Combating Multidrug‐Resistant Bacteria by Integrating a Novel Target Site Penetration and Receptor Binding Assay Platform Into Translational Modeling

Abstract

Multidrug-resistant bacteria are causing a serious global health crisis. A dramatic decline in antibiotic discovery and development investment by pharmaceutical industry over the last decades has slowed the adoption of new technologies. It is imperative that we create new mechanistic insights based on latest technologies, and use translational strategies to optimize patient therapy. Although drug development has relied on minimal inhibitory concentration testing and established in vitro and mouse infection models, the limited understanding of outer membrane permeability in Gramnegative bacteria presents major challenges. Our team has developed a platform using the latest technologies to characterize target site penetration and receptor binding in intact bacteria that inform translational modeling and guide new discovery. Enhanced assays can quantify the outer membrane permeability of β-lactam antibiotics and β-lactamase inhibitors using multiplex liquid chromatography tandem mass spectrometry. While β-lactam antibiotics are known to bind to multiple different penicillin-binding proteins (PBPs), their binding profiles are almost always studied in lysed bacteria. Novel assays for PBP binding in the periplasm of intact bacteria were developed and proteins identified via proteomics. To characterize bacterial morphology changes in response to PBP binding, high-throughput flow cytometry and time-lapse confocal microscopy with fluorescent probes provide unprecedented mechanistic insights. Moreover, novel assays to quantify cytosolic receptor binding and intracellular drug concentrations inform target site occupancy. These mechanistic data are integrated by quantitative and systems pharmacology modeling to maximize bacterial killing and minimize resistance in in vitro and mouse infection models. This translational approach holds promise to identify antibiotic combination dosing strategies for patients with serious infections.

Synthesis and Structure–Activity Relationship of Thioacetamide-Triazoles against Escherichia coli

“…Substitutions to the central acetamide linker section were more nuanced, the introduction of a methyl branch substantially decreased antibacterial activity, but the isomeric propionamide and N-benzamide systems retained activity. A primary challenge in Gram-negative drug discovery is understanding the SAR rules of MIC activity, which is a combination of the ability of the inhibitor to penetrate and accumulate into the bacterial cytoplasm, and its ability to inhibit the molecular target [19]. In this case, the TAT series has many desirable properties previously reported for To complement this study a subseries of compounds was generated, designed to increase intracellular accumulation by the incorporation of basic cycloalkyl rings to the aryl motif.…”

“…A primary challenge in Gram-negative drug discovery is understanding the SAR rules of MIC activity, which is a combination of the ability of the inhibitor to penetrate and accumulate into the bacterial cytoplasm, and its ability to inhibit the molecular target [ 19 ]. In this case, the TAT series has many desirable properties previously reported for Gram-negative entry, including a low molecular weight and polarity range [ 20 ].…”

Informing and Validating Translational Mechanism‐Based Models for Antibiotics by Experimental and Computational Approaches

“…In excellent agreement with results from mouse infection models and beneficial clinical outcomes (refs. 10 to 12 in Lang et al 6 ), 40% fT >MIC yielded zero to one log 10 killing and 60-75% fT >MIC near-maximal bacterial killing at 24 hours. At the higher inoculum, bacterial killing was predicted to be slower and the trough viable counts were predicted to occur slightly later compared with the low inoculum.…”

“…2,3 Thus, when informed by data at three inocula, MBMs can provide excellent predictive performance. [2][3][4][5][6] Jumbe et al (ref. 26 in Lang et al 6 ) pioneered how to prospectively and externally validate bacterial killing and resistance emergence for fluoroquinolones (using antibiotic-containing agar plates and polymerase chain reaction). Their model successfully predicted the time course of killing and resistance in mice and the probability for resistance emergence in patients with nosocomial pneumonia.…”

“…Contrary to Rayner et al, 1 previous studies have clearly shown that MBMs can both describe the observed inoculum effects and provide excellent predictions in internal and external validations, if MBMs are carefully informed and validated. [2][3][4][5][6] This letter provides a perspective on such strategies.…”