NPOmix: A machine learning classifier to connect mass spectrometry fragmentation data to biosynthetic gene clusters.

ABSTRACT: Microbial specialized metabolites are an important source of and inspiration for many pharmaceuticals, biotechnological products and play key roles in ecological processes. Untargeted metabolomics using liquid chromatography coupled with tandem mass spectrometry is an efficient technique to access metabolites from fractions and even environmental crude extracts. Nevertheless, metabolomics is limited in predicting structures or bioactivities for cryptic metabolites. Efficiently linking the biosynthetic potential inferred from (meta)genomics to the specialized metabolome would accelerate drug discovery programs by allowing metabolomics to make use of genetic predictions. Here, we present a k-nearest neighbor classifier to systematically connect mass spectrometry fragmentation spectra

SUBMITTER: Leao TF 

PROVIDER: S-EPMC9802219 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature