AUTOMATED MOTIF DETERMINATION IN ANTIGENIC PEPTIDES

抗原肽中的自动基序测定

• 批准号: 7953899
• 负责人: ILAN VIDAVSKY
• 金额: $ 0.01万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-02-01 至 2010-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7953899
• 关键词: Accounting; Algorithms; Alleles; Amino Acids; Autoimmune Diseases; Binding; Cell Line; Cell physiology; Cell surface; Cells; Complex; Computer Retrieval of Information on Scientific Projects Database; Enzymes; Funding; Grant; Immune response; Individual; Institution; Investigation; Length; Major Histocompatibility Complex; Mass Spectrum Analysis; Methods; Molecular Chaperones; Mutate; Peptides; Process; Proteins; Research; Research Personnel; Resources; Sorting - Cell Movement; Source; Structure; T-Lymphocyte; Testing; Time; United States National Institutes of Health; base; biomedical resource; computer program; nano; peptide A; protein aminoacid sequence; 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. Peptides are found on the surface of cells bound to the Major Histocompatibility Complex (MHC). These complexes are interrogated by T-cells to determine an immune response. The repertoire of the peptides sequences is determined by the binding constant of the peptide to the individual MHC (class I or II and the particular allele) and by the cell processing mechanisms (catabolic enzymes, chaperons). Determination of a sequence motif to these peptides has implications in finding peptides and proteins that trigger autoimmune diseases and in developing vaccins. Motif determination involves isolating and sequencing large number of peptides using nano-HPLC and tandem mass spectrometry from a cell line bearing a particular MHC. The long lists of peptides are sorted manually, motif hypothesises are suggested and tested using binding studies of mutated peptides. The motif can be refined by studying crystal structures of the complex, if it is available. This process can be very time and labor consuming. Also, binding studies don''t take into account the influence of other cell selection mechanisms. A new method for finding a sequence motif is suggested. It is based on finding it automatically using the isolated peptides sequences. Using a computer program the SW local alignment (with affine gap) of all peptides is maximized in finding of an average sequence. This average sequence is used in finding the binding core length of the peptide to the complex and to align each peptide sequence with the correct binding pockets of the protein in the complex. Statistical analysis of the amino acid content of each pocket reveals the motif. The influence of alignment parameters such as substitution matrixes and gap penalties is under investigation. Also the utility of a clustering algorithm to eliminate outliers and reveal multiple motifs is studied.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 在与主要组织相容性复合物 (MHC) 结合的细胞表面发现了肽。 T 细胞会询问这些复合物以确定免疫反应。肽序列的全部内容由肽与个体 MHC（I 类或 II 类和特定等位基因）的结合常数以及细胞加工机制（分解代谢酶、伴侣）决定。确定这些肽的序列基序对于寻找引发自身免疫性疾病的肽和蛋白质以及开发疫苗具有重要意义。 基序测定涉及使用纳米 HPLC 和串联质谱法从带有特定 MHC 的细胞系中分离和测序大量肽。手动对一长串肽进行排序，提出基序假设并使用突变肽的结合研究进行测试。如果有的话，可以通过研究复合物的晶体结构来完善该图案。这个过程可能非常耗时和费力。此外，结合研究没有考虑其他细胞选择机制的影响。 提出了一种寻找序列基序的新方法。它基于使用分离的肽序列自动找到它。使用计算机程序，所有肽的 SW 局部比对（具有仿射间隙）在寻找平均序列时得到最大化。该平均序列用于确定肽与复合物的结合核心长度，并将每个肽序列与复合物中蛋白质的正确结合袋进行比对。对每个口袋的氨基酸含量的统计分析揭示了该基序。替换矩阵和空位罚分等比对参数的影响正在研究中。还研究了聚类算法消除异常值和揭示多个主题的实用性。