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Deciphering the substrate specificity code of basidiomycete peptide synthetases

破译担子菌肽合成酶的底物特异性代码

基本信息

批准号：
242358822
负责人：
Professor Dr. Dirk Hoffmeister
金额：
--
依托单位：
Lehrstuhl für Pharmazeutische Mikrobiologie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2013
资助国家：
德国
起止时间：
2012-12-31 至 2016-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/242358822?language=en
关键词：
Deciphering substrate specificity code basidiomycete

项目摘要

The number of fully sequenced and publically accessible basidiomycete genomes is increasing at a fast pace. It has become evident that many species within this diverse group of fungi harbor the genetic material for a structurally diverse secondary metabolism to biosynthesize small molecule natural products, the majority of which has not been identified and chemically characterized yet. This research project serves to close this gap between genomics and natural product chemistry by enabling the prediction of natural product (partial) structures from genomic sequence data. The objective is to identify and characterize secondary metabolomes in a more straightforward way. Hence, discovery of new bioactive compounds which may serve as pharmaceutically relevant drug leads is facilitated.This work combines biochemistry, bioinformatics, and natural product chemistry, and focuses on nonribosomal peptide synthetases (NRPSs) and related proteins. These are multidomain enzymes which catalyze the assembly of complex natural products from generic substrates, such as amino acids, keto acids, and others. The substrate specificity and, thus, structural features of the product, is governed by ten positions within the primary NRPS amino acid sequence, which are collectively referred to as NRPS-code. This code is virtually unknown for the basidiomycetes.In vitro biochemical characterization of peptide synthetases of select Basidiomycota species will profile the substrate specificities and establish an NRPS-code for the individual substrates. This approach is supported by modeling the respective enzymes/domains in silico. Chemical investigations with the chosen fungal species, primarily feeding of labeled substrates, and natural product isolation and structure elucidation, will verify biochemical results.

完全测序且可公开获取的担子菌基因组的数量正在快速增加。很明显，这一不同真菌类群中的许多物种都拥有结构多样的次生代谢的遗传物质，以生物合成小分子天然产物，其中大部分尚未被鉴定和化学表征。该研究项目旨在通过基因组序列数据预测天然产物（部分）结构，从而缩小基因组学和天然产物化学之间的差距。目的是以更直接的方式识别和表征次级代谢组。因此，有助于发现可作为药学相关药物先导化合物的新生物活性化合物。这项工作结合了生物化学、生物信息学和天然产物化学，重点研究非核糖体肽合成酶（NRPS）和相关蛋白质。这些是多域酶，可催化从氨基酸、酮酸等通用底物组装复杂的天然产物。底物特异性以及产物的结构特征由初级 NRPS 氨基酸序列内的 10 个位置控制，这些位置统称为 NRPS 代码。该代码对于担子菌来说实际上是未知的。选定担子菌门物种的肽合成酶的体外生化表征将分析底物特异性并为各个底物建立 NRPS 代码。这种方法通过在计算机中模拟相应的酶/结构域来支持。对所选真菌物种的化学研究，主要是标记底物的喂养，以及天然产物的分离和结构阐明，将验证生化结果。