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使用 Antibodypedia 进行针对人类蛋白质组的抗体的染色体中心分析。

A chromosome-centric analysis of antibodies directed toward the human proteome using Antibodypedia.

机构信息

Science for Life Laboratory, KTH-Royal Institute of Technology , SE-171 21 Stockholm, Sweden.

出版信息

J Proteome Res. 2014 Mar 7;13(3):1669-76. doi: 10.1021/pr4011525. Epub 2014 Feb 17.

Abstract

Antibodies are crucial for the study of human proteins and have been defined as one of the three pillars in the human chromosome-centric Human Proteome Project (C-HPP). In this article the chromosome-centric structure has been used to analyze the availability of antibodies as judged by the presence within the portal Antibodypedia, a database designed to allow comparisons and scoring of publicly available antibodies toward human protein targets. This public database displays antibody data from more than one million antibodies toward human protein targets. A summary of the content in this knowledge resource reveals that there exist more than 10 antibodies to over 70% of all the putative human genes, evenly distributed over the 24 human chromosomes. The analysis also shows that at present, less than 10% of the putative human protein-coding genes (n = 1882) predicted from the genome sequence lack antibodies, suggesting that focused efforts from the antibody-based and mass spectrometry-based proteomic communities should be encouraged to pursue the analysis of these missing proteins. We show that Antibodypedia may be used to track the development of available and validated antibodies to the individual chromosomes, and thus the database is an attractive tool to identify proteins with no or few antibodies yet generated.

摘要

抗体对于人类蛋白质的研究至关重要,被定义为人类染色体中心人类蛋白质组计划 (C-HPP) 的三个支柱之一。在本文中,使用染色体中心结构来分析抗体的可用性,这是通过抗体门户 Antibodypedia 的存在来判断的,该数据库旨在允许对针对人类蛋白质靶标的可公开获得的抗体进行比较和评分。该公共数据库显示了针对超过 100 万个人类蛋白质靶标抗体的数据。该知识库内容的摘要揭示了存在针对超过 70%的所有推定人类基因的超过 10 种抗体,均匀分布在 24 个人类染色体上。分析还表明,目前,预测的基因组序列中不到 10%的假定人类蛋白质编码基因(n = 1882)缺乏抗体,这表明应鼓励基于抗体和基于质谱的蛋白质组学社区进行有针对性的努力,以研究这些缺失的蛋白质。我们表明,Antibodypedia 可用于跟踪针对各个染色体的可用和经过验证的抗体的发展,因此该数据库是一种很有吸引力的工具,可用于识别尚未产生抗体或产生抗体很少的蛋白质。

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