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Antimicrobial Proteins

Antimicrobial Proteins

Antimicrobial proteins are important components of the immune system. They aid the body in combating pathogens by either killing them directly or hindering their replication processes. Four main types of antimicrobial substances are interferons, the complement system, iron-binding proteins, and antimicrobial proteins.
Interferons
Interferons (IFNs) are proteins produced by lymphocytes, macrophages, and fibroblasts infected with viruses. While IFNs cannot prevent viruses from entering and...

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Anti-virulent Disruption of Pathogenic Biofilms using Engineered Quorum-quenching Lactonases

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机器学习模型识别了新德里的金属β-乳酸酶抑制剂.

Zishuo Cheng¹, Mahesh Aitha², Caitlyn A Thomas¹

¹Department of Chemistry and Biochemistry, Miami University, Oxford ,Ohio 45056, United States.

Journal of chemical information and modeling

|May 10, 2024

概括

此摘要是机器生成的。

新德里金属β-乳糖酶-1 (NDM-1) 威胁着抗生素的疗效. 研究人员开发了一种机器学习工具,以识别一种新型抑制剂,化合物72922413,该化合物恢复了对NDM-1生产细菌的美罗的有效性.

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科学领域:

抗微生物耐药性抗微生物耐药性
药物发现药物发现
计算化学是一种计算化学.

背景情况:

金属β-乳糖酶 (MBLs),特别是NDM-1,对关键β-乳糖抗生素的有效性构成越来越大的全球威胁.
临床管道中缺乏经批准的MBL抑制剂,尽管使用高通量查 (HTS) 和基于碎片的药物发现 (FBDD) 等方法进行了广泛的研究.

研究的目的:

开发和应用基于机器学习 (ML) 的预测工具,用于识别新型金属β-乳糖酶抑制剂.
为了验证计算机识别的抑制剂对NDM-1产生细菌的疗效.

主要方法:

在HTS数据上训练了一种机器学习模型,并发布了抑制数据.
使用ML工具对NIH创世纪图书馆进行虚拟选,然后进行定量HTS (qHTS).
使用生物物理技术和分子对接,研究了抑制机制.

主要成果:

一种新的MBL抑制剂,化合物72922413,通过ML驱动的虚拟查和qHTS被确定.
化合物72922413在临床孤立的*E. coli*和*K. pneumoniae*表达NDM-1的临床分离物中显示出降低美罗最小抑制度 (MIC) 的能力.
这项研究阐明了这种新的pyrido[1,2-a]pyrimidin-4-one支架的抑制机制.

结论:

机器学习与HTS相结合是发现新型抗生素耐药性抑制剂的有效策略.
化合物72922413代表了开发针对NDM-1-介导的卡巴胺耐药性的新疗法的有前途的头.
进一步开发这种抑制剂可能有助于对抗多药耐药细菌日益增长的威胁.