磷酸化蛋白芯片结合人工智能工具进行精准药物筛选

None Katsuhisa Horimoto, None Yuki Suyama, None Tadamasa Sasaki, None Kazuhiko Fukui, None Lili Feng, None Meiling Sun, None Yamin Tang, None Yixuan Zhang, None Dongyin Chen, None Feng Han
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引用次数: 0

摘要

我们开发了一种蛋白质阵列系统,名为“Phospho-Totum”,它可以在阵列上再现样品的磷酸化状态。该蛋白阵列包含来自173个已知信号通路的1471个蛋白。根据样品中酪氨酸激酶的活化程度,在相同条件下对阵列上相应的底物蛋白基团进行磷酸化。除了测量1471个底物的磷酸化水平外,我们开发并执行了人工智能辅助工具,以进一步表征磷酸化状态并估计途径激活、酪氨酸激酶激活以及产生与样品相似的磷酸化状态的激酶抑制剂列表。Phospho-Totum系统无缝连接并询问测量和分析,不仅有可能通过再现样品的磷酸化状态来阐明疾病的病理生理机制,而且对药物发现也很有用,特别是对潜在药物激酶抑制剂的靶向激酶筛选。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Phosphorylated protein chip combined with artificial intelligence tools for precise drug screening
We have developed a protein array system, named “Phospho-Totum”, which reproduces the phosphorylation state of a sample on the array. The protein array contains 1 471 proteins from 173 known signaling pathways. According to the activation degrees of tyrosine kinases in the sample, the corresponding groups of substrate proteins on the array are phosphorylated under the same conditions. In addition to the measured phosphorylation levels of the 1 471 substrates, we developed and performed the AI-assisted tools to further characterize the phosphorylation state and estimate pathway activation, tyrosine kinase activation, and a list of kinase inhibitors that produce phosphorylation states similar to that of the sample. The Phospho-Totum system, which seamlessly links and interrogates the measurements and analyses, has the potential to not only elucidate pathophysiological mechanisms in diseases, by reproducing the phosphorylation state of samples, but also be useful for drug discovery, particularly for screening targeted kinases for potential drug kinase inhibitors.
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