Your browser doesn't support javascript.
loading
BioCAT: Search for biosynthetic gene clusters producing nonribosomal peptides with known structure.
Konanov, Dmitry N; Krivonos, Danil V; Ilina, Elena N; Babenko, Vladislav V.
Afiliação
  • Konanov DN; 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.
  • Krivonos DV; 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.
  • Ilina EN; 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.
  • Babenko VV; 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 ; 20: 1218-1226, 2022.
Article em En | MEDLINE | ID: mdl-35317229
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.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2022 Tipo de documento: Article