This article is part of the supplement: Second Annual MidSouth Computational Biology and Bioinformatics Society Conference. Bioinformatics: a systems approach .

Proceedings

CLPM: A Cross-Linked Peptide Mapping Algorithm for Mass Spectrometric Analysis

Yong Tang^1,2 , Yingfeng Chen³ , Cheryl F Lichti³ , Roger A Hall² , Kevin D Raney³ and Steven F Jennings^1,2

¹  Department of Applied Science, University of Arkansas at Little Rock, Little Rock, Arkansas 72204

²  MidSouth Bioinformatics Center, University of Arkansas at Little Rock, Little Rock, Arkansas 72204

³  Department of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205

author email corresponding author email

BMC Bioinformatics 2005, 6(Suppl 2):S9doi:10.1186/1471-2105-6-S2-S9

Published:	15 July 2005

Abstract

Background

Protein-protein, protein-DNA and protein-RNA interactions are of central importance in biological systems. Quadrapole Time-of-flight (Q-TOF) mass spectrometry is a sensitive, promising tool for studying these interactions. Combining this technique with chemical crosslinking, it is possible to identify the sites of interactions within these complexes. Due to the complexities of the mass spectrometric data of crosslinked proteins, new software is required to analyze the resulting products of these studies.

Result

We designed a Cross-Linked Peptide Mapping (CLPM) algorithm which takes advantage of all of the information available in the experiment including the amino acid sequence from each protein, the identity of the crosslinker, the identity of the digesting enzyme, the level of missed cleavage, and possible chemical modifications. The algorithm does in silico digestion and crosslinking, calculates all possible mass values and matches the theoretical data to the actual experimental data provided by the mass spectrometry analysis to identify the crosslinked peptides.

Conclusion

Identifying peptides by their masses can be an efficient starting point for direct sequence confirmation. The CLPM algorithm provides a powerful tool in identifying these potential interaction sites in combination with chemical crosslinking and mass spectrometry. Through this cost-effective approach, subsequent efforts can quickly focus attention on investigating these specific interaction sites.