Deciphering the substrate specificity code of basidiomycete peptide synthetases

完全测序和公开访问担子菌基因组的数量正在快速增加。很明显，在这一多样化的真菌群体中，许多物种都含有遗传物质，用于结构多样化的次级代谢，以生物合成小分子天然产物，其中大多数尚未被鉴定和化学表征。该研究项目通过从基因组序列数据中预测天然产物（部分）结构，缩小了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（NRPSs）和相关蛋白。这些是多结构域酶，催化从一般底物组装复杂的天然产物，如氨基酸，酮酸等。底物特异性和产物的结构特征是由初级NRPS氨基酸序列中的十个位置决定的，这些位置统称为NRPS编码。这个密码对于担子菌来说几乎是未知的。选择担子菌属的多肽合成酶进行体外生化表征，分析底物的特异性，并建立单个底物的nrpps编码。该方法通过对各自的酶/结构域进行计算机建模得到支持。对选定的真菌种类进行化学研究，主要喂食标记的底物，以及天然产物的分离和结构阐明，将验证生化结果。

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.