Dataset Information

A prevalent peptide-binding domain guides ribosomal natural product biosynthesis.

ABSTRACT: Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a rapidly growing class of natural products. RiPP precursor peptides can undergo extensive enzymatic tailoring to yield structurally and functionally diverse products, and their biosynthetic logic makes them attractive bioengineering targets. Recent work suggests that unrelated RiPP-modifying enzymes contain structurally similar precursor peptide-binding domains. Using profile hidden Markov model comparisons, we discovered related and previously unrecognized peptide-binding domains in proteins spanning the majority of known prokaryotic RiPP classes, and we named this conserved domain the RiPP precursor peptide recognition element (RRE). Through binding studies we verified RRE's roles for three distinct RiPP classes: linear azole-containing peptides, thiopeptides and lasso peptides. Because numerous RiPP biosynthetic enzymes act on peptide substrates, our findings have powerful predictive value as to which protein(s) drive substrate binding, thereby laying a foundation for further characterization of RiPP biosynthetic pathways and the rational engineering of new peptide-binding activities.

SUBMITTER: Burkhart BJ

PROVIDER: S-EPMC4509860 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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A prevalent peptide-binding domain guides ribosomal natural product biosynthesis.

Burkhart Brandon J BJ Hudson Graham A GA Dunbar Kyle L KL Mitchell Douglas A DA

Nature chemical biology 20150713 8

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a rapidly growing class of natural products. RiPP precursor peptides can undergo extensive enzymatic tailoring to yield structurally and functionally diverse products, and their biosynthetic logic makes them attractive bioengineering targets. Recent work suggests that unrelated RiPP-modifying enzymes contain structurally similar precursor peptide-binding domains. Using profile hidden Markov model comparisons, we disco ...[more]

PMID: 26167873

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Project description:Natural products are molecules that fulfil a range of important ecological functions. Many natural products have been exploited for pharmaceutical and agricultural applications. In contrast to many other specialised metabolites, the products of modular nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) systems can often (partially) be predicted from the DNA sequence of the biosynthetic gene clusters. This is because the biosynthetic pathways of NRPS and PKS systems adhere to consistent rulesets. These universal biosynthetic rules can be leveraged to generate biosynthetic models of biosynthetic pathways. While these principles have been largely deciphered, software that leverages these rules to automatically generate visualisations of biosynthetic models has not yet been developed. To enable high-quality automated visualisations of natural product biosynthetic pathways, we developed RAIChU (Reaction Analysis through Illustrating Chemical Units), which produces depictions of biosynthetic transformations of PKS, NRPS, and hybrid PKS/NRPS systems from predicted or experimentally verified module architectures and domain substrate specificities. RAIChU also boasts a library of functions to perform and visualise reactions and pathways whose specifics (e.g., regioselectivity, stereoselectivity) are still difficult to predict, including terpenes, ribosomally synthesised and posttranslationally modified peptides and alkaloids. Additionally, RAIChU includes 34 prevalent tailoring reactions to enable the visualisation of biosynthetic pathways of fully maturated natural products. RAIChU can be integrated into Python pipelines, allowing users to upload and edit results from antiSMASH, a widely used BGC detection and annotation tool, or to build biosynthetic PKS/NRPS systems from scratch. RAIChU's cluster drawing correctness (100%) and drawing readability (97.66%) were validated on 5000 randomly generated PKS/NRPS systems, and on the MIBiG database. The automated visualisation of these pathways accelerates the generation of biosynthetic models, facilitates the analysis of large (meta-) genomic datasets and reduces human error. RAIChU is available at https://github.com/BTheDragonMaster/RAIChU and https://pypi.org/project/raichu .Scientific contributionRAIChU is the first software package capable of automating high-quality visualisations of natural product biosynthetic pathways. By leveraging universal biosynthetic rules, RAIChU enables the depiction of complex biosynthetic transformations for PKS, NRPS, ribosomally synthesised and posttranslationally modified peptide (RiPP), terpene and alkaloid systems, enhancing predictive and analytical capabilities. This innovation not only streamlines the creation of biosynthetic models, making the analysis of large genomic datasets more efficient and accurate, but also bridges a crucial gap in predicting and visualising the complexities of natural product biosynthesis.

Dataset Information

A prevalent peptide-binding domain guides ribosomal natural product biosynthesis.

Publications

A prevalent peptide-binding domain guides ribosomal natural product biosynthesis.

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