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一种基于光亲和标记的化学蛋白质组学策略,用于小分子候选药物的无偏靶标反卷积

A Photoaffinity Labeling-Based Chemoproteomics Strategy for Unbiased Target Deconvolution of Small Molecule Drug Candidates.

作者信息

Thomas Jason R, Brittain Scott M, Lipps Jennifer, Llamas Luis, Jain Rishi K, Schirle Markus

机构信息

Novartis Institutes for Biomedical Research, 181 Massachusetts Avenue, Cambridge, MA, 02139, USA.

出版信息

Methods Mol Biol. 2017;1647:1-18. doi: 10.1007/978-1-4939-7201-2_1.

Abstract

The combination of photoaffinity labeling (PAL) and quantitative chemoproteomics enables the comprehensive, unbiased determination of protein interaction profiles to support target identification of bioactive small molecules. This approach is amenable to cells in culture and compatible with pharmacologically relevant transmembrane target classes like G-protein coupled receptors and ions channels which have been notoriously hard to access by conventional chemoproteomics approaches. Here, we describe a strategy that combines PAL probe titration and competition with excess parental compounds with the goal of enabling the identification of specific interactors as well as assessing the functional relevance of a binding event for the phenotype under investigation.

摘要

光亲和标记(PAL)与定量化学蛋白质组学相结合,能够全面、无偏地确定蛋白质相互作用图谱,以支持生物活性小分子的靶点鉴定。这种方法适用于培养中的细胞,并且与药理相关的跨膜靶点类别兼容,如G蛋白偶联受体和离子通道,而传统化学蛋白质组学方法一直难以研究这些靶点。在这里,我们描述了一种策略,该策略将PAL探针滴定与与过量母体化合物的竞争相结合,目的是能够识别特定的相互作用分子,并评估结合事件对所研究表型的功能相关性。

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