New Methods for Phosphopeptide Identification

磷酸肽鉴定的新方法

基本信息

批准号：
7486739
负责人：
KATHERYN A RESING
金额：
$ 15.15万
依托单位：
UNIVERSITY OF COLORADO
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-09-01 至 2010-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7486739
关键词：
Adverse drug effect Affect Affinity Algorithms Behavior Cancer Etiology Cations Cells Charge Chemistry Chimera organism Class Collection Complex Complex Mixtures Computing Methodologies Core Facility Coupled Data Data Set Databases Detection Diagnosis Discrimination Disease Dissociation Electron Transport Event Gases Goals High Pressure Liquid Chromatography Ions Lead Libraries Malignant Neoplasms Maps Mass Spectrum Analysis Metals Methodology Methods Modification Monitor Parents Pathway interactions Peptides Performance Phase Phosphopeptides Phosphoproteins Phosphorylation Principal Investigator Property Protein Databases Proteins Proteolysis Proteomics Protocols documentation Range Reading Recovery Relative (related person)Reliance Resolution Sampling Score Scoring Method Sensitivity and Specificity Signal Pathway Site Surveys Technology Testing anticancer research base cancer therapy chemical property data acquisition design human disease improved inorganic phosphate instrument interest ionization mass spectrometer programs protein aminoacid sequence response size

项目摘要

New mass spectrometers capable of data dependent data acquisition and new database search algorithms have enabled proteomics profiling of complex samples by multidimensional LC/MSMS, where proteins are proteolyzed, separated chromatographically, and identified in a high throughput manner by peptide MSMS sequencing. An important goal is to identify phosphoproteins in complex mixtures and map their sites of modification by profiling phosphopeptides. Protein phosphorylation events are prevalent in cell regulatory and signaling pathways, and aberrations that lead to changes in phosphorylation are underlying causes of cancer and many other human diseases. Thus, the ability to profile phosphopeptides and monitor their changes in abundance is of key importance for cancer treatment and diagnosis. However, technical methods to achieve phosphoproteomics profiling have proven very difficult, due to the chemical properties of the phosphate, the large database size when searching a protein database allowing variable phosphorylation on Ser, Thr, and Tyr, and the resulting low sensitivity and specificity of current scoring methods. In order to match MSMS spectra to phosphopeptide sequences with greater accuracy, it is critical to develop a greater understanding about the MS behavior of phosphopeptides and chemistry of gas phase fragmentation, and evaluate the factors that interfere with their detection and identification. Therefore, studies in this proposal will improve the ability to identify phosphopeptides from high resolution MSMS spectra. In Sp. Aim 1, we will rigorously compare the

能够通过多维LC/MSMS对复杂样品进行蛋白质组学分析的新的质谱仪和新的数据库搜索算法启用了蛋白质组学分析，其中蛋白质是蛋白质水解，色谱分离的，并通过肽MSMS测序以高吞吐量的方式鉴定出高吞吐量。一个重要的目标是鉴定复杂混合物中的磷蛋白并绘制其位置通过分析磷酸肽的修饰。蛋白质磷酸化事件在细胞调节和信号传导途径中普遍存在，导致磷酸化变化的畸变是癌症的根本原因以及许多其他人类疾病。因此，对磷酸肽和监测丰度变化的能力对于癌症治疗和诊断至关重要。然而，由于磷酸盐的化学特性，搜索蛋白质数据库时允许在SER，THR和TYR上允许可变的磷酸化以及导致的当前训练方法的低敏感性和特异性时，实现磷酸蛋白质组学分析的技术方法已被证明非常困难。为了将MSMS光谱与磷酸肽序列具有更高的精度，至关重要的是，对磷酸肽和气相碎片化学的MS行为有更深入的了解，并评估因素干扰他们的检测和识别。因此，该提案中的研究将提高从高分辨率MSMS光谱中鉴定磷酸肽的能力。在sp。目标1，我们将严格比较