title: pTop 1.0: A High-Accuracy and High-Efficiency Search Engine for Intact Protein Identification.
abstract: There has been tremendous progress in top-down proteomics (TDP) in the past 5 years, particularly in intact protein separation and high-resolution mass spectrometry. However, bioinformatics to deal with large-scale mass spectra has lagged behind, in both algorithmic research and software development. In this study, we developed pTop 1.0, a novel software tool to significantly improve the accuracy and efficiency of mass spectral data analysis in TDP. The precursor mass offers crucial clues to infer the potential post-translational modifications co-occurring on the protein, the reliability of which relies heavily on its mass accuracy. Concentrating on detecting the precursors more accurately, a machine-learning model incorporating a variety of spectral features was trained online in pTop via a support vector machine (SVM). pTop employs the sequence tags extracted from the MS/MS spectra and a dynamic programming algorithm to accelerate the search speed, especially for those spectra with multiple post-translational modifications. We tested pTop on three publicly available data sets and compared it with ProSight and MS-Align+ in terms of its recall, precision, running time, and so on. The results showed that pTop can, in general, outperform ProSight and MS-Align+. pTop recalled 22% more correct precursors, although it exported 30% fewer precursors than Xtract (in ProSight) from a human histone data set. The running speed of pTop was about 1 to 2 orders of magnitude faster than that of MS-Align+. This algorithmic advancement in pTop, including both accuracy and speed, will inspire the development of other similar software to analyze the mass spectra from the entire proteins.
authors: Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS , Beijing 100190, China.
authors: Rui-Xiang
authors: RX
authors: Sun
authors: Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS , Beijing 100190, China.|University of Chinese Academy of Sciences , Beijing 100049, China.
authors: Lan
authors: L
authors: Luo
authors: Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS , Beijing 100190, China.|University of Chinese Academy of Sciences , Beijing 100049, China.
authors: Long
authors: L
authors: Wu
authors: Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS , Beijing 100190, China.|University of Chinese Academy of Sciences , Beijing 100049, China.
authors: Rui-Min
authors: RM
authors: Wang
authors: Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS , Beijing 100190, China.|University of Chinese Academy of Sciences , Beijing 100049, China.
authors: Wen-Feng
authors: WF
authors: Zeng
authors: Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS , Beijing 100190, China.
authors: Hao
authors: H
authors: Chi
authors: Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS , Beijing 100190, China.
authors: Chao
authors: C
authors: Liu
authors: Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS , Beijing 100190, China.
authors: Si-Min
authors: SM
authors: He
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D016247:Information Storage and Retrieval; D000069550:Machine Learning; D011506:Proteins / Q000032:analysis*; D012984:Software
chemical_list: D011506:Proteins