Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA.
Center for Synthetic Biology, Northwestern University, Evanston, IL, 60208, USA.
BMC Bioinformatics. 2023 Mar 22;24(1):106. doi: 10.1186/s12859-023-05149-8.
Biochemical reaction prediction tools leverage enzymatic promiscuity rules to generate reaction networks containing novel compounds and reactions. The resulting reaction networks can be used for multiple applications such as designing novel biosynthetic pathways and annotating untargeted metabolomics data. It is vital for these tools to provide a robust, user-friendly method to generate networks for a given application. However, existing tools lack the flexibility to easily generate networks that are tailor-fit for a user's application due to lack of exhaustive reaction rules, restriction to pre-computed networks, and difficulty in using the software due to lack of documentation.
Here we present Pickaxe, an open-source, flexible software that provides a user-friendly method to generate novel reaction networks. This software iteratively applies reaction rules to a set of metabolites to generate novel reactions. Users can select rules from the prepackaged JN1224min ruleset, derived from MetaCyc, or define their own custom rules. Additionally, filters are provided which allow for the pruning of a network on-the-fly based on compound and reaction properties. The filters include chemical similarity to target molecules, metabolomics, thermodynamics, and reaction feasibility filters. Example applications are given to highlight the capabilities of Pickaxe: the expansion of common biological databases with novel reactions, the generation of industrially useful chemicals from a yeast metabolome database, and the annotation of untargeted metabolomics peaks from an E. coli dataset.
Pickaxe predicts novel metabolic reactions and compounds, which can be used for a variety of applications. This software is open-source and available as part of the MINE Database python package ( https://pypi.org/project/minedatabase/ ) or on GitHub ( https://github.com/tyo-nu/MINE-Database ). Documentation and examples can be found on Read the Docs ( https://mine-database.readthedocs.io/en/latest/ ). Through its documentation, pre-packaged features, and customizable nature, Pickaxe allows users to generate novel reaction networks tailored to their application.
生化反应预测工具利用酶的多功能性规则来生成包含新化合物和反应的反应网络。生成的反应网络可用于多种应用,如设计新的生物合成途径和注释非靶向代谢组学数据。对于这些工具来说,提供一种强大的、用户友好的方法来为给定的应用生成网络是至关重要的。然而,由于缺乏详尽的反应规则、对预先计算的网络的限制以及由于缺乏文档而难以使用软件,现有的工具缺乏为用户的应用轻松生成网络的灵活性。
在这里,我们提出了 Pickaxe,这是一个开源的、灵活的软件,它提供了一种用户友好的方法来生成新的反应网络。该软件迭代地将反应规则应用于一组代谢物以生成新的反应。用户可以从预包装的 JN1224min 规则集中选择规则,这些规则源自 MetaCyc,也可以定义自己的自定义规则。此外,还提供了过滤器,可以根据化合物和反应的性质对网络进行实时修剪。这些过滤器包括与目标分子的化学相似性、代谢组学、热力学和反应可行性过滤器。给出了示例应用,以突出 Pickaxe 的功能:用新反应扩展常见的生物数据库、从酵母代谢组数据库生成工业有用的化学品以及注释来自大肠杆菌数据集的非靶向代谢组学峰。
Pickaxe 预测新的代谢反应和化合物,可用于多种应用。该软件是开源的,并作为 MINE 数据库 Python 包(https://pypi.org/project/minedatabase/)的一部分或在 GitHub(https://github.com/tyo-nu/MINE-Database)上提供。文档和示例可在 Read the Docs(https://mine-database.readthedocs.io/en/latest/)上找到。通过其文档、预包装的功能和可定制的性质,Pickaxe 允许用户生成适合其应用的新反应网络。