ISPTM: an iterative search algorithm for systematic identification of post-translational modifications from complex proteome mixtures

ISPTM:一种用于从复杂蛋白质组混合物中系统地识别翻译后修饰的迭代搜索算法

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作者:Xin Huang, Lin Huang, Hong Peng, Ashu Guru, Weihua Xue, Sang Yong Hong, Miao Liu, Seema Sharma, Kai Fu, Adam P Caprez, David R Swanson, Zhixin Zhang, Shi-Jian Ding

Abstract

Identifying protein post-translational modifications (PTMs) from tandem mass spectrometry data of complex proteome mixtures is a highly challenging task. Here we present a new strategy, named iterative search for identifying PTMs (ISPTM), for tackling this challenge. The ISPTM approach consists of a basic search with no variable modification, followed by iterative searches of many PTMs using a small number of them (usually two) in each search. The performance of the ISPTM approach was evaluated on mixtures of 70 synthetic peptides with known modifications, on an 18-protein standard mixture with unknown modifications and on real, complex biological samples of mouse nuclear matrix proteins with unknown modifications. ISPTM revealed that many chemical PTMs were introduced by urea and iodoacetamide during sample preparation and many biological PTMs, including dimethylation of arginine and lysine, were significantly activated by Adriamycin treatment in nuclear matrix associated proteins. ISPTM increased the MS/MS spectral identification rate substantially, displayed significantly better sensitivity for systematic PTM identification compared with that of the conventional all-in-one search approach, and offered PTM identification results that were complementary to InsPecT and MODa, both of which are established PTM identification algorithms. In summary, ISPTM is a new and powerful tool for unbiased identification of many different PTMs with high confidence from complex proteome mixtures.

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