ESKAPEing the labyrinth of antibacterial discovery

Journal name:
Nature Reviews Drug Discovery
Year published:
Published online
Corrected online
Corrected online


Antimicrobial drug resistance is a growing threat to global public health. Multidrug resistance among the 'ESKAPE' organisms — encompassing Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp. — is of particular concern because they are responsible for many serious infections in hospitals. Although some promising agents are in the pipeline, there is an urgent need for new antibiotic scaffolds. However, antibacterial researchers have struggled to identify new small molecules with meaningful cellular activity, especially those effective against multidrug-resistant Gram-negative pathogens. This difficulty ultimately stems from an incomplete understanding of efflux systems and compound permeation through bacterial membranes. This Opinion article describes findings from target-based and phenotypic screening efforts carried out at AstraZeneca over the past decade, discusses some of the subsequent chemistry challenges and concludes with a description of new approaches comprising a combination of computational modelling and advanced biological tools which may pave the way towards the discovery of new antibacterial agents.

At a glance


  1. Mean LogD values for internal AstraZeneca antibacterial project compounds and for exemplar hits from other disease areas.
    Figure 1: Mean LogD values for internal AstraZeneca antibacterial project compounds and for exemplar hits from other disease areas.

    The mean LogD values were calculated at pH 7.4 using AstraZeneca internal software that was parameterized on a continual basis using new data. Error bars indicate the 99% confidence interval for the mean of calculated LogD values for each category on the x axis. a | The mean LogD values for active compounds targeting 10 key pathogens are indicated by yellow diamonds, and the number of active compounds (n) with a minimum inhibitory concentration (MIC) ≤8 μg mL−1 is indicated in parentheses. The mean LogD values of inactive compounds (MIC >64 μg mL−1) are indicated by red hexagons. The mean of a random sample of 45,000 compounds from the AstraZeneca screening collection is shown for reference. b | The mean LogD values for hits from ten representative high-throughput screens are indicated by green circles, and the number of hits (n) included in the analysis is indicated in parentheses. A. baumannii, Acinetobacter baumannii; AccA, acetyl-CoA carboxyltransferase α-subunit; AccC, biotin carboxylase; AccD, acetyl-CoA carboxyltransferase β-subunit; CoaD, phosphopantetheine adenylyltransferase; E. coli, Escherichia coli; FabH, β-ketoacyl-(acyl carrier protein) synthase III; H. influenzae, Haemophilus influenzae; K. pneumoniae, Klebsiella pneumoniae; LigA, DNA ligase; MurC, uridine diphosphate (UDP)-N-acetylmuramate-L-alaninetransferase; P. aeruginosa, Pseudomonas aeruginosa; ParE, topoisomerase IV; PyrH, uridine monophosphate (UMP) kinase; S. aureus, Staphylococcus aureus; S. pneumoniae, Streptococcus pneumoniae; S. pyogenes, Streptococcus pyogenes; Tmk, deoxy-thymidine monophosphate (dTMP) kinase; TrmD, tRNA (guanine37-N1)-methyltransferase.

  2. The relationship over time between the biochemical potency against Pseudomonas aeruginosa MurC and the cLogD of newly synthesized programme compounds.
    Figure 2: The relationship over time between the biochemical potency against Pseudomonas aeruginosa MurC and the cLogD of newly synthesized programme compounds.

    As chemists were designing and synthesizing compounds over the course of the project (shown as sequential compound registrations on the x axis) the most potent examples trended towards having a high hydrophobicity (dark red squares). Efforts to reduce the hydrophobicity were generally met with reduced biochemical potency (green squares). The molecules are grouped by hydrophobicity, as measured by 'computed' LogD (cLogD) values, calculated using AstraZeneca's proprietary predictive model, AZlogD7.4, as indicated in the key.

  3. Gram-negative and Gram-positive cell walls.
    Figure 3: Gram-negative and Gram-positive cell walls.

    Gram-negative bacteria rely on both an inner and an outer membrane surrounding a thin peptidoglycan matrix and a periplasmic space (part a), whereas Gram-positive bacteria generally use a thicker peptidoglycan layer to protect a single cytoplasmic membrane (part b)27. Transport of antibiotics and other extracellular compounds across bacterial membranes occurs both actively and passively, depending on the nature of the transporter. There are numerous components associated with both types of cell walls that limit the ability of antibiotics to penetrate these structures, such as efflux pumps that expunge toxins, defensive enzymes, such as β‑lactamases, and complex carbohydrate networks that create a protective capsule coating. Integral and peripheral membrane proteins are shown in light and dark green, respectively. LPS, lipopolysaccharide; LTA, lipoteichoic acid; WTA, wall teichoic acid.

  4. Effect of porin point mutations on antibiotic transport.
    Figure 4: Effect of porin point mutations on antibiotic transport.

    Crystal structure of the porin OccD1 (Protein Data Bank identifier: 3SY7)6, 30, illustrating the effect of point mutations in the porin on translocation of meropenem36. The locations of the point mutations are indicated by white boxes, and the effects of the point mutations are colour coded: red indicates a reduction in permeability, yellow indicates no effect and green indicates an increase in permeability.

Accession codes

Referenced accessions

Protein Data Bank

Change history

Corrected online 14 July 2015
In reference 67 the journal name was incorrect. It has now been corrected online and in print.
Corrected online 14 August 2015
In the legend of Figure 3, Gram-negative and Gram-positive bacteria were incorrectly labelled. This has been corrected in the online version of the article.


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Author information


  1. Entasis Therapeutics, 35 Gatehouse Drive, Waltham, Massachusetts 02451, USA.

    • Ruben Tommasi &
    • Alita A. Miller
  2. AstraZeneca Pharmaceuticals, 35 Gatehouse Drive, Waltham, Massachusetts 02451, USA.

    • Dean G. Brown
  3. Agios Pharmaceuticals, 88 Sidney Street, Cambridge, Massachusetts 02139, USA.

    • Grant K. Walkup
  4. Novartis Institute for BioMedical Research, 186 Massachusetts Avenue, Cambridge, Massachusetts, USA.

    • John I. Manchester

Competing interests statement

All authors are current or former employees of AstraZeneca and, as such, may hold stock in the company.

Corresponding author

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Author details

  • Ruben Tommasi

    Ruben Tommasi obtained his doctorate degree in organic chemistry from the State University of New York–Albany, USA, in 1992, with Frank M. Hauser. He spent a year at the University of Colorado Boulder, USA, with Gary Molander and was subsequently a post-doctoral fellow at Upjohn, Kalamazoo, Michigan, USA, where his work on the dihydropyrone class of HIV protease inhibitors ultimately lead to the discovery of Tipranavir. In 1994, he joined Ciba-Geigy (now Novartis) as a medicinal chemist where he worked in several therapeutic areas including arthritis, bone metabolism and infection. During his 17-year tenure at Novartis, he had the opportunity to build a new chemistry team dedicated to hit-to-lead optimization and chemogenetics as well as lead the infectious disease chemistry team. He successfully led his teams to advance two candidates to Phase II clinical studies (Hepatitis C virus protease inhibitor, BZF961, and EF-Tu inhibitor for Clostridium difficile, LFF571). In 2011, he joined AstraZeneca to lead the infection chemistry team, where he led teams that advanced a clinical candidate (ETX0914 for the treatment of gonorrhoea) as well as a new early portfolio of programmes. In May of 2015, Ruben became the Chief Scientific Officer at Entasis Therapeutics, AstraZeneca's new antibacterial spin-out company. One of his main interests is to develop a better understanding of the factors that affect drug permeation into Gram-negative organisms. He is the co-author of 33 papers and co-inventor of 12 patents. Ruben Tommasi homepage.

  • Dean G. Brown

    Dean G. Brown is currently the Director of Infection Chemistry at AstraZeneca Pharmaceuticals. He obtained a B.Sc. in chemistry at Abilene Christian University, Texas, USA, and a Ph.D. at the University of Minnesota, Minneapolis, USA, in organic chemistry. While at AstraZeneca, he has been responsible for building many new scientific programmes in both neuroscience and infection, several which have resulted in successful transition to clinical trials. His scientific interests are in lead generation, library design and medicinal chemistry. He is listed as an author or co-author on more than 40 publications and patent applications in medicinal chemistry and drug design, including granted patents on clinical candidates.

  • Grant K. Walkup

    Grant K. Walkup has over a decade of experience conducting and leading anti-infective drug discovery projects from the lead discovery stages through to selection of candidates for development. During this time, he has developed or overseen ~80 screens covering the gamut of target-, phenotypic-, virtual-, fragment- and pharmacophore-based approaches. His research interests include bioorganic chemistry, chemical biology and elucidating the structural and kinetic factors that underlie the selective engagement of biological targets by small molecules. He has more than 20 peer reviewed publications and several patents, and he is a frequent reviewer for several widely-read journals. He received a B.Sc. in chemistry from The University of California, San Diego (UCSD), USA. He completed a doctorate in organic chemistry (with honours) from the California Institute of Technology, Pasadena, USA, studying with Barbara Imperiali designing selective fluorescent chemosensors. He continued post-doctoral studies as a US National Institutes of Health and Howard Hughes Medical Institute Fellow with Roger Tsien at UCSD. He presently holds the positions of Associate Director of Enzymology at Agios Pharmaceuticals in Cambridge, Massachusetts, USA, and Adjunct Professor at Stony Brook University, New York, USA.

  • John I. Manchester

    John I. Manchester led the computer-aided drug design group in infection at AstraZeneca Pharmaceuticals, and for many years sought relationships between the physical properties of small molecules and their antibacterial activity, until the revolution in graphics processing unit (GPU)-enabled computing made it possible to study the interactions between small molecules and bacterial membrane components at atomic resolution. His background is in modelling drug metabolism using high-performance computing and machine learning. He is author of more than 25 publications and an inventor on several patents. He is presently a senior scientific informatics lead for biology research platforms at Novartis Institutes for BioMedical Research in Cambridge, Massachusetts, USA.

  • Alita A. Miller

    Alita A. Miller holds a B.A. in chemistry from Kalamazoo College, Michigan, USA, and a Ph.D. in biochemistry and molecular biology from the University of Chicago, Illinois, USA. Her postdoctoral training focused on the molecular drivers of bacterial pathogenesis in the laboratory of Victor DiRita at the University of Michigan, USA. The main focus of her career has been on antibacterial preclinical discovery with positions held at Pharmacia, Pfizer and AstraZeneca. She is currently Director and Head of Biology at Entasis Therapeutics. Among her research interests are novel approaches to antibacterial discovery, including new ways of characterizing antibiotic penetration across bacterial membranes. She serves on several US National Institutes of Health review panels for proposals related to the field. She has over 30 publications and recently co-edited a textbook on emerging trends in antibacterial discovery.

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