Automatic Annotation and Dereplication of Tandem Mass Spectra of Peptidic Natural Products.
Emma RicartMaude PupinMarkus MüllerFrederique LisacekPublished in: Analytical chemistry (2020)
The various bioactivity types and potencies of peptidic natural products (PNPs) are of high interest for the development of new drugs. In particular, the intrinsic antibiotic properties of PNPs appear essential to combat antimicrobial resistance that is currently threatening the world. The first steps in dereplication and characterization of PNPs often involve tandem mass spectrometry (MS/MS). However, such structurally complex peptides challenge the interpretation of MS/MS results. Only a few software solutions are dedicated to PNP analysis but with a mutually exclusive focus on dereplication or annotation. Hence, key functionalities such as automatic peak annotation or statistically validated scoring systems to support the characterization/identification processes are missing. Here, we present NRPro, a new MS/MS analysis platform that overcomes some limitations of the existing software and provides a comprehensive toolset for both automatic annotation and dereplication of PNPs.
Keyphrases
- ms ms
- tandem mass spectrometry
- antimicrobial resistance
- ultra high performance liquid chromatography
- high performance liquid chromatography
- deep learning
- machine learning
- rna seq
- liquid chromatography tandem mass spectrometry
- simultaneous determination
- liquid chromatography
- gas chromatography
- solid phase extraction
- neural network
- high throughput