Software for Automated Identification of GAG Structures From MS/MS Spectra Using A Genetic Algorithm

摘要

A genetic algorithm based software has been developed for the automated structural identification of GAGs from MS/MS data. Current fitness tests examine the presence of glycosidic and cross-ring bond cleavage fragments in the MS/MS spectra as well as their corresponding intensities. Additional efforts are being made to examine the correlation between fragment peak abundances and structure. Finding diagnostic peaks or peak intensity ratios can significantly influence fitting parameters and eliminate the identification of false positives. We are current looking at non-bikunin GAG species with greater degrees of complexity. The binary representation for an individual residue is significantly more complex, but are generally shorter in length. Hence, a multi-bit set of binary values is used to express the existence of sulfates a specific positions.