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Related Concept Videos

Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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Quantifying the Antifungal Activity of Peptides Against Candida albicans
06:45

Quantifying the Antifungal Activity of Peptides Against Candida albicans

Published on: January 13, 2023

A Candida albicans PeptideAtlas.

Vital Vialas1, Zhi Sun2, Carla Verónica Loureiro y Penha1

  • 1Dept. Microbiología II, Universidad Complutense de Madrid, Madrid, Spain; IRYCIS: Instituto Ramón y Cajal de Investigación Sanitaria, Madrid, Spain.

Journal of Proteomics
|July 2, 2013
PubMed
Summary

This study introduces the Candida albicans PeptideAtlas, a comprehensive proteomic resource. It significantly enhances the study of fungal virulence factors and aids in selecting peptides for targeted proteomic experiments.

Keywords:
CGDCandida Genome DatabaseCandida albicansESSEmpirical Suitability ScoreFDRFalse Discovery RatePRIDEPSMPSSPeptideAtlasPeptide–Spectrum MatchPredicted Suitability ScoreProtein Identifications DatabaseProteotypic peptidesSRMSelected Reaction Monitoring

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Area of Science:

  • Proteomics
  • Mycology
  • Bioinformatics

Background:

  • Public proteomic datasets for Candida albicans are limited.
  • A comprehensive proteomic resource for this fungal pathogen was needed.

Purpose of the Study:

  • To create a Candida albicans PeptideAtlas.
  • To provide a searchable database of peptides and proteins.
  • To support research on fungal virulence and pathogenesis.

Main Methods:

  • Integrated data from 16 experiments.
  • Identified ~22,000 distinct peptides at 0.24% False Discovery Rate (FDR).
  • Characterized over 2500 canonical proteins at 1.2% FDR.

Main Results:

  • Achieved 41% coverage of Candida albicans open reading frame sequences.
  • Established a searchable platform with visualization tools.
  • Identified proteins linked to virulence mechanisms like dimorphism, adherence, and apoptosis.

Conclusions:

  • This resource fills a gap for fungal pathogens in the PeptideAtlas project.
  • It is the most extensive proteomic characterization of Candida albicans to date.
  • Facilitates research on virulence and selection of peptides for targeted proteomics (SRM, SWATH-MS).