A model of random sequences for de novo peptide sequencing

• Published in: Third IEEE Symposium on Bioinformatics and Bioengineering, 2003. Proceedings pp. 206 - 213
• Main Authors: Jarman, K.D., Cannon, W.R., Jarman, K.H., Heredia-Langner, A.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2003
• Subjects: Bioinformatics; DNA; Genetic mutations; Genomics; Laboratories; Mass spectroscopy; Organisms; Peptides; Random sequences
• ISBN: 0769519075; 9780769519074
• DOI: 10.1109/BIBE.2003.1188948

We present a model for the probability of random sequences appearing in product ion spectra obtained from tandem mass spectrometry experiments using collision-induced dissociation. We demonstrate the use of these probabilities for ranking candidate peptide sequences obtained using a de novo algorithm. Sequence candidates are obtained from a spectrum graph that is greatly reduced in size from those in previous graph-theoretical de novo approaches. Evidence of multiple instances of subsequences of each candidate, due to different fragment ion type series as well as isotopic peaks, is incorporated in a hierarchical scoring scheme. This approach is shown to be useful for confirming results from database search and as a first step towards a statistically rigorous de novo algorithm.