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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.

项目总结/摘要革兰氏阴性菌感染对常用抗生素耐药的百分比以1.5%的速度增加。在过去的十年里，这种疾病的发生率令人震惊，现在迫切需要发现有效的新型抗生素。对抗多重耐药革兰氏阴性病原体。抗菌剂发现的标准方法-整体- 细胞筛选的化合物收集-遇到了反复失败的革兰氏阴性，这些失败已经被追溯到这样一个事实，即在标准集合中很少有化合物可以渗透革兰氏阴性菌，细胞膜并在这些病原体中积累。不幸的是，关于这方面的信息很少。能够在革兰氏阴性菌中蓄积的化合物类型。令人兴奋的是，我们最近评估了一个超过180种不同化合物的独特集合，因为它们能够在E.大肠杆菌，训练了一个随机森林分类模型来分析结果，并从这些数据中我们确定了重要的物理化学性质积累，并制定了预测准则的化合物积累E。杆菌然后我们展示了通过将仅革兰氏阳性抗生素转化为广谱抗生素来利用这些指南。我们现在我建议开发工具，使我们能够充分定义使化合物的物理化学特性，在三种最受关注的革兰氏阴性菌、碳青霉烯类耐药菌肠杆菌科（CRE）、耐药不动杆菌和耐药铜绿假单胞菌（参考统称为EAP病原体）。具体来说，我们寻求在化学探针领域开发新的工具（化合物集合）、细菌菌株和计算模型。将这些工具与我们的充分验证的化合物积累试验，我们打算定义所需的理化性状，化合物在EAP病原体中的积累，包括评估孔蛋白和外排的影响泵，以及外膜和内膜对阻断化合物渗透率的相对贡献。我们预测指南将用于将几种高价值的革兰氏阳性化合物转化为广泛的广谱抗生素

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

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。

DOI：
10.1038/s41596-021-00598-y
发表时间：
2021-10
期刊：
Nature protocols
影响因子：
14.8
作者：
Geddes EJ;Li Z;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