Konanov Dmitry N, Krivonos Danil V, Ilina Elena N, Babenko Vladislav V
Federal Research and Clinical Centre of Physical and Chemical Medicine, Federal Medical and Biological Agency of Russia, ul. Malaya Pirogovskaya., 1s3, Moscow 119435, Russian Federation.
Comput Struct Biotechnol J. 2022 Mar 4;20:1218-1226. doi: 10.1016/j.csbj.2022.02.013. eCollection 2022.
Nonribosomal peptides are a class of secondary metabolites synthesized by multimodular enzymes named nonribosomal peptide synthetases and mainly produced by bacteria and fungi. NMR, LC-MS/MS and other analytical methods allow to determine a peptide structure precisely, but it is often not a trivial task to find natural producers of them. There are cases when potential producers should be found among hundreds of strains, for instance, when analyzing metagenomic data. We have developed BioCAT, a tool designed for finding biosynthetic gene clusters which may produce a given nonribosomal peptide when the structure of an interesting nonribosomal peptide has already been found. BioCAT unites the antiSMASH software and the rBAN retrosynthesis tool but some improvements were added to both gene cluster and peptide structure analysis. The main feature of the method is an implementation of a position-specific score matrix to store specificities of nonribosomal peptide synthetase modules, which has increased the alignment sensitivity in comparison with more strict approaches developed earlier. We tested the method on a manually curated nonribosomal peptide producers database and compared it with competing tools GARLIC and Nerpa. Finally, we showed the method's applicability on several external examples.
非核糖体肽是一类由名为非核糖体肽合成酶的多模块酶合成的次生代谢产物,主要由细菌和真菌产生。核磁共振(NMR)、液相色谱-串联质谱(LC-MS/MS)等分析方法能够精确确定肽的结构,但找到它们的天然生产者往往并非易事。例如,在分析宏基因组数据时,有时需要在数百个菌株中寻找潜在的生产者。我们开发了BioCAT,这是一种在已发现感兴趣的非核糖体肽结构时,用于寻找可能产生给定非核糖体肽的生物合成基因簇的工具。BioCAT整合了antiSMASH软件和rBAN逆合成工具,但在基因簇和肽结构分析方面都做了一些改进。该方法的主要特点是实现了一个位置特异性评分矩阵来存储非核糖体肽合成酶模块的特异性,与早期开发的更严格方法相比,提高了比对灵敏度。我们在一个人工整理的非核糖体肽生产者数据库上测试了该方法,并将其与竞争工具GARLIC和Nerpa进行了比较。最后,我们展示了该方法在几个外部实例中的适用性。