CIDer-p

CIDer-p models and converts fragmentation spectra between Collision-Induced Dissociation (CID) and Higher-energy C-trap Dissociation (HCD) to improve peptide detection in proteomics.

Key Features:

• Modeling Spectral Differences: CIDer-p employs a statistical framework using simple linear models grounded in peptide fragmentation principles that accounts for up to 43% of the variation observed across collision energy settings.
• Library Conversion: Enables conversion of spectral libraries from HCD to CID, facilitating reuse of HCD-derived libraries for resonance CID fragmentation experiments.
• Enhanced Peptide Detection: Searching converted CID libraries can detect more peptides under certain conditions than searches using existing CID libraries or machine-learning-predicted spectra generated from FASTA databases.

Scientific Applications:

• Proteomics Research: Facilitates interpretation and cross-use of HCD and CID spectral data to support peptide identification and spectral library searches in proteomic experiments.
• Interim Library Strategy: Provides an interim approach to maximize the utility of large-scale HCD-derived spectral libraries while comprehensive CID libraries are developed.

Methodology:

CIDer-p applies simple linear statistical models grounded in peptide fragmentation principles and empirical analysis to model and convert differences between HCD and CID spectra across collision energy settings.