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Knowledge-guided data mining on the standardized architecture of NRPS: Subtypes, novel motifs, and sequence entanglements.
He, Ruolin; Zhang, Jinyu; Shao, Yuanzhe; Gu, Shaohua; Song, Chen; Qian, Long; Yin, Wen-Bing; Li, Zhiyuan.
Afiliação
  • He R; Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
  • Zhang J; State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, PR China.
  • Shao Y; Savaid Medical School, University of Chinese Academy of Sciences, Beijing, PR China.
  • Gu S; Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
  • Song C; Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
  • Qian L; Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
  • Yin WB; Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
  • Li Z; Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
PLoS Comput Biol ; 19(5): e1011100, 2023 05.
Article em En | MEDLINE | ID: mdl-37186644
ABSTRACT
Non-ribosomal peptide synthetase (NRPS) is a diverse family of biosynthetic enzymes for the assembly of bioactive peptides. Despite advances in microbial sequencing, the lack of a consistent standard for annotating NRPS domains and modules has made data-driven discoveries challenging. To address this, we introduced a standardized architecture for NRPS, by using known conserved motifs to partition typical domains. This motif-and-intermotif standardization allowed for systematic evaluations of sequence properties from a large number of NRPS pathways, resulting in the most comprehensive cross-kingdom C domain subtype classifications to date, as well as the discovery and experimental validation of novel conserved motifs with functional significance. Furthermore, our coevolution analysis revealed important barriers associated with re-engineering NRPSs and uncovered the entanglement between phylogeny and substrate specificity in NRPS sequences. Our findings provide a comprehensive and statistically insightful analysis of NRPS sequences, opening avenues for future data-driven discoveries.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeo Sintases / Peptídeos Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeo Sintases / Peptídeos Idioma: En Ano de publicação: 2023 Tipo de documento: Article