file contains Supplementary Tables 1–3, Supplementary Figure 1 and Supplementary Methods (PDF 176 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Loose, C., Jensen, K., Rigoutsos, I. et al. A linguistic model for the rational design of antimicrobial peptides. Nature 443, 867–869 (2006). https://doi.org/10.1038/nature05233

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature05233

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

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