Department of Chemistry and Biology, Ryerson University, Toronto, Canada.
J Proteomics. 2010 Apr 18;73(6):1163-75. doi: 10.1016/j.jprot.2010.02.007. Epub 2010 Feb 17.
Sequence analysis of the blood peptides and their qualities will be key to understanding the mechanisms that contribute to error in LC-ESI-MS/MS. Analysis of peptides and their proteins at the level of sequences is much more direct and informative than the comparison of disparate accession numbers. A portable database of all blood peptide and protein sequences with descriptor fields and gene ontology terms might be useful for designing immunological or MRM assays from human blood. The results of twelve studies of human blood peptides and/or proteins identified by LC-MS/MS and correlated against a disparate array of genetic libraries were parsed and matched to proteins from the human ENSEMBL, SwissProt and RefSeq databases by SQL. The reported peptide and protein sequences were organized into an SQL database with full protein sequences and up to five unique peptides in order of prevalence along with the peptide count for each protein. Structured query language or BLAST was used to acquire descriptive information in current databases. Sampling error at the level of peptides is the largest source of disparity between groups. Chi Square analysis of peptide to protein distributions confirmed the significant agreement between groups on identified proteins.
对血液肽及其质量进行序列分析对于理解导致 LC-ESI-MS/MS 错误的机制至关重要。与不同的访问号相比，对肽及其蛋白质进行序列水平的分析更加直接和有信息。具有描述符字段和基因本体论术语的所有血液肽和蛋白质序列的便携式数据库可能有助于从人血中设计免疫学或 MRM 测定。通过 SQL 解析了十二项通过 LC-MS/MS 鉴定的人类血液肽和/或蛋白质的研究结果，并与各种遗传文库进行了关联，并与人类 ENSEMBL、SwissProt 和 RefSeq 数据库中的蛋白质进行了匹配。报告的肽和蛋白质序列被组织到一个 SQL 数据库中，其中包含完整的蛋白质序列和按流行度排列的多达五个独特肽，以及每种蛋白质的肽计数。使用结构化查询语言或 BLAST 从现有数据库中获取描述性信息。肽水平的抽样误差是组间差异的最大来源。肽到蛋白质分布的卡方分析证实了两组在鉴定的蛋白质上具有显著的一致性。
