DeNovoID

DeNovoID identifies peptides and proteins from mass spectrometry (MS)-derived de novo peptide sequencing data by matching degenerate amino acid compositions to sequence databases to enable identification of spectra not matched by Sequest or Mascot in proteomics.

Key Features:

• Handling Incomplete Data: Processes ordered and disordered sequence tags and mass tags from de novo peptide sequencing to utilize incomplete sequence information that is challenging for BLAST or FASTA.
• Degenerate Sequence Utilization: Processes degenerate amino acid sequences and associated mass data by focusing on amino acid composition rather than enumerating all peptide sequence permutations.
• Efficient Search Algorithm: Reduces computational complexity by considering only amino acid compositions consistent with the observed spectrum, narrowing candidate peptide matches in the database.
• Geometric Indexing Scheme: Incorporates a geometric indexing scheme to minimize the number of calculations required to identify the optimal peptide match, facilitating faster and more accurate identification.

Scientific Applications:

• Proteomics identification from challenging spectra: Enables identification of peptides and proteins from spectra that fail conventional spectral matching programs such as Sequest or Mascot in high-throughput proteomics.
• Novel peptide discovery: Facilitates discovery of novel peptide sequences from incomplete de novo sequencing data by leveraging composition-based matching approaches.

Methodology:

Accepts de novo peptide sequencing data from mass spectrometry (MS), processes ordered/disordered sequence tags and mass tags, analyzes degenerate amino acid sequences and mass data using amino acid composition-based matching, employs an algorithm that considers only compositions consistent with the spectrum, and uses a geometric indexing scheme to minimize calculations when locating optimal database matches.