Antibacterial Drug Discovery: Some Assembly Required - ACS

Subscriber access provided by - Access paid by the | UCSB Libraries

Perspective

Antibacterial Drug Discovery: Some Assembly Required Ruben Tommasi, Ramkumar Iyer, and Alita A Miller ACS Infect. Dis., Just Accepted Manuscript • DOI: 10.1021/acsinfecdis.8b00027 • Publication Date (Web): 27 Feb 2018 Downloaded from http://pubs.acs.org on March 2, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

ACS Infectious Diseases is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Infectious Diseases

Title:

Antibacterial Drug Discovery: Some Assembly Required

Authors:

Rubén Tommasi*, Ramkumar Iyer and Alita A. Miller

Mailing address:

Entasis Therapeutics, Inc. , 35 Gatehouse Drive, Waltham MA 02451

*Corresponding author: [email protected]

Our limited understanding of the molecular basis for compound entry into and efflux out of Gram-negative bacteria is now recognized as a key bottleneck for the rational discovery of novel antibacterial compounds. Traditional, large-scale biochemical or target-agnostic phenotypic antibacterial screening efforts have, as a result, not been very fruitful. A main driver of this knowledge gap has been the historical lack of predictive cellular assays, tools, and models that provide structure-activity relationships to inform optimization of compound accumulation. A variety of recent approaches have recently been described to address this conundrum. This perspective explores these approaches and considers ways in which their integration could successfully redirect antibacterial drug discovery efforts.

Keywords: novel antibacterials, permeation, efflux, drug discovery, accumulation, rules of uptake

ACS Paragon Plus Environment

ACS Infectious Diseases 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 2 of 26

There has been increased attention to the challenges of antimicrobial resistance over the last few years, with significant improvements made in the economic and regulatory landscapes that pave the way for progress in this space. In recent years, the Innovative Medicines Initiative in Europe followed by the creation of CARB-X as a global initiative have helped ameliorate the economic challenges to discover and develop novel antibacterials 1. Furthermore, the new regulatory RoadMap that has been championed recently provides several paths to registration for novel therapies to make their way to the many patients that so desperately need them 2. However, we are still a long way from having this significant global threat under control. This is due to a number of factors including additional economic

3-4

, regulatory

5-7

and

scientific 8-9 challenges. A robust pipeline of therapies targeting novel mechanisms of action is still lacking, despite specific investments made by various large pharmaceuticals to achieve this goal. In particular, novel therapies to address multi-drug resistant Gram-negative pathogens are needed, which is especially challenging due to the complexity of the dual membranes in these bacteria (Figure 1). Although highthroughput screening approaches identified numerous biochemical hits for some genetically validated targets, the conversion of these hits to advanced Lead Compounds was found to be a rare event, and clinical candidates have not emerged from these major investments. Possible approaches to address these challenges has been discussed and reviewed extensively over the last few years 10-13 including the development of a RoadMap by Pew Trusts with input from many thought leaders in the antibacterial space 14

.


Page 3 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 1. Multiple defense mechanisms encompassed within the Gram-negative bacterial cell envelope make new antibiotic discovery extremely challenging.

The magnitude of the problem Having worked on dozens of antibacterial programs for more than a decade, one of our major frustrations is the fact that we have not been able to learn from one program to the next how to achieve better cellular activity. Approaches, such as altering physicochemical properties (Molecular weight., logD, Hydrogenbond donors or acceptors, positive or negative charges), that help progress one program or chemical series do not appear to help the next. A great example of this is illustrated by an experience during a medicinal chemistry portfolio review we had across the antibacterial programs at AstraZeneca in 2011. At the time, there were three projects which were exploring chemical property space to improve the minimal inhibitory concentrations (MICs) required to inhibit bacterial growth for their programs. All had potent biochemical activity against their targets with IC50 values well below 100 nM and the discussion of the day was ‘lowering logD’. This would be addressed by introduction of polar substituents, both positively charged and uncharged. When the naïve question was asked of the three team leaders as to



where the logD ‘sweet spot’ was for their program (e.g. at what logD did they believe their compounds were the most active against the same Gram-negative pathogens), they each answered a different value! One interpretation of that discussion could be that each of the series were utilizing a different mechanism or mode of uptake. Unfortunately, we never had the opportunity to test that hypothesis. That experience, along with similar ones from earlier programs, have since motivated us to build an understanding of factors that influence uptake and efflux in addition to biochemical potency. We, along with many others in the field, realized the strategy of improving the target IC50 with the hope that eventually a better MIC would follow was fundamentally flawed: sadly, hope is not a strategy. Therefore, we have begun to focus on identifying ways of addressing the cellular accumulation problem using a variety of methods that may ultimately provide workarounds for this conundrum. This perspective seeks to explore these approaches, considers both their strengths and challenges and shares a vision for how we may be able to assemble all the available methods together into an improved strategy for antibacterial drug discovery. Overview of Large Screening Efforts Two comprehensive summaries of screening efforts have been published by GlaxoSmithKline and AstraZeneca

9, 15

. It is clear from the results of these efforts that, despite large investments in Pharma

towards the discovery of antibacterial compounds with novel mechanisms of action, the identification of new agents using large screening approaches has not panned out. Furthermore, a key challenge highlighted through these approaches is that we were not able to apply learnings from optimization against one target towards another. An alternate approach to address these challenges was to leverage phenotypic screens using outer membrane barrier- or efflux-compromised strains to increase chances of success. While these screens did in fact identify hits, there were two issues that emerged. The modes of action of many were not novel and the path to optimization of these hits to analogs with wild type activity


Page 4 of 26

Page 5 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


was still refractory (likely due to issues with uptake and efflux). Variations of this approach utilizing pathway-specific sensitized strains have also been attempted 16-17. Unfortunately, these approaches were equally disappointing in identifying viable leads likely for similar reasons. Physicochemical Properties – Is this the answer? The challenges highlighted in the reviews of large screening efforts as well as the obvious lack of novel agents has prompted researchers to investigate whether or how the physicochemical properties of compounds dictate antibacterial activity and, more importantly, whether large commercial or Pharmabased screening collections contain compounds which are likely to be in the “Physicochemical Property Space” consistent with established antibacterials. This concept was catalyzed by O’Shea and Moser 18 with a physicochemical property analysis of all marketed antibacterials and comparing them with compounds found in screening collections as well as marketed drugs for other indications. The conclusion from this analysis was that antibacterials are both larger and more polar than the average values for screening collections. Thus, high throughput screening (HTS) efforts interrogating these large libraries are less likely to identify novel hits. This realization has prompted many to seek “Permeability Rules” similar to what Lipinski published as guidelines to increase the likelihood of human absorption 19. This is going to be a challenging endeavor as the permeation of small molecules into the large diversity of Gram-negative pathogens is much more disparate in its needs than the relative similarity of achieving good absorption characteristics in a single species (i.e., human). It is clear from the vast diversity of chemical structures that we already know are capable of permeating certain Gram-negative pathogens that the challenge in this space is significantly broader. Take for example the structural diversity between argyrin B and the relatively small β-lactam ampicillin as illustrated in Figure 2. While argyrin B appears to permeate P. aeruginosa well enough based on its MIC to enter the cytoplasm and reach its target Elongation factor-g (EF-g) 20, ampicillin struggles to reach sufficient concentrations even in the P. aeruginosa periplasm to inhibit its PBP targets. While macrocycles can adopt a variety of conformations which may allow argyrin-



B to present several structural features during its permeation through membranes 21,22, it is disconcerting to the antibacterial drug designer that we don’t have a clear understanding of how it accomplishes this feat and what structural features drive this permeation, much less how to apply this to other chemical scaffolds. In fact, a mechanism of uptake for argyrin-B has not been elucidated, illustrating just how little we know about these phenomena. In contrast to ampicillin, the small and negatively charged avibactam permeates into the periplasm effectively enough to broadly inhibit β-lactamases in P. aeruginosa as well as E. coli and K. pneumoniae based on its ability to potentiate ceftazidime in these pathogens. 23 ETX2514 (Figure 3), a clinical candidate in the same chemical class as avibactam (with expanded spectrum to include inhibition of Class-D β-lactamases) also permeates effectively into A. baumannii as demonstrated by its ability to potentiate sulbactam. 24 Despite the successful discovery and development of these new agents, we still know very little about what structural factors drive accumulation and in fact we know very little about the actual rate of permeation of any of these compounds. A few years ago, we performed a retrospective analysis of the physicochemical properties of ∼3200 antibacterial project compounds with whole cell activity against either Gram-negative or Gram-positive pathogens compared to those of the hits found from 23 high throughput screens (HTS) conducted on either biochemical or phenotypic bacterial targets

25

. Overall, we found that the HTS actives were

significantly more hydrophobic than antibacterial project compounds with higher average clogDs. Further analyses revealed that lead identification programs often increased hydrophobicity with increased biochemical potency, making the separation even larger between the physicochemical properties of known antibacterial agents and the HTS active starting point, resulting in higher probability of plasma protein binding and cytotoxicity. We also found that cell-based activity in Gram-negative bacteria was severely limited or, if present, demonstrated significant efflux. Compounds least susceptible to efflux were those which were highly polar and small in MW or very large and typically zwitterionic. Hydrophobicity was often the dominant driver for HTS actives but, more often than not, precluded whole


Page 6 of 26

Page 7 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


cell antibacterial activity. However, simply designing polar compounds was not sufficient to achieve antibacterial activity. These learnings were recently challenged by Hergenrother and colleagues based on the findings from a prospective assessment of the accumulation of 180 chemically diverse compounds in E. coli using LCMS/MS

26

. Results from this study suggested that the key features required for small molecules to

permeate and remain in E. coli were high rigidity and amphilicity, low globularity and the presence of a primary amine. The authors successfully applied these guidelines to broaden the spectrum of the Grampositive-specific, natural product deoxynybomyxin, adding activity against several Gram-negative bacteria (Figure 2, compounds 4 and 5). While encouraging, numerous examples in the literature, such as those described above, clearly show there are many exceptions to these minimal guidelines. These disparities highlight our lack of understanding of the complexity of physical properties and molecular mechanisms driving the permeation of small molecules across bacterial envelopes. Molecular Drivers of Compound Uptake The compound class for which we understand the most with respect to uptake is the carbapenems. Some of the earliest clinical resistance to carbapenems in P. aeruginosa was found to be due to mutations in the outer membrane channel, OprD 27, implicating this porin in carbapenem uptake into the periplasm. Inactivation or downregulation of OprD in P. aeruginosa resulted in abrogated antibacterial activity in lab strains as well 28. However, to date this has been the only class of compounds to elicit this phenotype in response to loss of porin function, even when multi-porin knockout strains were tested 29. Generally, the use of individual or multiple porin knock out strains has not been as useful probably due to the existence of redundant modes of uptake which is not easily discernable using this approach. This highlights the difficulty in understanding the structural requirements that drive compound permeation across the Gramnegative outer membrane.



Figure 2 – A brief illustration of representative structures that permeate Gram-negative pathogens. 1 permeates well into P. aeruginosa. Despite the smaller size, 2 accumulates well into E. coli, but not P. aeruginosa. 3 lacks any positive charge but does permeate well into E. coli, K. pneumoniae and P. aeruginosa. 4 lacks activity in Gram-negative species while addition of a primary amine to generate 5 provides activity in E. coli.

Figure 3 – Meropenem and structurally related analogs containing side-chain variations which hamper (7) or enhance (8) uptake via OprD

Figure 4 – ETX2514 (9) and structurally related analogs containing methyl substituents which either improve (11) or hamper (10) permeation via OmpA


Page 8 of 26

Page 9 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Research into the structural features required for uptake and the various mechanisms involved has been ongoing for nearly three decades beginning with the seminal work of Nikaido 30 and Hancock 31. Nikaido demonstrated nicely in E. coli that rate of permeation into the periplasm could be calculated for β-lactam compounds by using the rate of hydrolysis by endogenous AmpC 32. With these efforts, Nikaido was clearly able to show that permeation into E. coli cells was a process driven by passive permeation through outer membrane porins (mostly OmpC) 33. In further work, Nikaido has shown that the permeability of small molecules across the outer membrane barrier of P. aeruginosa is significantly (100-fold) slower than across E. coli membranes

34

. Hancock has clearly illustrated that small molecule permeation into P.

aeruginosa is facilitated by small, substrate-specific porins (such as OprD) and that P. aeruginosa is lacking the larger, general porins such as those found in E. coli 31, 35-36. As a result of these early efforts, great attention has been given to the structural elucidation of many of these porins, primarily from van den Berg and coworkers 37-38. The emergence of these crystal structures has prompted several groups to begin study of their structural features and potential elements of recognition and thus permeation. There has been great progress in this area despite the intense computational efforts that are required for these studies. Computational study of permeation is distinct from traditional structure based design as we are not simply seeking to accurately measure binding. Instead, Molecular Dynamics simulations are used to explore the potential trajectories that small molecules may take to traverse these pores which could lead to an understanding of the structural features that contribute to substrate recognition and permeation. The computational effort required to accomplish these calculations is significantly more time consuming than traditional structure-based drug design, and that has made progress in this area challenging. Despite these challenges, some important observations have already emerged.

Ceccarelli and co-workers have

demonstrated that changes in the electric field in the constriction zone of mutated OmpC in E. coli impacts the ability of imipenem and meropenem to traverse the porin 39. These results suggest that the proper



Page 10 of 26

placement of charges in a molecule without consideration of the effects on the dipole moment and its ability to line up with the requirements of uptake would not be an optimal approach to improve antibiotic entry. Nevertheless, without the detailed understanding of what structural features are required for optimal permeation, we will need to make libraries which systematically vary number of charges and location to generate the SAR required to inform us. Certainly, this is already clear from the available structures of P. aeruginosa porins which have now been divided into two major families: OccD and OccK, based on their substrate preferences. Although both families of porins contain an arginine ladder, the OccD family recognizes substrates with positive charges (e.g., arginine, lysine)

40

and the OccK family

recognizes negatively charged substrates such as pyroglutamate and phenylacetate as well as aztreonam 41

. Electrophysiology has been used to help elucidate uptake through various porins and changes in ion

flux can be readily measured in these systems 42,43,44,45. Recent advances in automated patch-clamp and bilayer technologies based on a chip have been enabling in this area 46. However, correlating ion flux alterations to structural features that affect compound accumulation in the cells may not be straightforward. The need for higher salt concentrations in recordings to sensitively measure current fluctuations and the use of antibiotic concentrations in the millimolar range which are not physiologically relevant could complicate the interpretation of ion flux changes. Finally, the indirect nature of the measurement i.e., changes in ion flux by addition of small molecules is another complicating feature to this type of analysis. Interference of flux may or may not require actual permeation of the small molecule through the pore, rather just blocking the constriction zone reversibly could affect the measurements. Regardless, the approach is valuable and provides an orthogonal method to quantifying the role of individual porins in permeation of compounds of interest 42. Further research in this area is still required to make this structurally informative to the drug designer and efforts are ongoing. Even though our internal research interests are focused on small molecule permeation, we would be remiss if we did not acknowledge the extent to which bacterial efflux systems exacerbate the challenges


Page 11 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


of small molecule antibacterial discovery, especially due to their diversity and complexity.

Not

surprisingly, as much if not more research over the decades has been devoted to similar studies on the molecular drivers of antibiotic efflux, including structural characterization of many prototypical members of various transporter families 47,48,49,50 and inhibitor-efflux pump co-crystal structures 51 52. More recent efforts include molecular dynamic simulations studies on several of these (see for example Wang et al. (2015)53 and Cacciotto et al. (2018) 54). As we could not do justice to the work of many talented experts in the field, for those readers interested in learning more, we would recommend several recent reviews 55,56,57,58,59

, as well as a particularly comprehensive recent textbook edited by Zgurskaya and colleagues 60.

Mathematical modeling approaches represent an alternative to the computationally intensive Molecular Dynamic study of porin permeation and/or antibiotic efflux. This approach could provide quantitative methods to compare compounds where ultimately the effects of influx and efflux could be calculated across a series of compounds. Initial approaches towards this modeling were built upon the premise that uptake into cells was driven by passive diffusion and thus these should obey Fick’s Law 33,61. More recently, an alternative which provides a more general approach was reported by Zgurskaya, Rybenkov and coworkers that may provide insight in situations where uptake is not driven by passive diffusion and it also considers target potency as well as the effects of efflux 62. The model depends on two parameters to account for the rate of uptake and efflux. By including these two parameters together, the model allows for analysis of the non-linearity of accumulation. This is nicely exemplified by the fitting for the uptake of the bis-benzimide Hoechst 33342, a fluorescent topoisomerase inhibitor which is amenable to uptake studies, in wild type cells as well as cells which expressed a mutant, hyper-porinated variant of FhuA (as discussed below). It will be interesting to see how this model may be applied in other cases, in particular for non-fluorescent compounds. It will be especially useful to consider these mathematical models as more information for accumulation of compounds becomes available from Mass Spectroscopy or other



quantitative measurements. The structure-accumulation and structure-efflux relationships generated from these two accumulation parameters should be critical in this context. Taken together, these learnings should dissuade us from seeking an over-arching single principle based solely on physical or structural properties to discover novel broad-spectrum agents. Thus, rather than establishing ‘rules’ for Gram-negative permeation, we are more likely to define emerging guidelines for optimal permeation into Gram-negative bacteria, likely to differ across species, as well as chemical class. In other words, what may work for passive diffusion in E. coli will likely not work for P. aeruginosa or A. baumannii given the outer membrane of these pathogens is more restrictive. Nevertheless, we should certainly recognize that large, non-polar compounds such as those found in Big Pharma libraries are highly unlikely to permeate any of the species of Gram-negative pathogens of interest and so we have at least learned a rule of what NOT to do. Measuring antibiotic accumulation within bacteria Life for the antibacterial researcher would certainly be much easier if one could simply and consistently measure intracellular compound concentration over time without relying on biochemical or antibacterial activity. While there are many ongoing attempts to accomplish this, developing a robust, broadly applicable, and high-throughput approach has been challenging. Indeed, the lack of molecular tools to quantify compound penetration into and efflux out of Gram-negative bacteria has been identified as a key bottleneck for the rational discovery of novel antibacterial compounds by the PEW, NIAID and other funding institutions 14. Traditionally, comparative MIC assays (i.e., comparing MICs of a compound of interest against wildtype vs. isogenic mutant strains, where the gene of interest has been deleted or inactivated) has been the workhorse of assays used in the field to define the molecular drivers of antibiotic uptake and efflux. Indeed, demonstration of measurable MICs against efflux-compromised or membrane permeabilized


Page 12 of 26

Page 13 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


strains is logically still among the first objectives for most of the earliest stage projects in the field. However, as mentioned above, the possibility that a meaningful phenotype related to compound uptake might be masked due to either redundant or complementary functions for inactivated genes is a potential caveat to this type of approach. To address this possibility and to further define bacterial porin function/selectivity, our team recently developed a system called TOMAS (for Titrable Outer Membrane Assay System) to perform comparative MICs on bacterial strains engineered for “gain-of-function” phenotypes

63

. Specifically, we adapted a tightly regulated, arabinose-inducible system to allow

expression of any porin of interest in an E. coli strain whose three major porins (ompA, ompC and ompF) were deleted (in both efflux-proficient and -deficient backgrounds). We found this system sufficiently sensitive to establish structure-porin-permeation relationships (SPPR) for carbapenem passage through P. aeruginosa OprD 63, (Figure 3, compounds 6-8), demonstrating proof of concept for the approach. We have since used it to demonstrate, for the first time, that a new class of beta-lactamase inhibitors, the diazabicyclooctenones, permeate Acinetobacter baumannii through the major porin OmpAAb 64 (Figure 4, compounds 9-11). An interesting observation from this study is that small structural changes such as the addition of a single methyl group to avibactam resulting in 10, appeared to negatively impact the permeation characteristics through OmpA in this system, while just moving the methyl group from the 2position of ETX2514 (9) to the 3-position resulting in 11 actually improved permeation through the same channel 64. Clearly these results suggest that there is subtle SAR related to permeation which requires careful analysis. We are currently using TOMAS to define additional SPPR of novel and established classes for multiple ESKAPE pathogen porins. Zgurskaya and coworkers have developed a different take on porin overexpression to study antibiotic permeation 65. This cleverly engineered “hyperporination” system is based on the controlled expression of a large, non-selective variant of the FhuA transporter (without compromising the integrity of the membrane bilayer) in either wildtype or efflux-deficient E. coli strains. The authors used this approach to



Page 14 of 26

deconvolute the contributions of membrane permeability vs. efflux in E. coli for several antibiotic classes that differed significantly in their physicochemical properties and mechanisms of action. They have since deployed the system in more problematic pathogens with distinct permeability barriers, namely A. baumannii, P. aeruginosa and Burkholderia spp. 13. In doing so, they found that no universal “rule” of antibiotic permeation into Gram-negative bacteria exist. However, they were able to classify antibiotics into four groups according to specific biological determinants such as the presence of specific porins in the outer membrane, targeting of the outer membrane or specific recognition by efflux pumps. Finally, the range of physicochemical properties for each cluster of antibiotics was found to be quite broad. Although comparative MICs such as those described above provide key information for the field, their rudimentary nature (i.e. visual detection of bacterial growth after overnight incubation) admittedly makes them a rather blunt tool for these types of studies. This is particularly true when trying to evaluate kinetic effects such as rates of entry and/or efflux. An alternate approach, the related ‘time kill’ assay, traditionally employed to define the pharmacodynamic properties of antibiotics, can be used to perform more refined, kinetic assessments of the molecular drivers of antibiotic activity.

This concept is

exemplified by the comparison of the rates of kill of meropenem against wildtype vs. efflux-compromised (tolC-) E. coli. Although the lack of difference in the MIC of meropenem against these two strains (0.03 mg/L for both) suggest its activity is not affected by efflux, a very different picture emerges when its relative rates of kill are compared (Figure 5A, B). However, the standard readout of this method, namely determining relative bacterial CFUs at various time points after antibiotic exposure by manually counting serially diluted samples plated on agar, is very time-, labor- and resource-intensive. We have recently addressed these limitations by adapting a previously described luciferase-based reporter system as a surrogate for bacterial viability.

66

The change in luminescence in real-time qualitatively mirrors the

relative changes in bacterial load and tracks with incremental, drug-mediated cell killing over time. This


Page 15 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


allows for much greater throughput in a fraction of the time and cost, (Figure 5C, D) and which we are now incorporating into our discovery efforts. Numerous biophysical methods to quantify antibiotic passage and accumulation have been described in the literature, including electrophysiological measurements on reconstituted membranes or whole cells 67

, single particle X-ray diffraction 68, synchrotron UV fluorescent microscopy 69, Raman spectroscopy 70,

nanofluidics

71

or 3D subcellular imaging of antibiotics72. These approaches, while informative, are not

readily amenable to development into an assay platform with reasonable throughput and require specialized equipment, and therefore do not represent practical solutions for the field at present. In contrast, mass spectroscopy-based methods may have more potential to quantify intracellular antibiotic concentrations, as recently exemplified by the aforementioned study from the Hergenrother group 26. However, it is important to recognize that numerous factors keep even these approaches from being

Figure 5 – Dose responses of time kill results measured as CFU for meropenem in wt E. coli (A) and tolC- E. coli (B) and by luminescence (K-12 E. coli expressing luciferase (Photorhabdus luminescens), wild type (C) and tolC- (D). In panels C-D, green arrow denotes time of compound addition.



easily converted into a “one-size-fits-all” high throughput assay, as optimized conditions for one series of compounds may not be suitable for another. This was one of our learnings a few years ago, when we attempted to develop a MS-based method to indirectly determine intracellular antibiotic concentrations by measuring the difference in external drug concentrations in the presence of wildtype vs. isogenic mutant bacterial cells 73. Although this method did help minimize variability due to multiple washing steps and/or non-specific binding (i.e. known limitations of directly measuring intracellular antibiotic concentrations) as we had hoped, we still observed notable, compound-specific variability in optimal assay conditions, such as in non-specific binding of compounds to the plates and/or strains, differences in optimal incubation times, etc. One clever approach to get around this conundrum was recently published by researchers at Novartis describing the optimization of CoaD inhibitors against E. coli that included the use of both liquid chromatography mass spectroscopy (LC-MS) and automated solid-phase extraction mass spectroscopy (SPE-MS) 74. Instead of directly measuring intracellular concentrations of the inhibitors themselves, the authors tracked levels of CoA metabolites as biomarkers of target inhibition 74. This strategy resulted in a 100-fold more sensitive detection of the intracellular activity of CoaD inhibitors than traditional MIC assays, which ultimately helped facilitate design of compounds with measurable antibacterial activity against wildtype cells. Similar assessments of antibiotic effects on entire bacterial metabolomes to quantify intracellular inhibitor concentrations have also been described 75,76. Outlook: Piecing it All Together Multiple public health authorities have recently prioritized antibiotic resistance as a significant threat to human health. This is exacerbated by the lack of novel therapies, especially for the treatment of multidrug-resistant Gram-negative infections. A key bottleneck to the discovery of such agents is a basic lack of understanding of the molecular basis for compound penetration into and efflux out of Gram-


Page 16 of 26

Page 17 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


negative bacteria.

While it is clear that the field is still developing, a number of important,

multidisciplinary advances have recently been made, several of which have been discussed here. In order to change the paradigm of antibacterial drug discovery, we will need to continue developing these novel approaches, but more importantly, learn how to use these together in a more coherent fashion. We will need to build broader datasets to explore the structural relationships to both uptake and efflux and generate general libraries of compounds that are not per se antibacterial libraries. We may need to take a step back and explore the structural and physicochemical features of small structurally diverse compounds leveraging the advances in MS detection of accumulation. This would allow us to focus on exploring variations in shape, dipole moment and presentation of charges as well as hydrogen bonding characteristics. If we limit our focus solely to compounds that may have some antibacterial activity, it may take us longer to learn the basic principles of accumulation. A simple example of how we limit ourselves if we focus on antibacterial scaffolds was presented here with the meropenem analogs in Figure 3. The analogs explored in that study were all focused on the right side of the scaffold because it is known that there is space in the PBP3 protein to tolerate those substitutions. It is interesting however to ponder, without concern for biochemical potency or antibacterial activity, where the charges should be best placed to optimize accumulation into P. aeruginosa and the other Gram-negative ESKAPE pathogens (Figure 6) – obviously, those compounds have never been made. It’s clear from this example that the choices we make about which compounds to study are critical to the scope of knowledge that we can uncover. Academic investigations in this space and proper funding for it are therefore desperately needed to address this basic research need. Another example to support this concept is our lack of understanding of the basic SAR of nutrient uptake into these pathogens. For example, while we know benzoic acid is taken up by most members of the OccK family 41,77, we do not know relative efficiencies of uptake by any of these porins and we do not know the SAR of this uptake. What benzoic acid substitutions are tolerated? Are other polar groups besides the carboxyl moiety beneficial? Would a hydrogen bond donor or acceptor



in the right place benefit uptake and in the wrong place hurt it? Or what happens if we add a simple methyl group in the right or wrong place such as those changes illustrated for ETX2514 in Figure 4?

Figure 6 – Areas where we have explored (green) or not explored (red) the chemical space for effects of uptake and efflux around example chemical scaffolds

Until recently, we really had no way to address these seemingly simple questions. Varying nutrients to measure relative uptake would be confounded for example by ability or inability of downstream enzymes to properly metabolize these nutrients. Our vision for the future involves the use of novel accumulation methods and where applicable, the rational design of porin permeation and efflux avoidance using molecular dynamics and crystal structures to build a better understanding of the SAR of these biological functions. We are still missing critical pieces to this important puzzle. For example, how will we design and synthesize these generic libraries and how would that work be funded? Currently, there is no simple path to obtain funding for such basic research which is so desperately needed. However, interest in the area is increasing and awareness of the importance of discovering new antibacterials is becoming more widespread. Efforts such as the RoadMap that the Pew Trusts have published have helped in that area. There may not be a simple set of rules or guidelines that one can follow blindly in the hopes of discovering novel antibacterials. Instead we are likely to find a host of structure-accumulation relationships. Indeed, continued interest and greater funding opportunities will be critical to enable innovative thinking to both develop untested ideas and approaches and advance the ones described herein to fuel the discovery and development of new medicines that are so desperately needed.


Page 18 of 26

Page 19 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


ABBREVIATIONS MWt, Molecular Weight; MIC, minimum inhibitory concentration; SPPR, structure-porin-permeation relationship; SAR, structure-activity relationship; logD distribution coefficient, EF-g elongation factor-G. AUTHOR INFORMATION Current address of all authors: Entasis Therapeutics, Inc., 35 Gatehouse Drive, Waltham, MA 02451 AUTHOR CONTRIBUTIONS All authors contributed equally to this work ACKNOWLEDGEMENTS Authors thank Thomas Durand-Réville and Manos Perros for review of this manuscript. The work was fully funded by Entasis Therapeutics, and all authors are full-time employees of Entasis Therapeutics Inc.



REFERENCES

1. Outterson, K.; Rex, J. H.; Jinks, T.; Jackson, P.; Hallinan, J.; Karp, S.; Hung, D. T.; Franceschi, F.; Merkeley, T.; Houchens, C.; Dixon, D. M.; Kurilla, M. G.; Aurigemma, R.; Larsen, J., Accelerating global innovation to address antibacterial resistance: introducing CARB-X. Nature Reviews Drug Discovery 2016, 15, 589. DOI: 10.1038/nrd.2016.155. 2. Rex, J. H.; Talbot, G. H.; Goldberger, M. J.; Eisenstein, B. I.; Echols, R. M.; Tomayko, J. F.; Dudley, M. N.; Dane, A., Progress in the Fight Against Multidrug-Resistant Bacteria 2005–2016: Modern Noninferiority Trial Designs Enable Antibiotic Development in Advance of Epidemic Bacterial Resistance. Clinical Infectious Diseases 2017, 65 (1), 141-146. DOI: 10.1093/cid/cix246. 3. Årdal, C.; Baraldi, E.; Ciabuschi, F.; Outterson, K.; Rex, J. H.; Piddock, L. J. V.; Findlay, D., To the G20: incentivising antibacterial research and development. The Lancet Infectious Diseases 2017, 17 (8), 799-801. DOI: 10.1016/S1473-3099(17)30404-8. 4. Towse, A.; Hoyle, C. K.; Goodall, J.; Hirsch, M.; Mestre-Ferrandiz, J.; Rex, J. H., Time for a change in how new antibiotics are reimbursed: Development of an insurance framework for funding new antibiotics based on a policy of risk mitigation. Health Policy 2017, 121 (10), 1025-1030. DOI: 10.1016/j.healthpol.2017.07.011. 5. Rex, J. H.; Goldberger, M.; Eisenstein, B. I.; Harney, C., The evolution of the regulatory framework for antibacterial agents. Annals of the New York Academy of Sciences 2014, 1323 (1), 11-21. DOI: 10.1111/nyas.12441. 6. Shlaes, D. M., Research and Development of Antibiotics: The Next Battleground. ACS Infectious Diseases 2015, 1 (6), 232-233. DOI: 10.1021/acsinfecdis.5b00048. 7. Spellberg, B.; Marr, K. A.; Brass, E. P., Regulatory Pathways for New Antimicrobial Agents: Tradeoffs to Keep the Perfect From Being the Enemy of the Good. Clinical pharmacology and therapeutics 2016, 100 (6), 597-599. DOI: 10.1002/cpt.510. 8. Gwynn, M. N.; Portnoy, A.; Rittenhouse, S. F.; Payne, D. J., Challenges of antibacterial discovery revisited. Annals of the New York Academy of Sciences 2010, 1213 (1), 5-19. DOI: 10.1111/j.17496632.2010.05828.x. 9. Tommasi, R.; Brown, D. G.; Walkup, G. K.; Manchester, J. I.; Miller, A. A., ESKAPEing the labyrinth of antibacterial discovery. Nat Rev Drug Discov 2015, 14 (8), 529-42. DOI: 10.1038/nrd4572. 10. Kostyanev, T.; Bonten, M. J. M.; O'Brien, S.; Steel, H.; Ross, S.; François, B.; Tacconelli, E.; Winterhalter, M.; Stavenger, R. A.; Karlén, A.; Harbarth, S.; Hackett, J.; Jafri, H. S.; Vuong, C.; MacGowan, A.; Witschi, A.; Angyalosi, G.; Elborn, J. S.; deWinter, R.; Goossens, H., The Innovative Medicines Initiative's New Drugs for Bad Bugs programme: European public–private partnerships for the development of new strategies to tackle antibiotic resistance. Journal of Antimicrobial Chemotherapy 2016, 71 (2), 290-295. DOI: 10.1093/jac/dkv339. 11. Silver, L. L., A Gestalt approach to Gram-negative entry. Bioorganic & Medicinal Chemistry 2016, 24 (24), 6379-6389. DOI: 10.1016/j.bmc.2016.06.044. 12. Pawlowski, A. C.; Johnson, J. W.; Wright, G. D., Evolving medicinal chemistry strategies in antibiotic discovery. Current Opinion in Biotechnology 2016, 42 (Supplement C), 108-117. DOI: 10.1016/j.copbio.2016.04.006. 13. Krishnamoorthy, G.; Leus, I. V.; Weeks, J. W.; Wolloscheck, D.; Rybenkov, V. V.; Zgurskaya, H. I., Synergy between Active Efflux and Outer Membrane Diffusion Defines Rules of Antibiotic Permeation into Gram-Negative Bacteria. mBio 2017, 8 (5), e01172-17. DOI: 10.1128/mBio.01172-17. 14. Shore, C.; Coukell, A. A Scientific Roadmap for Antibiotic Discovery; Pew Charitable Trusts: Washington, DC, 2016.


Page 20 of 26

Page 21 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


15. Payne, D. J.; Gwynn, M. N.; Holmes, D. J.; Pompliano, D. L., Drugs for bad bugs: confronting the challenges of antibacterial discovery. Nature Reviews Drug Discovery 2006, 6, 29. DOI: 10.1038/nrd2201. 16. Wang, J.; Soisson, S. M.; Young, K.; Shoop, W.; Kodali, S.; Galgoci, A.; Painter, R.; Parthasarathy, G.; Tang, Y. S.; Cummings, R.; Ha, S.; Dorso, K.; Motyl, M.; Jayasuriya, H.; Ondeyka, J.; Herath, K.; Zhang, C.; Hernandez, L.; Allocco, J.; Basilio, Á.; Tormo, J. R.; Genilloud, O.; Vicente, F.; Pelaez, F.; Colwell, L.; Lee, S. H.; Michael, B.; Felcetto, T.; Gill, C.; Silver, L. L.; Hermes, J. D.; Bartizal, K.; Barrett, J.; Schmatz, D.; Becker, J. W.; Cully, D.; Singh, S. B., Platensimycin is a selective FabF inhibitor with potent antibiotic properties. Nature 2006, 441, 358. DOI: 10.1038/nature04784 17. Singh, S. B.; Young, K.; Miesel, L., Screening strategies for discovery of antibacterial natural products. Expert Review of Anti-infective Therapy 2011, 9 (8), 589-613. DOI: 10.1586/eri.11.81. 18. O’Shea, R.; Moser, H. E., Physicochemical Properties of Antibacterial Compounds: Implications for Drug Discovery. Journal of Medicinal Chemistry 2008, 51 (10), 2871-2878. DOI: 10.1021/jm700967e. 19. Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J., Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3–25.1. Advanced Drug Delivery Reviews 2001, 46 (1), 3-26. DOI: 10.1016/S0169409X(00)00129-0. 20. Nyfeler, B.; Hoepfner, D.; Palestrant, D.; Kirby, C. A.; Whitehead, L.; Yu, R.; Deng, G.; Caughlan, R. E.; Woods, A. L.; Jones, A. K.; Barnes, S. W.; Walker, J. R.; Gaulis, S.; Hauy, E.; Brachmann, S. M.; Krastel, P.; Studer, C.; Riedl, R.; Estoppey, D.; Aust, T.; Movva, N. R.; Wang, Z.; Salcius, M.; Michaud, G. A.; McAllister, G.; Murphy, L. O.; Tallarico, J. A.; Wilson, C. J.; Dean, C. R., Identification of Elongation Factor G as the Conserved Cellular Target of Argyrin B. PLOS ONE 2012, 7 (9), e42657. DOI: 10.1371/journal.pone.0042657. 21. Driggers, E. M.; Hale, S. P.; Lee, J.; Terrett, N. K., The exploration of macrocycles for drug discovery — an underexploited structural class. Nature Reviews Drug Discovery 2008, 7, 608. DOI: 10.1038/nrd2590 22. Rezai, T.; Yu, B.; Millhauser, G. L.; Jacobson, M. P.; Lokey, R. S., Testing the Conformational Hypothesis of Passive Membrane Permeability Using Synthetic Cyclic Peptide Diastereomers. Journal of the American Chemical Society 2006, 128 (8), 2510-2511. DOI: 10.1021/ja0563455. 23. Stone, G. G.; Bradford, P. A.; Yates, K.; Newell, P., In vitro activity of ceftazidime/avibactam against urinary isolates from patients in a Phase 3 clinical trial programme for the treatment of complicated urinary tract infections. Journal of Antimicrobial Chemotherapy 2017, 72 (5), 1396-1399. DOI: 10.1093/jac/dkw561. 24. Durand-Réville, T. F.; Guler, S.; Comita-Prevoir, J.; Chen, B.; Bifulco, N.; Huynh, H.; Lahiri, S.; Shapiro, A. B.; McLeod, S. M.; Carter, N. M.; Moussa, S. H.; Velez-Vega, C.; Olivier, N. B.; McLaughlin, R.; Gao, N.; Thresher, J.; Palmer, T.; Andrews, B.; Giacobbe, R. A.; Newman, J. V.; Ehmann, D. E.; de Jonge, B.; O'Donnell, J.; Mueller, J. P.; Tommasi, R. A.; Miller, A. A., ETX2514 is a broad-spectrum β-lactamase inhibitor for the treatment of drug-resistant Gram-negative bacteria including Acinetobacter baumannii. Nature Microbiology 2017, 2, 17104. DOI: 10.1038/nmicrobiol.2017.104. 25. Brown, D. G.; May-Dracka, T. L.; Gagnon, M. M.; Tommasi, R., Trends and Exceptions of Physical Properties on Antibacterial Activity for Gram-Positive and Gram-Negative Pathogens. Journal of Medicinal Chemistry 2014, 57 (23), 10144-10161. DOI: 10.1021/jm501552x. 26. Richter, M. F.; Drown, B. S.; Riley, A. P.; Garcia, A.; Shirai, T.; Svec, R. L.; Hergenrother, P. J., Predictive compound accumulation rules yield a broad-spectrum antibiotic. Nature 2017, 545, 299. DOI: 10.1038/nature22308.



27. Quinn, J.; Dudek, E.; DiVincenzo, C.; Lucks, D.; Lerner, S., Emergence of resistance to imipenem during therapy for Pseudomonas aeruginosa infections. J Infect. Dis. 1986, 154 (2), 289-294. 28. Trias, J.; Nikaido, H., Outer membrane protein D2 catalyzes facilitated diffusion of carbapenems and penems through the outer membrane of Pseudomonas aeruginosa. Antimicrobial Agents and Chemotherapy 1990, 34 (1), 52-57. 29. Isabella, Vincent M.; Campbell, Arthur J.; Manchester, J.; Sylvester, M.; Nayar, Asha S.; Ferguson, Keith E.; Tommasi, R.; Miller, Alita A., Toward the Rational Design of Carbapenem Uptake in Pseudomonas aeruginosa. Chemistry & Biology 2015, 22 (4), 535-547. DOI: 10.1016/j.chembiol.2015.03.018. 30. Nikaido, H., Molecular Basis of Bacterial Outer Membrane Permeability Revisited. Microbiology and Molecular Biology Reviews 2003, 67 (4), 593-656. DOI: 10.1128/MMBR.67.4.593-656.2003. 31. Hancock, R. E. W.; Brinkman, F. S. L., Function of Pseudomonas Porins in Uptake and Efflux. Annual Review of Microbiology 2002, 56 (1), 17-38. DOI: 10.1146/annurev.micro.56.012302.160310. 32. Lim, S. P.; Nikaido, H., Kinetic Parameters of Efflux of Penicillins by the Multidrug Efflux Transporter AcrAB-TolC of Escherichia coli. Antimicrobial Agents and Chemotherapy 2010, 54 (5), 18001806. DOI: 10.1128/AAC.01714-09. 33. Kojima, S.; Nikaido, H., Permeation rates of penicillins indicate that Escherichia coli porins function principally as nonspecific channels. Proceedings of the National Academy of Sciences of the United States of America 2013, 110 (28), E2629-E2634. DOI: 10.1073/pnas.1310333110. 34. Yoshimura, F.; Nikaido, H., Permeability of Pseudomonas aeruginosa outer membrane to hydrophilic solutes. Journal of Bacteriology 1982, 152 (2), 636-642. 35. Tamber, S.; Hancock, R. E. W., On the mechanism of solute uptake in Pseudomonas. Frontiers in Bioscience 2003, 8, s472-483. 36. Tamber, S.; Ochs, M. M.; Hancock, R. E. W., Role of the Novel OprD Family of Porins in Nutrient Uptake in Pseudomonas aeruginosa. Journal of Bacteriology 2006, 188 (1), 45-54. DOI: 10.1128/JB.188.1.45-54.2006. 37. Eren, E.; Parkin, J.; Adelanwa, A.; Cheneke, B.; Movileanu, L.; Khalid, S.; van den Berg, B., Toward Understanding the Outer Membrane Uptake of Small Molecules by Pseudomonas aeruginosa. The Journal of Biological Chemistry 2013, 288 (17), 12042-12053. DOI: 10.1074/jbc.M113.463570. 38. Zahn, M.; Bhamidimarri, Satya P.; Baslé, A.; Winterhalter, M.; van den Berg, B., Structural Insights into Outer Membrane Permeability of Acinetobacter baumannii. Structure 2016, 24 (2), 221-231. DOI: 10.1016/j.str.2015.12.009. 39. Bajaj, H.; Scorciapino, M. A.; Moynié, L.; Page, M. G. P.; Naismith, J. H.; Ceccarelli, M.; Winterhalter, M., Molecular Basis of Filtering Carbapenems by Porins from β-Lactam-resistant Clinical Strains of Escherichia coli. The Journal of Biological Chemistry 2016, 291 (6), 2837-2847. DOI: 10.1074/jbc.M115.690156. 40. Liu, J.; Wolfe, A. J.; Eren, E.; Vijayaraghavan, J.; Indic, M.; van den Berg, B.; Movileanu, L., Cation Selectivity is a Conserved Feature in the OccD Subfamily of Pseudomonas aeruginosa. Biochimica et biophysica acta 2012, 1818 (11), 2908-2916. DOI: 10.1016/j.bbamem.2012.07.009. 41. Liu, J.; Eren, E.; Vijayaraghavan, J.; Cheneke, B. R.; Indic, M.; van den Berg, B.; Movileanu, L., OccK Channels from Pseudomonas aeruginosa Exhibit Diverse Single-Channel Electrical Signatures but Conserved Anion Selectivity. Biochemistry 2012, 51 (11), 2319-2330. DOI: 10.1021/bi300066w. 42. Bajaj, H.; Acosta Gutierrez, S.; Bodrenko, I.; Malloci, G.; Scorciapino, M. A.; Winterhalter, M.; Ceccarelli, M., Bacterial Outer Membrane Porins as Electrostatic Nanosieves: Exploring Transport Rules of Small Polar Molecules. ACS Nano 2017, 11 (6), 5465-5473. DOI: 10.1021/acsnano.6b08613. 43. Bodrenko, I. V.; Wang, J.; Salis, S.; Winterhalter, M.; Ceccarelli, M., Sensing Single Molecule Penetration into Nanopores: Pushing the Time Resolution to the Diffusion Limit. ACS Sensors 2017, 2 (8), 1184-1190. DOI: 10.1021/acssensors.7b00311.


Page 22 of 26

Page 23 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


44. Ghai, I.; Winterhalter, M.; Wagner, R., Probing transport of charged β-lactamase inhibitors through OmpC, a membrane channel from E. coli. Biochemical and Biophysical Research Communications 2017, 484 (1), 51-55. DOI: 10.1016/j.bbrc.2017.01.076. 45. Soundararajan, G.; Bhamidimarri, S. P.; Winterhalter, M., Understanding Carbapenem Translocation through OccD3 (OpdP) of Pseudomonas aeruginosa. ACS Chemical Biology 2017, 12 (6), 1656-1664. DOI: 10.1021/acschembio.6b01150. 46. Mahendran, K. R.; Kreir, M.; Weingart, H.; Fertig, N.; Winterhalter, M., Permeation of Antibiotics through Escherichia coli OmpF and OmpC Porins:Screening for Influx on a Single-Molecule Level. Journal of Biomolecular Screening 2010, 15 (3), 302-307. DOI: 10.1177/1087057109357791. 47. Nakashima, R.; Sakurai, K.; Yamasaki, S.; Nishino, K.; Yamaguchi, A., Structures of the multidrug exporter AcrB reveal a proximal multisite drug-binding pocket. Nature 2011, 480, 565. DOI: 10.1038/nature10641. 48. Hinchliffe, P.; Symmons, M. F.; Hughes, C.; Koronakis, V., Structure and Operation of Bacterial Tripartite Pumps. Annual Review of Microbiology 2013, 67 (1), 221-242. DOI: 10.1146/annurev-micro092412-155718. 49. Dreier, J.; Ruggerone, P., Interaction of antibacterial compounds with RND efflux pumps in Pseudomonas aeruginosa. Frontiers in Microbiology 2015, 6 (660). DOI: 10.3389/fmicb.2015.00660. 50. Daury, L.; Orange, F.; Taveau, J.-C.; Verchère, A.; Monlezun, L.; Gounou, C.; Marreddy, R. K. R.; Picard, M.; Broutin, I.; Pos, K. M.; Lambert, O., Tripartite assembly of RND multidrug efflux pumps. Nature Communications 2016, 7, 10731. DOI: 10.1038/ncomms10731. 51. Sjuts, H.; Vargiu, A. V.; Kwasny, S. M.; Nguyen, S. T.; Kim, H.-S.; Ding, X.; Ornik, A. R.; Ruggerone, P.; Bowlin, T. L.; Nikaido, H.; Pos, K. M.; Opperman, T. J., Molecular basis for inhibition of AcrB multidrug efflux pump by novel and powerful pyranopyridine derivatives. Proceedings of the National Academy of Sciences of the United States of America 2016, 113 (13), 3509-3514. DOI: 10.1073/pnas.1602472113. 52. Nakashima, R.; Sakurai, K.; Yamasaki, S.; Hayashi, K.; Nagata, C.; Hoshino, K.; Onodera, Y.; Nishino, K.; Yamaguchi, A., Structural basis for the inhibition of bacterial multidrug exporters. Nature 2013, 500, 102. DOI: 10.1038/nature12300. 53. Wang, B.; Weng, J.; Wang, W., Substrate binding accelerates the conformational transitions and substrate dissociation in multidrug efflux transporter AcrB. Frontiers in Microbiology 2015, 6 (302). DOI: 10.3389/fmicb.2015.00302. 54. Cacciotto, P.; Ramaswamy, V. K.; Malloci, G.; Ruggerone, P.; Vargiu, A. V., Molecular Modeling of Multidrug Properties of Resistance Nodulation Division (RND) Transporters. In Bacterial Multidrug Exporters: Methods and Protocols, Yamaguchi, A.; Nishino, K., Eds. Springer New York: New York, NY, 2018; pp 179-219. DOI: 10.1007/978-1-4939-7454-2_11. 55. Fernández, L.; Hancock, R. E. W., Adaptive and Mutational Resistance: Role of Porins and Efflux Pumps in Drug Resistance. Clinical Microbiology Reviews 2012, 25 (4), 661-681. DOI: 10.1128/CMR.0004312. 56. Schweizer, H. P., Understanding efflux in Gram-negative bacteria: opportunities for drug discovery. Expert Opinion on Drug Discovery 2012, 7 (7), 633-642. DOI: 10.1517/17460441.2012.688949. 57. Blair, J. M.; Richmond, G. E.; Piddock, L. J., Multidrug efflux pumps in Gram-negative bacteria and their role in antibiotic resistance. Future Microbiology 2014, 9 (10), 1165-1177. DOI: 10.2217/fmb.14.66. 58. Anes, J.; McCusker, M. P.; Fanning, S.; Martins, M., The ins and outs of RND efflux pumps in Escherichia coli. Frontiers in Microbiology 2015, 6, 587. DOI: 10.3389/fmicb.2015.00587. 59. Li, X.-Z.; Plésiat, P.; Nikaido, H., The Challenge of Efflux-Mediated Antibiotic Resistance in GramNegative Bacteria. Clinical Microbiology Reviews 2015, 28 (2), 337-418. DOI: 10.1128/CMR.00117-14.



60. Efflux-Mediated Antimicrobial Resistance in Bacteria: Mechanisms, Regulation and Clinical Implications. Li, X.Z., Elkins, C.A, and Zgurskaya, H.I., eds.; Springer International Publishing, Switzerland: 2016. DOI: 10.1007/978-3-319-39658-3. 61. Nichols, W. W., Modeling the Kinetics of the Permeation of Antibacterial Agents into Growing Bacteria and Its Interplay with Efflux. Antimicrobial Agents and Chemotherapy 2017, 61 (10). DOI: 10.1128/aac.02576-16. 62. Westfall, D. A.; Krishnamoorthy, G.; Wolloscheck, D.; Sarkar, R.; Zgurskaya, H. I.; Rybenkov, V. V., Bifurcation kinetics of drug uptake by Gram-negative bacteria. PLOS ONE 2017, 12 (9), e0184671. DOI: 10.1371/journal.pone.0184671. 63. Iyer, R.; Sylvester, M. A.; Velez-Vega, C.; Tommasi, R.; Durand-Reville, T. F.; Miller, A. A., WholeCell-Based Assay To Evaluate Structure Permeation Relationships for Carbapenem Passage through the Pseudomonas aeruginosa Porin OprD. ACS Infectious Diseases 2017, 3 (4), 310-319. DOI: 10.1021/acsinfecdis.6b00197. 64. Iyer, R.; Moussa, S. H.; Durand-Reville, T. F.; Tommasi, R.; Miller, A. A., Acinetobacter baumannii OmpA is a selective antibiotic permeant porin. ACS Infectious Diseases 2017. DOI: 10.1021/acsinfecdis.7b00168. 65. Krishnamoorthy, G.; Wolloscheck, D.; Weeks, J. W.; Croft, C.; Rybenkov, V. V.; Zgurskaya, H. I., Breaking the Permeability Barrier of Escherichia coli by Controlled Hyperporination of the Outer Membrane. Antimicrobial Agents and Chemotherapy 2016, 60 (12), 7372-7381. DOI: 10.1128/AAC.0188216. 66. Hilpert, K.; Hancock, R. E. W., Use of luminescent bacteria for rapid screening and characterization of short cationic antimicrobial peptides synthesized on cellulose using peptide array technology. Nature Protocols 2007, 2, 1652. DOI: 10.1038/nprot.2007.203. 67. Tran, Q.-T.; Pearlstein, R. A.; Williams, S.; Reilly, J.; Krucker, T.; Erdemli, G., Structure-kinetic relationship of carbapenem antibacterials permeating through E. coli OmpC porin. Proteins: Structure, Function, and Bioinformatics 2014, 82 (11), 2998-3012. DOI: 10.1002/prot.24659. 68. Miao, J.; Hodgson, K. O.; Ishikawa, T.; Larabell, C. A.; LeGros, M. A.; Nishino, Y., Imaging whole Escherichia coli bacteria by using single-particle x-ray diffraction. Proceedings of the National Academy of Sciences of the United States of America 2003, 100 (1), 110-112. DOI: 10.1073/pnas.232691299. 69. Kaščáková, S.; Maigre, L.; Chevalier, J.; Réfrégiers, M.; Pagès, J.-M., Antibiotic Transport in Resistant Bacteria: Synchrotron UV Fluorescence Microscopy to Determine Antibiotic Accumulation with Single Cell Resolution. PLoS ONE 2012, 7 (6), e38624. DOI: 10.1371/journal.pone.0038624. 70. Heidari Torkabadi, H.; Bethel, C. R.; Papp-Wallace, K. M.; de Boer, P. A. J.; Bonomo, R. A.; Carey, P. R., Following Drug Uptake and Reactions inside Escherichia coli Cells by Raman Microspectroscopy. Biochemistry 2014, 53 (25), 4113-4121. DOI: 10.1021/bi500529c. 71. Hong, S.; Moritz, T. J.; Rath, C. M.; Tamrakar, P.; Lee, P.; Krucker, T.; Lee, L. P., Assessing Antibiotic Permeability of Gram-Negative Bacteria via Nanofluidics. ACS Nano 2017, 11 (7), 6959-6967. DOI: 10.1021/acsnano.7b02267. 72. Tian, H.; Six, D. A.; Krucker, T.; Leeds, J. A.; Winograd, N., Subcellular Chemical Imaging of Antibiotics in Single Bacteria Using C60-Secondary Ion Mass Spectrometry. Analytical Chemistry 2017, 89 (9), 5050-5057. DOI: 10.1021/acs.analchem.7b00466. 73. Zhou, Y.; Joubran, C.; Miller-Vedam, L.; Isabella, V.; Nayar, A.; Tentarelli, S.; Miller, A., Thinking Outside the “Bug”: A Unique Assay To Measure Intracellular Drug Penetration in Gram-Negative Bacteria. Analytical Chemistry 2015, 87 (7), 3579-3584. DOI: 10.1021/ac504880r. 74. Rath, C. M.; Benton, B. M.; de Vicente, J.; Drumm, J. E.; Geng, M.; Li, C.; Moreau, R. J.; Shen, X.; Skepper, C. K.; Steffek, M.; Takeoka, K.; Wang, L.; Wei, J.-R.; Xu, W.; Zhang, Q.; Feng, B. Y., Optimization of CoaD Inhibitors against Gram-Negative Organisms through Targeted Metabolomics. ACS Infectious Diseases 2017. DOI: 10.1021/acsinfecdis.7b00214.


Page 24 of 26

Page 25 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


75. Davis, T. D.; Gerry, C. J.; Tan, D. S., General Platform for Systematic Quantitative Evaluation of Small-Molecule Permeability in Bacteria. ACS Chemical Biology 2014, 9 (11), 2535-2544. DOI: 10.1021/cb5003015. 76. Jansen, R. S.; Rhee, K. Y., Emerging Approaches to Tuberculosis Drug Development: At Home in the Metabolome. Trends in Pharmacological Sciences 2017, 38 (4), 393-405. DOI: 10.1016/j.tips.2017.01.005. 77. Campbell, A. J.; Sylvester, M.; Isabella, V.; Patey, S.; Nayar, A.; McLaughlin, B.; MacCormack, K.; Eyermann, J.; Fleming, P.; Basarab, G. A., Beth ; deJonge, B.; Gupta, A.; Buurman, E.; Chen, A.; Mattes, K.; Joubran, C.; Doig, P.; Sriram, S.; Wesolowski, S.; Durand-Reville, T.; Ceccarelli, M.; van den Berg, B.; Huband, M.; Miller, A.; Mills, S.; Manchester, J.; Bisacchi, G.; Tommasi, R. In Improving our understanding of porin permeability in Gram-negative bacteria, Boston Area Antimicrobial Research Network (BAARN), Boston, MA 02451 USA, November, 2013.



For Table of Contents Use Only


Page 26 of 26

Antibacterial Drug Discovery: Some Assembly Required - ACS

Recommend Documents