用自动信息搜索算法探索非核糖体肽家族。

Chemistry & biology Pub Date : 2015-09-17 Epub Date: 2015-09-10 DOI:10.1016/j.chembiol.2015.08.008
Lian Yang, Ashraf Ibrahim, Chad W Johnston, Michael A Skinnider, Bin Ma, Nathan A Magarvey
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引用次数: 9

摘要

微生物天然产物是一些最重要的药物制剂,具有无与伦比的化学多样性。在这里,我们提出了一种非靶向代谢组学算法,该算法建立在我们经过验证的iSNAP平台上,可以快速识别肽天然产物家族。通过利用已知的或在硅去复制的种子结构,该算法筛选串联质谱数据,以高可信度和统计显著性详细阐述粗微生物培养提取物中广泛的分子家族。对肽天然产物生产者的分析揭示了大量未报告的同源物,揭示了迄今为止描述的最大的天然产物家族之一,以及具有更大效力的新变体。这些发现证明了iSNAP平台作为快速分析大型非核糖体肽家族的准确工具的有效性。
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Exploration of Nonribosomal Peptide Families with an Automated Informatic Search Algorithm.

Microbial natural products are some of the most important pharmaceutical agents and possess unparalleled chemical diversity. Here we present an untargeted metabolomics algorithm that builds on our validated iSNAP platform to rapidly identify families of peptide natural products. By utilizing known or in silico-dereplicated seed structures, this algorithm screens tandem mass spectrometry data to elaborate extensive molecular families within crude microbial culture extracts with high confidence and statistical significance. Analysis of peptide natural product producers revealed an abundance of unreported congeners, revealing one of the largest families of natural products described to date, as well as a novel variant with greater potency. These findings demonstrate the effectiveness of the iSNAP platform as an accurate tool for rapidly profiling large families of nonribosomal peptides.

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来源期刊
Chemistry & biology
Chemistry & biology 生物-生化与分子生物学
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审稿时长
4-8 weeks
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