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利用肽微阵列和宏阵列测定蛋白激酶的底物特异性

Determination of the Substrate Specificity of Protein Kinases with Peptide Micro- and Macroarrays.

作者信息

Lai Shenshen, Winkler Dirk F H, Zhang Hong, Pelech Steven

机构信息

Kinexus Bioinformatics Corporation, Suite 1, 8755 Ash Street, Vancouver, British Columbia, Canada, V6P 6T3.

Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.

出版信息

Methods Mol Biol. 2016;1360:183-202. doi: 10.1007/978-1-4939-3073-9_14.

Abstract

Elucidation of the key determinants for the phosphorylation site specificities of protein kinases facilitates identification of their physiological substrates, and serves to better define their critical roles in the signaling networks that underlie a multitude of cellular activities. Albeit with some apparent limitations, such as the lack of contextual information for secondary substrate-binding sites, the synthetic peptide-based approach has been adopted widely for the kinase specificity profiling studies, especially when they are used in an array format, which permits the screening of large numbers of potential peptide substrates in parallel. In this chapter, we present detailed protocols for determining protein kinase substrate specificity using an approach that involves both peptide microarrays and macroarrays. In particular, SPOT synthesis on macroarrays can be used to follow up on in silico predictions of protein kinase substrate specificity with predictive algorithms.

摘要

阐明蛋白激酶磷酸化位点特异性的关键决定因素有助于识别其生理底物,并有助于更好地界定它们在众多细胞活动所依赖的信号网络中的关键作用。尽管存在一些明显的局限性,例如缺乏关于二级底物结合位点的背景信息,但基于合成肽的方法已被广泛用于激酶特异性分析研究,尤其是当它们以阵列形式使用时,这种形式允许并行筛选大量潜在的肽底物。在本章中,我们介绍了使用涉及肽微阵列和宏阵列的方法来确定蛋白激酶底物特异性的详细方案。特别是,宏阵列上的SPOT合成可用于通过预测算法对蛋白激酶底物特异性的计算机预测进行后续研究。

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