4.7 Review

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

Journal

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
Volume 18, Issue -, Pages 1838-1851

Publisher

ELSEVIER
DOI: 10.1016/j.csbj.2020.06.032

Keywords

RiPP; Genome mining; Bioinformatics; Antibiotic; Natural product; Biosynthesis

Funding

  1. Biotechnology and Biological Sciences Research Council Norwich Research Park Doctoral Training Partnership grant [BB/M011216/1]
  2. Royal Society University Research Fellowship
  3. BBSRC [BBS/E/J/000PR9790, 1800125] Funding Source: UKRI

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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. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

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