Ultrasensitive, multiplexed chemoproteomic profiling with soluble activity-dependent proximity ligation

蛋白质组 计算生物学 仿形(计算机编程) 药物发现 多路复用 寡核苷酸 蛋白质组学 生物 DNA 计算机科学 生物化学 生物信息学 基因 操作系统
作者
Gang� Li,Mark A. Eckert,Jae Won Chang,Jeffrey E. Montgomery,Agnieszka Chryplewicz,Ernst Lengyel,Raymond E. Moellering
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [National Academy of Sciences]
卷期号:116 (43): 21493-21500 被引量:11
标识
DOI:10.1073/pnas.1912934116
摘要

Chemoproteomic methods can report directly on endogenous, active enzyme populations, which can differ greatly from measures of transcripts or protein abundance alone. Detection and quantification of family-wide probe engagement generally requires LC-MS/MS or gel-based detection methods, which suffer from low resolution, significant input proteome requirements, laborious sample preparation, and expensive equipment. Therefore, methods that can capitalize on the broad target profiling capacity of family-wide chemical probes but that enable specific, rapid, and ultrasensitive quantitation of protein activity in native samples would be useful for basic, translational, and clinical proteomic applications. Here we develop and apply a method that we call soluble activity-dependent proximity ligation (sADPL), which harnesses family-wide chemical probes to convert active enzyme levels into amplifiable barcoded oligonucleotide signals. We demonstrate that sADPL coupled to quantitative PCR signal detection enables multiplexed "writing" and "reading" of active enzyme levels across multiple protein families directly at picogram levels of whole, unfractionated proteome. sADPL profiling in a competitive format allows for highly sensitive detection of drug-protein interaction profiling, which allows for direct quantitative measurements of in vitro and in vivo on- and off-target drug engagement. Finally, we demonstrate that comparative sADPL profiling can be applied for high-throughput molecular phenotyping of primary human tumor samples, leading to the discovery of new connections between metabolic and proteolytic enzyme activity in specific tumor compartments and patient outcomes. We expect that this modular and multiplexed chemoproteomic platform will be a general approach for drug target engagement, as well as comparative enzyme activity profiling for basic and clinical applications.

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