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Master
English

Study of Cyclic Non-Ribosomal Peptides Fragmentation Patterns Obtained Through Tandem Mass Spectrometry (MS/MS)

Contributors

Stricker, Thomas

Directors

Muller, Markus Johann; Lisacek, Frédérique

Master program title

Master in Biology, Orientation Bioinformatics and Data Analysis in Biology (BIADB)

Defense date

2015

Abstract

Nonribosomal peptides (NRP) are secondary metabolites produced by large multi-enzymatic complexes known as Nonribosomal Peptides Synthetases (NRPS). These short oligomers are synthetised in a variety of microorganisms such as bacteria and fungi. They are known for having a vast spectrum of biological activities and pharmaceutical applications, including antibiotic, antitumor and immunosuppressant activities. Mass Spectrometry (MS) is the method of choice for the study of these biomolecules. However the analysis of NRPs is a complex and laborious task due to their unusual structure and composition. Therefore we developed a java application, called NoriCype, with the aim of laying the foundations for a larger bioinformatics platform dedicated to the discovery of new antimicrobial drugs and biosurfactants. It consists of a set of three tools (fragmentation, matching, scoring) designed for the identification of cyclic nonribosomal peptides in tandem mass spectra and two unique visualization methods. These methods allow to quickly identify the peptide bonds that are more likely to be cleaved during the dissociation process of a tandem mass spectrometry (MS/MS) experiment .

Keywords

  • Bioinformatics
  • Mass Spectrometry
  • Nonribosomal Peptide
  • Software

UNIGE affiliation entities

Citation (ISO format)

STRICKER, Thomas. Study of Cyclic Non-Ribosomal Peptides Fragmentation Patterns Obtained Through Tandem Mass Spectrometry (MS/MS). Master, 2015.

Main files (1)

Master thesis

Identifiers

  • PID : unige:76264
246views
5downloads

Technical informations

Creation

19/10/2015 11:00:00

First validation

19/10/2015 11:00:00

Update

14/03/2023 23:43:19

Status update

14/03/2023 23:43:19

Last indexation

31/10/2024 01:35:52
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