New Methods for Phosphopeptide Identification

磷酸肽鉴定的新方法

• 批准号: 7289671
• 负责人: KATHERYN A RESING
• 金额: $ 18.18万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7289671
• 关键词: Adverse drug effect; Affect; Affinity; Algorithms; Behavior; Biological; Biological Markers; Biomedical Research; Cancer Etiology; Cations; Cells; Charge; Chemistry; Chimera organism; Class; Collection; Communities; Complex; Complex Mixtures; Computing Methodologies; Condition; Core Facility; Coupled; Data; Data Set; Databases; Detection; Diagnosis; Diagnostic Procedure; Discrimination; Disease; Dissociation; Electron Transport; Event; Future; Gases; Goals; High Pressure Liquid Chromatography; Ions; Kinetics; Lead; Libraries; Malignant Neoplasms; Malignant neoplasm of prostate; Maps; Mass Spectrum Analysis; Metals; Methodology; Methods; Modeling; Modification; Monitor; Parents; Pathway interactions; Peptides; Performance; Phase; Phosphopeptides; Phosphoproteins; Phosphorylation; Prevalence; Property; Protein Databases; Proteins; Proteolysis; Proteomics; Protocols documentation; Range; Reading; Recovery; Relative (related person); Reliance; Research Personnel; Resolution; Sampling; Scientist; Score; Scoring Method; Sensitivity and Specificity; Signal Pathway; Signal Transduction; Signal Transduction 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; melanoma; novel therapeutics; performance tests; protein aminoacid sequence; research study; response; size

DESCRIPTION (provided by applicant): 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 performance of the most promising MS protocols currently available for phosphoproteomics. In Sp. Aim 2, we will improve computational technologies for automated searching of phosphopeptides by positive ion MSMS, by incorporating information about their unique chemistry into scoring algorithms. In Sp. Aim 3 we will test the performance of negative ion MSMS for phosphopeptides, which is very promising but relatively unexplored, and compare it against the most promising positive ion methods, asking whether preferential ionization of phosphopeptides by negative ion MSMS alleviates the need for enrichment. Our optimized methods will be applied in future studies to identify signal transduction targets and biomarkers in melanoma and prostate cancer, and will be widely useful to basic researchers and clinician scientists in the cancer research community. Dysregulation of protein phosphorylation in response to signal transduction pathways is commonly observed in diseases such as cancer and as a side effect of drug treatment. Therefore, methods that screen for changes in protein phosphorylation under disease conditions would reveal targets that can be used to design new therapeutic or diagnostic methods. Our proposal will rigorously compare MS protocols for phosphoproteomics and develop improved experimental and computational approaches to improve the sensitivity and specificity of this experiment. These methods will be applied in future studies to identify signal transduction targets and biomarkers in melanoma and prostate cancer, and will be widely useful and freely available to basic researchers and clinician scientists in the cancer and biomedical research community.

描述（由申请人提供）：能够通过多维LC/MSMS对复杂样品进行蛋白质组学分析的新型质谱仪和新的数据库搜索算法具有蛋白质组学对蛋白质分析，其中蛋白质是蛋白质水解，分离的，具有色谱，并通过肽MSMS序列鉴定在高通过透过的方式中。一个重要的目标是鉴定复杂混合物中的磷酸蛋白，并通过分析磷酸肽来绘制其修饰部位。蛋白质磷酸化事件在细胞调节和信号通路中很普遍，导致磷酸化变化的畸变是癌症和许多其他人类疾病的根本原因。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电流扫描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。为了使MSMS光谱与磷酸肽序列具有更高的准确性相匹配，至关重要的是，对磷酸肽的MS行为和气相碎片的化学性质有更深入的了解，并评估干扰其检测和鉴定的因素。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。 AIM 1，我们将严格比较当前可用于磷蛋白质组学的最有希望的MS协议的性能。在sp。 AIM 2，我们将通过将有关其独特化学的信息纳入评分算法来改善通过正离子MSM自动搜索磷酸肽的计算技术。在sp。 AIM 3我们将测试磷酸肽负离子MSMS的性能，这是非常有前途但没有探索的，并将其与最有希望的阳性离子方法进行比较，询问负离子MSMS对磷酸化的优先电离是否减轻了富集的需求。我们的优化方法将在未来的研究中应用，以确定黑色素瘤和前列腺癌中的信号转导靶标和生物标志物，并将对癌症研究界的基础研究人员和临床医生广泛用来。在癌症等疾病和药物治疗的副作用中，通常观察到蛋白质磷酸化反应蛋白质磷酸化的失调。因此，在疾病条件下筛选蛋白质磷酸化变化的方法将揭示可用于设计新的治疗或诊断方法的靶标。我们的建议将严格比较磷蛋白质组学的MS方案，并开发改进的实验和计算方法，以提高该实验的敏感性和特异性。这些方法将在以后的研究中应用，以确定黑色素瘤和前列腺癌中的信号转导靶标和生物标志物，并将广泛有用，并为癌症和生物医学研究界的基础研究人员和临床医生免费提供。