Predictive Guidelines for Penetrance and Discovery of Broad-Spectrum Antibiotics

广谱抗生素外显率和发现的预测指南

基本信息

批准号：
10326787
负责人：
Paul Hergenrother
金额：
$ 114.09万
依托单位：
UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-02-06 至 2024-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10326787
关键词：
Acinetobacter Acute Amines Anti-Bacterial Agents Antibiotics Area Bacteria Biological Assay Cell membrane Cells Charge Chemicals Classification Collection Computational algorithm Computer Models Critical Pathways Data Development Drug Screening Drug resistance Drug usage Escherichia coli Failure Fusidic Acid Gram-Negative Bacteria Gram-Negative Bacterial Infections Guidelines Individual Infection Literature Membrane Methods Modeling Molecular Multi-Drug Resistance Mus Mutate National Institute of Allergy and Infectious Disease Nature Penetrance Pharmaceutical Preparations Property Pseudomonas aeruginosa Publications Resistance Scientist Training VDAC1 gene Variant World Health Organization carbapenem-resistant Enterobacteriaceae efflux pump experimental study flexibility functional group novel novel drug class outcome prediction pathogen pathogenic bacteria prevent random forest screening simulation tool trait

项目摘要

PROJECT SUMMARY/ABSTRACT The percent of Gram-negative bacterial infections that are resistant to common antibiotics has increased at an alarming rate over the last decade, and there is now an acute need for the discovery of novel antibiotics effective against multidrug-resistant Gram-negative pathogens. The standard method of antibacterial discovery – whole- cell screening of compound collections – has met with repeated failure for Gram-negatives, and these failures have been traced to the fact that very few compounds in standard collections can penetrate the Gram-negative cell membranes and accumulate in these pathogens. Unfortunately, there has been scant information about the types of compounds that are competent for accumulation in Gram-negatives. Excitingly, we recently assessed a unique collection of >180 diverse compounds for their ability to accumulate in E. coli, trained a random forest classification model to analyze the results, and from this data we identified physicochemical properties important for accumulation and developed predictive guidelines for compound accumulation in E. coli. We then showed the utility of these guidelines by converting a Gram-positive-only antibiotic into a broad-spectrum agent. We now propose to develop tools that will allow us to fully define the physicochemical traits that enable compounds accumulation in three of the most concerning Gram-negative bacteria, carbapenem-resistant Enterobacteriaceae (CRE), drug-resistant Acinetobacter, and drug-resistant P. aeruginosa (to be referred to collectively as EAP pathogens). Specifically, we seek to develop novel tools in the area of chemical probes (compound collections), bacterial strains, and computational models. Using these tools in conjunction with our well-validated compound accumulation assay, we intend to define the physicochemical traits needed for compound accumulation in the EAP pathogens, including assessment of the influence of porins and efflux pumps, and the relative contribution of the outer and inner-membranes to blocking compound penetrance. Our predictive guidelines will be utilized to convert several high-value Gram-positive-only compounds into broad- spectrum antibiotics.

项目摘要/摘要在在过去的十年中，令人震惊的速度令人震惊，现在急需发现新型抗生素有效针对抗多药的革兰氏阴性病原体。抗菌发现的标准方法 - 整个化合物收集的细胞筛选 - 已经遇到了革兰氏阴性剂的反复失败，这些失败已经追溯到这样一个事实，即标准集合中很少的化合物可以穿透革兰氏阴性细胞膜并积聚在这些病原体中。不幸的是，关于能够在革兰氏阴性剂中积累的化合物类型。令人兴奋的是，我们最近评估了独特的> 180名潜水员化合物的独特集合，可以在大肠杆菌中积聚，训练了一个随机森林分类模型以分析结果，从这些数据中，我们确定了物理特性很重要用于积累和制定的预测指南，用于在大肠杆菌中复合积累。然后我们展示了这些准则通过将革兰氏阳性的抗生素转化为广谱剂的实用性。我们现在提出开发工具的建议，使我们能够完全定义启用化合物的物理特征在三种最令人关注的革兰氏阴性细菌中积聚肠杆菌科（CRE），耐药性杆菌和耐药性铜绿假单胞菌（请参考集体作为EAP病原体）。具体来说，我们试图在化学问题领域开发新颖的工具（化合物集合），细菌菌株和计算模型。将这些工具与我们结合使用精心验证的复合积累测定法，我们打算定义 EAP病原体中的复合积累，包括评估孔蛋白和外排的影响泵，外膜和内膜对阻断复合渗透的相对贡献。我们的预测指南将用于将几种高价值革兰氏阳性化合物转换为广泛的光谱抗生素。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（1）

Compound Uptake into E. coli Can Be Facilitated by N-Alkyl Guanidiniums and Pyridiniums.

DOI：
10.1021/acsinfecdis.0c00715
发表时间：
2021-01-08
期刊：
ACS infectious diseases
影响因子：
5.3
作者：
Perlmutter SJ;Geddes EJ;Drown BS;Motika SE;Lee MR;Hergenrother PJ
通讯作者：
Hergenrother PJ

Synthesis of Fusidic Acid Derivatives Yields a Potent Antibiotic with an Improved Resistance Profile.

DOI：
10.1021/acsinfecdis.0c00869
发表时间：
2021-02-12
期刊：
ACS infectious diseases
影响因子：
5.3
作者：
Garcia Chavez M;Garcia A;Lee HY;Lau GW;Parker EN;Komnick KE;Hergenrother PJ
通讯作者：
Hergenrother PJ

Facilitating Compound Entry as a Means to Discover Antibiotics for Gram-Negative Bacteria.

DOI：
10.1021/acs.accounts.0c00895
发表时间：
2021-03-16
期刊：
Accounts of chemical research
影响因子：
18.3
作者：
Muñoz KA;Hergenrother PJ
通讯作者：
Hergenrother PJ

Allylic C-H amination cross-coupling furnishes tertiary amines by electrophilic metal catalysis.

DOI：
10.1126/science.abn8382
发表时间：
2022-04-15
期刊：
SCIENCE
影响因子：
56.9
作者：
Ali, Siraj Z.;Budaitis, Brenna G.;Fontaine, Devon F. A.;Pace, Andria L.;Garwin, Jacob A.;White, M. Christina
通讯作者：
White, M. Christina

An LC-MS/MS assay and complementary web-based tool to quantify and predict compound accumulation in E. coli.

LC-MS/MS 测定和基于网络的补充工具，用于量化和预测大肠杆菌中的化合物积累。