Evidence map›Paper›PMID 37186644›Full record

ArticlePLoS computational biology2023

Knowledge-guided data mining on the standardized architecture of NRPS: Subtypes, novel motifs, and sequence entanglements.

Ruolin He, Jinyu Zhang, Yuanzhe Shao, Shaohua Gu, Chen Song, Long Qian, Wen-Bing Yin, Zhiyuan Li

Abstract read
In one paragraph

Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ruolin HeCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.ORCID 0000-0003-2163-5526
Jinyu ZhangState Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, PR China.
Yuanzhe ShaoPeking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
Shaohua GuCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
Chen SongCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.ORCID 0000-0001-9730-3216
Long QianCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.ORCID 0000-0003-3728-7917
Wen-Bing YinState Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, PR China.ORCID 0000-0002-9184-3198
Zhiyuan LiCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.ORCID 0000-0001-6662-2636

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

PeptidesPeptide Synthasesnon-ribosomal peptide synthasePeptidesPeptide Synthases

Identifiers

PMID37186644
PMCPMC10212144

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.