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Genome mining strategies for ribosomally synthesised and post-translationally modified peptides

机译:基因组采矿策略用于核糖体合成和翻译后修饰的肽

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摘要

Genome mining is a computational method for the automatic detection and annotation of biosynthetic gene clusters (BGCs) from genomic data. This approach has been increasingly utilised in natural product (NP) discovery due to the large amount of sequencing data that is now available. Ribosomally synthesised and post-translationally modified peptides (RiPPs) are a class of structurally complex NP with diverse bioactivities. RiPPs have recently been shown to occupy a much larger expanse of genomic and chemical space than previously appreciated, indicating that annotation of RiPP BGCs in genomes may have been overlooked in the past. This review provides an overview of the genome mining tools that have been specifically developed to aid in the discovery of RiPP BGCs, which have been built from an increasing knowledgebase of RiPP structures and biosynthesis. Given these recent advances, the application of targeted genome mining has great potential to accelerate the discovery of important molecules such as antimicrobial and anticancer agents whilst increasing our understanding about how these compounds are biosynthesised in nature.
机译:基因组挖掘是一种从基因组数据自动检测和注释生物合成基因簇(BGC)的计算方法。由于现在可用的大量测序数据,这种方法越来越多地利用了天然产品(NP)发现。核糖体合成和翻译后修饰的肽(RIPP)是一类结构性复合NP,具有不同的生物活化。最近被证明占据了比以前欣赏的基因组和化学空间的更大扩大,表明过去可能忽略了基因组中的RIPP BGCS的注释。本综述概述了专门用于帮助发现RIPP BGCS的基因组采矿工具,该工具是由RIPP结构和生物合成的增加的知识库构建。鉴于这些最新进展,靶向基因组挖掘的应用具有很大的潜力,加速如抗菌重要分子和抗癌药物的发现,同时提高对这些化合物是如何在自然界中生物合成我们的理解。

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