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Image-based compound profiling reveals a dual inhibitor of tyrosine kinase and microtubule polymerization

机译:基于图像的化合物谱分析揭示了酪氨酸激酶和微管聚合的双重抑制剂

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摘要

Small-molecule compounds are widely used as biological research tools and therapeutic drugs. Therefore, uncovering novel targets of these compounds should provide insights that are valuable in both basic and clinical studies. I developed a method for image-based compound profiling by quantitating the effects of compounds on signal transduction and vesicle trafficking of epidermal growth factor receptor (EGFR). Using six signal transduction molecules and two markers of vesicle trafficking, 570 image features were obtained and subjected to multivariate analysis. Fourteen compounds that affected EGFR or its pathways were classified into four clusters, based on their phenotypic features. Surprisingly, one EGFR inhibitor (CAS 879127-07-8) was classified into the same cluster as nocodazole, a microtubule depolymerizer. In fact, this compound directly depolymerized microtubules. These results indicate that CAS 879127-07-8 could be used as a chemical probe to investigate both the EGFR pathway and microtubule dynamics. The image-based multivariate analysis developed herein has potential as a powerful tool for discovering unexpected drug properties.
机译:小分子化合物被广泛用作生物学研究工具和治疗药物。因此,发现这些化合物的新靶标应该提供在基础研究和临床研究中均有价值的见解。我通过量化化合物对表皮生长因子受体(EGFR)的信号转导和囊泡运输的影响,开发了一种基于图像的化合物谱分析方法。使用六个信号转导分子和两个标记的囊泡运输,获得了570个图像特征,并进行了多变量分析。根据其表型特征,影响EGFR或其途径的十四种化合物被分为四个簇。令人惊讶的是,一种EGFR抑制剂(CAS 879127-07-8)与微管解聚剂Nocodazole属于同一类。实际上,该化合物直接使微管解聚。这些结果表明,CAS 879127-07-8可用作研究EGFR途径和微管动力学的化学探针。本文开发的基于图像的多元分析有潜力作为发现意外药物特性的有力工具。

著录项

  • 期刊名称 Scientific Reports
  • 作者

    Kenji Tanabe;

  • 作者单位
  • 年(卷),期 -1(6),-1
  • 年度 -1
  • 页码 25095
  • 总页数 11
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

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