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.

  • News & Views
  • Published:

ANTIMICROBIAL PEPTIDES

Antibiotic discovery with machine learning

Nature Biotechnology volume 40, pages 833–834 (2022)Cite this article

Subjects

Artificial intelligence finds candidate peptide antibiotics in the human gut microbiome.

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

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: AI enables antibiotic discovery in the gut microbiome.

References

  1. Magana, M. et al. Lancet Infect. Dis. 20, e216–e230 (2020).

    Article  CAS  Google Scholar 

  2. Ma, Y. et al. Nat. Biotechnol. https://doi.org/10.1038/s41587-022-01226-0 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Der Torossian Torres, M. & de la Fuente-Nunez, C. Chem. Commun. (Camb.) 55, 15020–15032 (2019).

    Article  Google Scholar 

  4. Antimicrobial Resistance Collaborators. Lancet 399, 629–655(2022).

  5. Porto, W. F. et al. Nat. Commun. 9, 1490 (2018).

    Article  Google Scholar 

  6. Stokes, J. M. et al. Cell 181, 475–483 (2020).

    Article  CAS  Google Scholar 

  7. Das, P. et al. Nat. Biomed. Eng. 5, 613–623 (2021).

    Article  CAS  Google Scholar 

  8. Torres, M. D. T., Melo, M. C. R., Crescenzi, O., Notomista, E. & de la Fuente-Nunez, C. Nat. Biomed. Eng. 6, 67–75 (2022).

    Article  Google Scholar 

  9. Sberro, H. et al. Cell 178, 1245–1259.e14 (2019).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Cesar de la Fuente-Nunez

  2. Departments of Bioengineering and Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA

    Cesar de la Fuente-Nunez

  3. Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA, USA

    Cesar de la Fuente-Nunez

Authors
  1. Cesar de la Fuente-Nunez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cesar de la Fuente-Nunez.

Ethics declarations

Competing interests

The author declares no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de la Fuente-Nunez, C. Antibiotic discovery with machine learning. Nat Biotechnol 40, 833–834 (2022). https://doi.org/10.1038/s41587-022-01327-w

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41587-022-01327-w

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research