A Multi-stage Spectral Alignment Strategy for Unrestrictive PTM Peptide Identification

Spectral alignment, which studies the matching of ion peaks between the investigated spectrum and theoretical spectrum of peptide in the peptide database, is a very useful topic in computational proteomics. So far, the efficient, accurate and practical spectral alignment algorithm is still urgently needed due to its important application in the PTM unrestrictive peptide identification. In this paper, a multi-stage spectral alignment algorithm called MS-SA is proposed with the following two features: (a) it provided four different levels of alignment aims according to the alignment quality which can be specified by users, (b) it provided the capability of analyzing the detail modification types and locations for spectrum with multiple PTM sites. Therefore, MS-SA is of high practicality and can be applied to different specific applications such as being a filter in the large-scale database searching, a tool for detail modification types and locations analysis in small-scale spectral alignment and so on. A large number of experiments on real MS/MS data have been done for testing the performance of MS-SA. Also, the results of MS-SA are compared with those of same type of algorithms such as SA and SPC. The results show that MS-SA possesses strong practicality and outperforms the SA and SPC algorithms on several aspects.