GENOME DATABASE SEARCHING SOFTWARE FOR ID PROTEINS USING MASS SPECTROMETRY DATA

使用质谱数据搜索 ID 蛋白质的基因组数据库软件

• 批准号: 7957361
• 负责人: ALMA L BURLINGAME
• 金额: $ 10.68万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-06-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7957361
• 关键词: Amino Acid Sequence; Amino Acids; Automation; Biological Process; Cells; Computer Retrieval of Information on Scientific Projects Database; Computer software; DNA Sequence; Data; Databases; Dissociation; Enzymes; Fingerprint; Funding; Genome; Genomics; Grant; Individual; Institution; Ions; Life; Manuals; Mass Spectrum Analysis; Measurement; Measures; Molecular Machines; Organism; Peptide Sequence Determination; Peptides; Protein Array; Proteins; Reporting; Research; Research Personnel; Resources; Sampling; Side; Source; Techniques; Time; United States National Institutes of Health; gene cloning; genome database; helix-loop-helix protein differentiation inhibitor; instrument; mass spectrometer; molecular mass; protein aminoacid sequence; repository; research and development; research study; software development; tandem mass spectrometry

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The Genome Projects worldwide are rapidly pouring a wealth of DNA sequence data into databases at the National Institutes of Health (NIH) and many other repositories. Within this vast quantity of data lie the largely not-yet-understood blueprints which the individual cells in an organism use to build the array of proteins that serve as the molecular machines for executing the wide variety of biological processes necessary to sustain life. These is ever-growing genomic databases serve as a fundamental resource in accelerating research using mass spectrometry for identification of proteins. Mass spectrometry (MS) techniques produce two types of information from a single sample in a matter of minutes. The first are peptide mass values. A so-called peptide-mass fingerprint is obtained after using an enzyme to digest a target protein into a mixture of smaller pieces called peptides. The molecular masses of each peptide in the mixture are measured with a mass spectrometer. The resulting set of masses constitutes a fingerprint. The second is peptide sequence. In a tandem MS experiment individual peptide components in either an unseparated or separated mixture can be selectively dissociated to yield a spectrum of product ions(collision induced dissociation spectrum). Subsequent measurement of the mass values of all of these product ions provides the mass differences between adjacent product ions that can be assigned to amino acid side chain and thus peptide sequence. Because of the complexity of the data produced from these types of experiments and the tremendous sample throughput potential from automation of MS instruments we are continuing to develop software for automatic peptide sequence assignment from these CID spectra. In those situations when the particular protein sequence is not in these databases, de novo sequence can be deduced by manual interpretation of these CID spectra that can be used to initiate gene-cloning efforts. Alternatively, strategies to detect remote homologies from existing database entries can be employed. These are being developed as well. (Additional effort and instrument time reported under Collaborative projects and other Technical Research and Development projects.)

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 世界各地的基因组计划正在迅速将丰富的DNA序列数据注入美国国立卫生研究院(NIH)和许多其他储存库的数据库中。在这海量的数据中，隐藏着在很大程度上还不为人所知的蓝图，生物体中的单个细胞用来构建蛋白质阵列，这些蛋白质充当分子机器，执行维持生命所必需的各种生物过程。这些不断增长的基因组数据库是加速利用质谱学鉴定蛋白质的研究的基本资源。质谱学(MS)技术在几分钟内从一个样品中产生两种类型的信息。第一个是多肽质量值。在使用一种酶将目标蛋白质消化成一种称为多肽的较小片段的混合物后，就会获得所谓的多肽-质量指纹。用质谱仪测量混合物中每种多肽的分子质量。由此产生的一组肿块构成了指纹。二是多肽序列。在串联MS实验中，未分离或分离的混合物中的单个多肽成分可以被选择性地解离，以产生产物离子的光谱(碰撞诱导解离光谱)。随后对所有这些产物离子的质量值的测量提供了相邻产物离子之间的质量差，这些质量差可以被分配到氨基酸侧链，从而可以分配到肽序列。由于这些类型的实验产生的数据的复杂性，以及来自MS仪器自动化的巨大样品吞吐潜力，我们正在继续开发用于根据这些CID谱自动分配多肽序列的软件。 在特定蛋白质序列不在这些数据库中的情况下，可以通过手动解释这些可用于启动基因克隆努力的CID谱来推断从头开始的序列。或者，可以采用从现有数据库条目中检测远程同源性的策略。这些也在开发中。 (在协作项目和其他技术研究和开发项目下报告的额外工作量和仪器时间。)