Structural engineering of antimicrobials for optimal broad-spectrum activity

IF 9.1 Q1 ENGINEERING, CHEMICAL Green Chemical Engineering Pub Date : 2023-12-14 DOI:10.1016/j.gce.2023.12.001
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Abstract

Antimicrobial materials are a crucial component in eradicating and managing the spread of infectious diseases. They are expected to act on a broad-spectrum of microbes, including emerging pathogens which could cause the next Disease X. Herein, we reassessed a series of antimicrobial imidazolium polymers on our shelves and uncovered extended functionality through dual modes of action. By redesigning their structures, a truly broad-spectrum antimicrobial material with optimized activity against bacteria (G ​+ve, G -ve) and fungi, as well as enveloped and non-enveloped viruses was developed. We demonstrated that the imidazolium polymer exhibits dual modes of function against microbes: targeting the microbial membrane and binding DNA. The latter DNA binding affinity was found to be key against non-enveloped viruses. With this insight, we designed small molecule compounds that exhibited optimum broad-spectrum antimicrobial activity and excellent efficacy against ESKAPE group of pathogens that are responsible for some of the deadliest nosocomial infections worldwide. Our results could also shed light on the design of broad-spectrum antimicrobial compounds against Disease X.

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抗菌剂的结构工程,实现最佳广谱活性
抗菌材料是消除和控制传染病传播的重要组成部分。在此,我们对货架上的一系列抗菌咪唑聚合物进行了重新评估,并通过双重作用模式发现了其扩展功能。通过重新设计其结构,我们开发出了一种真正的广谱抗菌材料,对细菌(G +ve、G -ve)、真菌以及包膜和非包膜病毒具有最佳活性。我们证明,咪唑聚合物对微生物具有双重作用模式:靶向微生物膜和结合 DNA。我们发现,后者的 DNA 结合亲和力是对抗无包膜病毒的关键。有了这一认识,我们设计的小分子化合物表现出了最佳的广谱抗菌活性,对 ESKAPE 类病原体具有卓越的疗效,这些病原体是造成全球一些最致命的院内感染的罪魁祸首。我们的研究结果还有助于设计针对 X 病的广谱抗菌化合物。
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来源期刊
Green Chemical Engineering
Green Chemical Engineering Process Chemistry and Technology, Catalysis, Filtration and Separation
CiteScore
11.60
自引率
0.00%
发文量
58
审稿时长
51 days
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OFC: Outside Front Cover Outside Back Cover Outside Back Cover OFC: Outside Front Cover Integration of physical information and reaction mechanism data for surrogate prediction model and multi-objective optimization of glycolic acid production
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