Combating resistant superbugs by understanding the molecular determinants of target site penetration and binding

通过了解目标位点渗透和结合的分子决定因素来对抗耐药超级细菌

• 批准号: 9761971
• 负责人: Jurgen Bernd Bulitta
• 金额: $ 113.46万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-10 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9761971
• 关键词: Acinetobacter baumannii; Antibiotic Therapy; Antibiotics; Bacteria; Binding; Biological Assay; Blood Circulation; Cell Membrane Permeability; Cells; Chemical Structure; Combined Antibiotics; Combined Modality Therapy; Dangerousness; Data; Descriptor; Dose; Folic Acid Antagonists; Genetic Engineering; Goals; Gram-Negative Bacteria; Health; Healthcare Systems; Human; Immune system; In Vitro; Infection; Klebsiella pneumonia bacterium; Knock-out; Lactamase; Libraries; Measures; Membrane; Modeling; Molecular; Morbidity - disease rate; Multi-Drug Resistance; Multidrug-resistant Acinetobacter; Mus; Nosocomial Infections; Nutrient; Patients; Penetration; Permeability; Pharmaceutical Preparations; Pharmacology; Property; Proteomics; Pseudomonas aeruginosa; Pump; Regimen; Research; Resistance; Respiratory System; Scheme; Series; Site; Structure; Superbug; System; Time; Treatment Efficacy; United States; Up-Regulation; Urinary tract; VDAC1 gene; Vertebral column; World Health Organization; base; beta-Lactamase; beta-Lactams; cellular imaging; combat; cost; design; efflux pump; extracellular; global health; improved; in vivo; inhibitor/antagonist; innovation; insight; molecular phenotype; mortality; multidisciplinary; novel; periplasm; predictive modeling; prevent; prospective; receptor; receptor binding; receptor expression; tool; uptake; wound

Project Summary/Abstract A severe lack of effective antibiotic treatment options against multidrug-resistant (MDR) Gram-negative bacteria (i.e., “superbugs”) is causing one of the world’s three most serious human health threats. Exacerbating this is a dramatic decline in the number of new antibiotics effective against MDR Acinetobacter baumannii, Klebsiella pneumoniae and Pseudomonas aeruginosa. These “superbugs” cause serious bloodstream, respira- tory and urinary tract, wound, and other infections with very high morbidity and up to 80% mortality. Many antibiotics have extremely poor penetration to their target site, especially in A. baumannii and P. aeruginosa. For these antibiotics, the combination of poor target site penetration and extensive efflux causes the antibiotic concentration at the target site to be over 1,000-fold lower than that of the extracellular antibiotic concentration. Unsurprisingly, many antibiotic candidates fail because of poor penetration to and/or extensive efflux from their bacterial target site. Importantly, there are very substantial gaps in the current understanding of how to maximize the antibiotic target site penetration, avoid efflux from bacterial cells, and thereby maximize receptor binding. This multi-disciplinary project, however, will identify the molecular determinants of how to maximize antibiotic target site concentrations and receptor binding to combat resistant “superbugs”. Our preliminary data and models demonstrate that molecular descriptors can predict the antibiotic target site penetration and effect of multiple efflux pumps in P. aeruginosa. We have developed a series of assays that characterize the penetration of key selected antibiotics to their periplasmic or cytosolic target sites and antibiotic binding to their receptors in intact bacteria. In Aim 1, these new molecular and phenotypic assays will be greatly extended and applied to all three “superbugs”; additionally, a series of isogenic efflux pump knockout strains will be created. The resulting data will uniquely inform novel quantitative models (Aim 2) that can predict penetration, efflux, and thus receptor binding at the bacterial target sites based on molecular antibiotic properties. These models will enable the targeted synthesis of key selected antibiotic probes (Aim 3) that are used to prospectively validate these predictive models. These new probes will serve as the backbone of innovative antibiotic combi- nation dosing strategies that will be rationally optimized via Quantitative and Systems Pharmacology models in Aim 4. Dynamic in vitro and murine infection models with an intact or compromised immune system will then prospectively evaluate these combination regimens. These models can simulate antibiotic concentration-time profiles that mirror those in patients. Overall, this project will provide the molecular insights that enable drug developers to design new antibiotics that achieve high concentrations at their bacterial target site and thereby improve receptor binding. This approach and the targeted new antibiotic probes synthesized in this project hold excellent promise to substantially contribute to combating the three MDR Gram-negative “superbugs”.

项目总结/文摘