[go: up one dir, main page]
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.

  • Review Article
  • Published:

Drugs for bad bugs: confronting the challenges of antibacterial discovery

Nature Reviews Drug Discovery volume 6, pages 29–40 (2007)Cite this article

Key Points

  • Despite the well-recognized medical need for new antibiotics, there has been a marked decrease in antibacterial drug discovery, with many companies leaving the area. In addition to the regulatory requirements and competitive commercial environment, which pose significant barriers to investment, there are scientific hurdles to making novel antibacterials that are underappreciated.

  • Bacterial genome sequencing and analysis has greatly enhanced our understanding of evolution and bacterial physiology. In the mid-1990s, many in the scientific community and pharmaceutical industry believed that this knowledge was going to translate into a new generation of antibacterial drugs that acted by novel mechanisms.

  • GlaxoSmithKline (GSK) embraced this 'genomics' approach to antibacterial discovery, using bioinformatic analysis of genomic information to identify target genes, testing the importance of these genes to bacterial viability by genetic means and finally screening compound collections against the target gene product for inhibitor compounds. GSK scientists validated hundreds of candidate genes and ran more than 70 high-throughput screening (HTS) campaigns between 1995–2001.

  • Blind spots in target validation and an inability to find lead compounds from HTS together with the larger problem of making a single compound that has broad-spectrum activity and is safe at the high serum concentrations needed to cover the least susceptible organisms have left an empty industrial antibacterial portfolio. Eleven years after the first bacterial genome was sequenced, there is still not a single agent in the industrial pipeline that can be construed as being derived from genomic efforts.

  • GSK has found that optimizing novel chemical structures that inhibit highly validated targets for drug-like properties is a more promising, if less trendy, route. Since 2002, our strategy has been to invest heavily in a select number of programmes, with large teams of chemists synthesizing drug-like compounds and with biologists focused on accelerating the critical path pharmacology and microbiological efficacy studies for each new compound synthesized.

  • This approach has produced more novel mechanism antibacterial development candidates at GSK in the past 4 years than in the previous 20. However, high attrition rates in clinical development demand a broader industrial involvement and more aggressive research efforts to assure novel mechanism agents for the future.

Abstract

The sequencing of the first complete bacterial genome in 1995 heralded a new era of hope for antibacterial drug discoverers, who now had the tools to search entire genomes for new antibacterial targets. Several companies, including GlaxoSmithKline, moved back into the antibacterials area and embraced a genomics-derived, target-based approach to screen for new classes of drugs with novel modes of action. Here, we share our experience of evaluating more than 300 genes and 70 high-throughput screening campaigns over a period of 7 years, and look at what we learned and how that has influenced GlaxoSmithKline's antibacterials strategy going forward.

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

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Figure 1: Estimated success metrics and timelines for the development of a systemic broad-spectrum antibacterial.
Figure 2: Method for testing gene essentiality.
Figure 3: Results of gene essentiality testing in Streptococcus pneumoniae.
Figure 4: The chemical diversity of antibacterials is different to other drugs.

Similar content being viewed by others

References

  1. House of Lords Select Committee on Science and Technology Seventh Report. Resistance to Antibiotics and Other Antimicrobial Agents [online], (Stationary Office, London, UK, 1998).

  2. Shlaes, D. M. et al. Antibiotic discovery: state of the state. ASM News 70, 275–281 (2004).

    Google Scholar 

  3. Talbot, G. H. et al. Bad bugs need drugs: an update on the development pipeline from the antibacterial availability task force of the IDSA. Clin. Infect. Dis. 42, 657–668 (2006).

    Article  Google Scholar 

  4. Wenzel, R. P. The antibiotic pipeline — challenges, costs, and values. N. Engl. J. Med. 351, 523–526 (2004).

    Article  CAS  Google Scholar 

  5. Infectious Disease Society of America. Bad Bugs, No Drugs [online], (2004). Seminal review by key opinion leaders on the shrinking investment by big pharma in antibacterial discovery, and the growing challenge of resistant pathogens.

  6. Tickell, S. The Antibiotic Innovation Study: Expert Voices on a Critical Need [online], (2005).

  7. Nathan, C. Antibiotics at the cross roads. Nature 431, 899–902 (2004).

    Article  CAS  Google Scholar 

  8. Kaplan, W. & Laing, R. Priority Medicines for Europe and the World [online], (World Health Organization, Geneva, 2004).

    Google Scholar 

  9. Brown, J. R. & Warren, P. V. Antibiotic discovery: is it in the genes? Drug Discov. Today 3, 564–566 (1998).

    Article  Google Scholar 

  10. Chan, P. F., Macarron, R., Payne, D. J., Zalacain, M. & Holmes, D. J. Novel antibacterials: a genomics approach to drug discovery. Curr. Drug Targets — Infect. Dis. 2, 109–119 (2002).

    Article  Google Scholar 

  11. Chan, P. F. et al. Characterization of a noval fucose-regulated promoter (PfcsK) suitable for gene essentiality and antibacterial mode of action studies in Streptococcus pneumoniae. J. Bacteriol. 185, 2051–2058 (2003).

    Article  CAS  Google Scholar 

  12. Zhang, L. et al. Regulated gene expression in Staphylococcus aureus for identifying conditional lethal phenotypes and antibiotic mode of action. Gene 255, 297–305 (2000).

    Article  CAS  Google Scholar 

  13. Yin, D. et al. Identification of Antimicrobial targets using a comprehensive genomic approach. Pharmacogenomics 5, 101–113 (2004).

    Article  CAS  Google Scholar 

  14. Zalacain, M. et al. A global approach to identify novel broad-spectrum antibacterial targets among proteins of unknown function. J. Mol. Microbiol. Biotechnol. 6, 109–126 (2003).

    Article  CAS  Google Scholar 

  15. Jarvest, R. L., et al. Nanomolar inhibitors of Staphylococcus aureus methionyl tRNA synthetase with potent antibacterial activity against Gram-positive pathogens. J. Med. Chem. 45, 1959–1962 (2002).

    Article  CAS  Google Scholar 

  16. Payne, D. J. et al. Discovery of a novel and potent class of FabI directed antibacterial agents. Antimicrob. Agents Chemother. 46, 3118–3124 (2002).

    Article  CAS  Google Scholar 

  17. Fan, F. et al. Defining and combating the mechanisms of triclosan resistance in clinical isolates of Staphylococcus aureus. Antimicrob. Agents Chemother. 46, 3343–3347 (2002).

    Article  CAS  Google Scholar 

  18. Aubert, K. & Zalacain, M. 3 Peptide deformylase inhibitors. Prog. Med. Chem. 44, 109–143 (2006).

    Article  Google Scholar 

  19. Gentry, D. R. et al. Variable sensitivity to bacterial methionyl-tRNA synthetase inhibitors reveals subpopulations of Streptococcus pneumoniae with two distinct methionyl-tRNA synthetase genes. Antimicrob. Agents Chemother. 47, 1784–1789 (2003). An example illustrating the risk associated with exploitation of non-clinically validated targets for antibacterial discovery.

    Article  CAS  Google Scholar 

  20. Du, W. et al. Two active forms of UDP-N-acetylglucosamine enolpyruvyl transferase in Gram-positive bacteria. J. Bacteriol. 182, 4146–4152 (2000).

    Article  CAS  Google Scholar 

  21. Heath, R. J. & Rock, C. O. A triclosan-resistant bacterial enzyme. Nature 406, 145 (2000).

    Article  CAS  Google Scholar 

  22. Payne, D. J., Gwynn, M. N., Holmes, D. J. & Rosenberg, M. Genomic approaches to antibacterial discovery. Methods Mol. Biol. 266, 231–259 (2004).

    CAS  PubMed  Google Scholar 

  23. Andries, K. et al. A diarylquinoline drug active on the ATP synthase of Mycobacterium tuberculosis. Science 307, 223–227 (2005).

    Article  CAS  Google Scholar 

  24. Heerding, D. A. et al. New benzylidenethiazolidine-doines as antibacterial agents. Bioorg. Med. Chem. Lett. 13, 3771–3773 (2003).

    Article  CAS  Google Scholar 

  25. Chan, P. F. et al. Finding the gems using genomic discovery: antibacterial drug discovery strategies — the successes and the challenges. Drug Discov. Today: Ther. Strategies 1, 519–527 (2004)

    CAS  Google Scholar 

  26. Pace, N. R. A molecular view of microbial diversity and the biosphere. Science 276, 734 (1997).

    Article  CAS  Google Scholar 

  27. Wong, K. K. et al. Engineering a cell-free murein biosynthetic pathway: combinatorial enzymology in drug discovery. J. Am. Chem. Soc. 120, 13527–13528 (1998).

    Article  CAS  Google Scholar 

  28. DeVito, J. A. et al. An array of target-specific screening strains for antibacterials discovery. Nature Biotechnol. 20, 478–483 (2002).

    Article  CAS  Google Scholar 

  29. Wong, K. K. & Pompliano, D. L. in Resolving the Antibiotic Paradox: Progress in Understanding Drug Resistance and Development of New Antibiotics (eds Rosen, B. P. & Mobashery, S.) (Plenum, New York, 1999)

    Google Scholar 

  30. Feher, M. & Schmidt, J. M. Property distributions: differences between drugs, natural products, and molecules from combinatorial chemistry. J. Chem. Inf. Comput. Sci. 43, 218–227 (2003).

    Article  CAS  Google Scholar 

  31. Lipinski, C. A., Lombardo, F., Dominy, B. W. & Feeney, P. J. Experimental and computional approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 23, 3–25 (1997).

    Article  CAS  Google Scholar 

  32. Walsh, C. T. Combinatorial biosynthesis of antibiotics: challenges and opportunities. Chembiochem 3, 125–134 (2002)

    Article  Google Scholar 

  33. Throup, J. P. et al. A genomic analysis of two-component signal transduction in Streptococcus pneumoniae. Mol. Microbiol. 35, 566–576 (2000).

    Article  CAS  Google Scholar 

  34. Ji. Y. et al. Identification of critical staphylococcal genes using conditional phenotypes generated by antisense RNA. Science 293, 2266–2269 (2001)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank the numerous scientists from all parts of GSK who have contributed to the data discussed in this review and thank C. Edge (GSK, Molecular Discovery Research) for figure 4.

Author information

Authors and Affiliations

  1. Infectious Diseases Centre of Excellence for Drug Discovery, GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, 19426, Pennsylvania, USA

    David J. Payne, Michael N. Gwynn, David J. Holmes & David L. Pompliano

Authors
  1. David J. Payne
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael N. Gwynn
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David J. Holmes
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. David L. Pompliano
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David L. Pompliano.

Ethics declarations

Competing interests

D.J.P, M.N.G., D.J.H. and D.L.P. are employees of GlaxoSmithKline, which is involved in the discovery and commercialization of therapeutics for the treatment of antibacterial infections.

Related links

Related links

FURTHER INFORMATION

Centers for Medicines Research

Drugs @ FDA

Glossary

Antibacterial development candidate

A compound that achieves target antibacterial activity in vitro (MIC90s) and in vivo (infection models), shows a viable therapeutic window based on rodent toxicity, and has physical and pharmaceutical properties suitable for preclinical GLP toxicology studies.

Paramecia

Freshwater protozoa of the genus Paramecium with an oral groove for feeding.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Payne, D., Gwynn, M., Holmes, D. et al. Drugs for bad bugs: confronting the challenges of antibacterial discovery. Nat Rev Drug Discov 6, 29–40 (2007). https://doi.org/10.1038/nrd2201

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrd2201

This article is cited by

Search

Advanced 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