RxnCluster:一个基于网络的工具,通过数字化典型的生物合成模式来探索导致目标分子的反应簇。

IF 3.9 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Shaozhen Ding, Yu Tian, Dongliang Liu, Dachuan Zhang, HuaDong Xing, Junni Chen, Zhiguo Liu and Qian-Nan Hu*, 
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引用次数: 0

摘要

生产靶分子的生物合成途径可以看作是一系列连续的反应,也可以被数字化为生产类似物的典型生物合成模式(反应规则簇)。传统的路径设计方法只考虑单个步骤的反应规则,而忽略了跨多个步骤的更有效的合成策略。分子的结构是拓扑的,可以分为多个子结构;具有一个或多个相同亚结构片段的不同分子可能具有相似的生物合成策略。本文基于基因簇的概念,首次将典型的生物合成模式数字化,构建了一个用户友好型平台(RxnCluster)。RxnCluster包含14,378种生物合成模式(反应规则簇),涵盖37,317种反应组合(反应簇),其步骤数从1到4不等。结果表明,该平台可以识别不同步数的反应簇,与湿法实验室的实验结果一致。此外,它还可以识别其他尚未报道的新反应簇,这将为通过不同策略进行分子生物合成的途径挖掘铺平道路。RxnCluster可从http://design.rxnfinder.org/rxncluster/获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

RxnCluster: A Web-Based Tool for Exploring Reaction Clusters Leading to Target Molecules by Digitalizing Typical Biosynthetic Patterns

RxnCluster: A Web-Based Tool for Exploring Reaction Clusters Leading to Target Molecules by Digitalizing Typical Biosynthetic Patterns

Biosynthetic pathways for producing target molecules can be regarded as series of sequential reactions that can also be digitalized as typical biosynthetic patterns (reaction rule clusters) for producing analogs. Conventional methods for pathway design in silico consider only reaction rules with a single step, which neglect the more efficient synthetic strategies crossing multiple steps. The structure of a molecule is topological and can be divided into multiple substructures; different molecules with one or more identical substructure fragments may have similar biosynthetic strategies. Here, based on the concept of gene clusters, we constructed a user-friendly platform (RxnCluster) by digitalizing the typical biosynthetic patterns for the first time. RxnCluster contains 14,378 biosynthetic patterns (reaction rule clusters) covering 37,317 reaction combinations (reaction clusters) whose numbers of steps vary from 1 to 4. According to the results, this platform can identify the reaction clusters in various numbers of steps, which are consistent with the experimental results obtained in wet laboratories. In addition, it can identify other novel reaction clusters that have not yet been reported, which will pave the way toward pathway mining for molecule biosynthesis via different strategies. RxnCluster is available at http://design.rxnfinder.org/rxncluster/.

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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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