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利用乙酰转移酶化学蛋白质组探针中的离子选择性。

Harnessing Ionic Selectivity in Acetyltransferase Chemoproteomic Probes.

机构信息

Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702, United States.

Stowers Institute for Medical Research, Kansas City, Missouri 64110, United States.

出版信息

ACS Chem Biol. 2021 Jan 15;16(1):27-34. doi: 10.1021/acschembio.0c00766. Epub 2020 Dec 29.

Abstract

Chemical proteomics provides a powerful strategy for the high-throughput assignment of enzyme function or inhibitor selectivity. However, identifying optimized probes for an enzyme family member of interest and differentiating signal from the background remain persistent challenges in the field. To address this obstacle, here we report a physiochemical discernment strategy for optimizing chemical proteomics based on the coenzyme A (CoA) cofactor. First, we synthesize a pair of CoA-based sepharose pulldown resins differentiated by a single negatively charged residue and find this change alters their capture properties in gel-based profiling experiments. Next, we integrate these probes with quantitative proteomics and benchmark analysis of "probe selectivity" versus traditional "competitive chemical proteomics." This reveals that the former is well-suited for the identification of optimized pulldown probes for specific enzyme family members, while the latter may have advantages in discovery applications. Finally, we apply our anionic CoA pulldown probe to evaluate the selectivity of a recently reported small molecule N-terminal acetyltransferase inhibitor. These studies further validate the use of physical discriminant strategies in chemoproteomic hit identification and demonstrate how CoA-based chemoproteomic probes can be used to evaluate the selectivity of small molecule protein acetyltransferase inhibitors, an emerging class of preclinical therapeutic agents.

摘要

化学蛋白质组学为高通量分配酶功能或抑制剂选择性提供了强大的策略。然而,鉴定针对感兴趣的酶家族成员的优化探针并区分信号与背景仍然是该领域的持续挑战。为了解决这个障碍,我们在这里报告了一种基于辅酶 A(CoA)辅因子的化学蛋白质组学优化的物理化学辨别策略。首先,我们合成了一对基于 CoA 的琼脂糖下拉树脂,通过一个带负电荷的残基区分,我们发现这种变化改变了它们在基于凝胶的分析实验中的捕获特性。接下来,我们将这些探针与定量蛋白质组学结合,并对“探针选择性”与传统的“竞争性化学蛋白质组学”进行基准分析。这表明前者非常适合鉴定特定酶家族成员的优化下拉探针,而后者在发现应用中可能具有优势。最后,我们应用我们的阴离子 CoA 下拉探针来评估最近报道的小分子 N-端乙酰转移酶抑制剂的选择性。这些研究进一步验证了物理判别策略在化学蛋白质组学命中鉴定中的应用,并展示了如何使用基于 CoA 的化学蛋白质组学探针来评估小分子蛋白乙酰转移酶抑制剂的选择性,这是一类新兴的临床前治疗药物。

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