基于生物网络的共享肽归属及蛋白质定性算法研究

项目名称： 基于生物网络的共享肽归属及蛋白质定性算法研究

项目编号： No.61502166

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 计算机科学学科

项目作者： 钟坚成

作者单位： 湖南师范大学

项目金额： 20万元

中文摘要： 蛋白质定性是蛋白质组学中非常重要的步骤。目前，采用鸟枪法蛋白质组学的步骤是先将标识生物样本中的蛋白质酶解为肽段混合物，肽段混合物通过色谱分离和离子化后，经高通量串联质谱仪产生质谱数据用于肽段鉴定，再从鉴定的肽段推导可能存在的蛋白质。但是由于蛋白质在酶解过程中割裂了肽和蛋白质的关系，使存在如下问题：一个肽映射不同蛋白质、蛋白质只被一个肽映射等，这极大地增加了蛋白质定性的复杂性。本项目从系统生物学角度出发，在融合蛋白质相互作用网络信息、基因表达信息、序列信息、功能注释信息、组织特异性信息的基础上，深入分析蛋白质中相关的生物特征，拟设计出蛋白质推断的多权图模型，用于解决蛋白质组学中科研人员关注的几个基本问题，如: 共享肽的归属问题、蛋白质定性问题等。最终，本项目拟将基于多权图模型研发一套蛋白质组学数据分析及可视化软件，为生物学家鉴定蛋白质以及进一步研究提供有价值的参考信息。

中文关键词： 生物信息学；蛋白质推断；蛋白质相互作用网络；基因表达水平；蛋白质组学

英文摘要： Protein inference of shotgun proteomics, i.e. inferring proteins from tandem mass spectrometry (MS/MS) samples, is the crucial step in proteomics analysis. The workflow of shotgun proteomics consists of the following steps: The first step is the preparation of samples. In this step, certain proteolytic enzymes are added to protein samples to be analyzed for digesting proteins into mixture of peptides. The second step is sequencing. The sample is sequenced by a combination of high performance liquid chromatography (LC) and mass spectrometry (MS) to ionize, fragment and scan the resulting mixture of peptides and produce a set of MS/MS spectra. The third step is to use some proteomics computational tools to identify the peptides by searching the protein sequence or de novo assembling, such as Sequest, Mascot, X!tendem, and Peaks etc. The fourth step is to infer and quantify the protein. Since the proteins are digested into mixture of peptides, peptides does not correspond to proteins they came from, which causes the problem of shared peptides and ‘one hit protein’. The problem poses the challenge for protein inference. Our project will integrate multiple information including protein interaction data, gene expression information, sequencing information, gene ontology (GO) annotation to analyze the biological features of proteins and construct the multi-weighted network for inferring the shared peptides and proteins. Base on the multi-weighted network, we will develop a software for analyzing, processing, visualizing proteomics data, which will help the biological scientists with their further research.

英文关键词： bioinformatics;protein inference;Protein-protein interaction;gene expression;proteomics