CAREER: A Complete System for Protein Identification with Computational Approaches

蛋白质鉴定是蛋白质组学的一个重要研究方向，在信号转导和疾病治疗方面具有重要意义。已经开发了几种用于蛋白质鉴定的技术。其中，串联质谱（MS/MS）是目前最常用的蛋白质鉴定技术。通过串联质谱法识别蛋白质的过程类似于使用他/她的指纹识别一个人。由于MS/MS谱通常是不完整的，并且包含由于污染物、差的肽段分割以及其他技术或生物学原因而导致的噪声峰，因此它对蛋白质鉴定是一个具有挑战性的问题。当光谱包含翻译后修饰（PTM）时，问题变得更加困难。PTM的存在大大增加了从头测序和数据库检索的难度，本研究通过理论研究和计算方法解决了这一具有挑战性的蛋白质鉴定问题。本工作建立了一个完整的系统，重点是通过确定蛋白质的氨基酸序列，从他们的MS/MS光谱鉴定蛋白质。具体而言，对于给定的实验串联质谱，系统通过一系列活动来识别其氨基酸序列和PTM：（a）分离不同的离子类型和噪声，（B）生成序列标签，c）识别候选肽序列，以及（d）验证候选肽序列并识别PTM。

Protein identification is a major research perspective in proteomics holding the promise of signaling and treating diseases. Several techniques have been developed for protein identification. Among which, tandem mass spectrometry (MS/MS) is currently the most popular technique used to identify proteins. The process of identifying proteins by tandem mass spectrometry is analogous to identifying a person using his/her fingerprints. Since a MS/MS spectrum usually is incomplete and contains noise peaks due to contaminants, poor peptide segmentation, and other technical or biological reasons, it is a challenging problem to protein identification. The problem becomes more difficult when the spectrum contains post-translational modifications (PTMs). The presence of PTMs significantly increases the difficulty of both de novo sequencing and database search.This research addresses this challenging problem of protein identification with theoretical studies and computational approaches. This work builds a complete system focusing on identifying proteins by determining the amino acid sequences of the proteins from their MS/MS spectra. In particular, for a given experimental tandem mass spectrum, the system identifies its amino acid sequence and PTMs through a series of activities: (a) separating different ion types and noises, (b) generating sequence tags, c) identifying candidate peptide sequences, and (d) verifying the candidate peptide sequences and identifying PTMs.