Integration of sequence and reaction data for the design and engineering of methionine adenosyltransferases and other SAM–dependent enzymes

整合序列和反应数据，用于甲硫氨酸腺苷转移酶和其他 SAM 依赖性酶的设计和工程

• 批准号: 530620831
• 负责人: Professorin Dr. Jennifer Andexer
• 金额: --
• 依托单位: Abteilung für Technische Biochemie
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/530620831?language=en
• 关键词: Integration; sequence; reaction; data; design

In this project P8, an integrated computational platform for analysing data on sequence, structure, and function of enzymes will be developed and applied to design tailored methionine adenosyltransferases (MATs) with an altered substrate profile. In cells, MATs produce S adenosylmethionine (SAM) from 5´-adenosine triphosphate (ATP) and L-methionine. The target for the envisioned enzyme variants is the control of the enzyme’s discrimination of L- and D-methionine. In addition to selective variants, also unselective variants will be designed and characterised. The integrated platform will be developed alongside the MAT project and comprises bioinformatics workflows and a research data management toolbox for biocatalytic data. The bioinformatics workflows are applied for studying sequence-function relationships, finding new enzyme candidates in sequence databases, and designing highly enriched mutant libraries. The research data management toolbox is based on the standardised data exchange format EnzymeML and is applied for managing, analysing, and publishing experimental and modelling results according to the FAIR data principles. The platform development is a collaborative project using existing tools such as GitHub, Jupyter, the Biopython library, and Galaxy, and incorporates existing databases, formats, and standards. The platform is used by all FOR partners, who will be enabled to install it locally, adapt it to their needs, and apply if for analyzing and publishing their data and for sharing methods and results. The computational tools developed in P8 are reusable and extensible, the workflows enable reproducibility of data analysis, and the use of standardized formats make results interoperable. The tools developed in P8 focus to the needs of the FOR but can be extended and generalized beyond this FOR and thus contribute to the digitalization of (bio)catalytic sciences.

在该项目P8中，将开发用于分析酶的序列，结构和功能数据的集成计算平台，并将其应用于设计具有改变的底物分布的定制甲硫氨酸腺苷转移酶（MAT）。在细胞中，MAT从5 ′-腺苷三磷酸（ATP）和L-甲硫氨酸产生S腺苷甲硫氨酸（SAM）。设想的酶变体的目标是控制酶对L-和D-甲硫氨酸的区分。除了选择性变体之外，还将设计和表征非选择性变体。该集成平台将与MAT项目一起开发，包括生物信息学工作流程和生物催化数据的研究数据管理工具箱。生物信息学工作流程应用于研究序列-功能关系，在序列数据库中发现新的候选酶，以及设计高度富集的突变体文库。研究数据管理工具箱基于标准化数据交换格式EnzymeML，用于根据FAIR数据原则管理、分析和发布实验和建模结果。平台开发是一个合作项目，使用现有的工具，如GitHub，Biopython库和Galaxy，并结合现有的数据库，格式和标准。该平台由所有FOR合作伙伴使用，他们将能够在本地安装该平台，使其适应他们的需求，并应用于分析和发布他们的数据以及共享方法和结果。在P8中开发的计算工具是可重复使用和可扩展的，工作流程使数据分析具有可重复性，标准化格式的使用使结果具有互操作性。P8开发的工具专注于FOR的需求，但可以扩展和推广，从而有助于（生物）催化科学的数字化。