打开组织转谷氨酰胺酶:当构象比酶活性更重要。

Med One Pub Date : 2018-01-01 Epub Date: 2018-11-22 DOI:10.20900/mo.20180011
William P Katt, Marc A Antonyak, Richard A Cerione
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引用次数: 15

摘要

组织转谷氨酰胺酶(tTG),也称为2型转谷氨酰胺酶或Gαh,可以结合和水解GTP,并具有蛋白质交联酶的功能。tTG广泛表达,可以在细胞内和细胞外空间检测到。与许多酶相比,tTG的活性和非活性构象明显不同。催化无活性形式的tTG采用紧凑的“封闭状态”构象,而催化活性形式的蛋白质采用拉长的“开放状态”构象。长期以来,tTG一直被认为是许多疾病的重要参与者,包括乳糜泻、神经退行性疾病和癌症,它在这些疾病中的作用往往取决于它的构象和催化活性。虽然其促进这些疾病的能力传统上被认为依赖于其蛋白质交联活性,但最近的研究结果表明,tTG所采用的构象状态对于介导其作用也很重要。特别是,我们和其他人已经证明tTG的关闭状态对促进细胞生长和存活是重要的,而保持tTG的开放状态是细胞毒性的。在这篇综述中,我们研究了tTG的两种独特构象以及它们如何参与不同的生物过程。我们还将描述如何使用这些信息来产生治疗疾病的新疗法,特别关注癌症。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Opening up about Tissue Transglutaminase: When Conformation Matters More than Enzymatic Activity.

Tissue transglutaminase (tTG), also referred to as type 2 transglutaminase or Gαh, can bind and hydrolyze GTP, as well as function as a protein crosslinking enzyme. tTG is widely expressed and can be detected both inside cells and in the extracellular space. In contrast to many enzymes, the active and inactive conformations of tTG are markedly different. The catalytically inactive form of tTG adopts a compact "closed-state" conformation, while the catalytically active form of the protein adopts an elongated "open-state" conformation. tTG has long been appreciated as an important player in numerous diseases, including celiac disease, neuronal degenerative diseases, and cancer, and its roles in these diseases often depend as much upon its conformation as its catalytic activity. While its ability to promote these diseases has been traditionally thought to be dependent on its protein crosslinking activity, more recent findings suggest that the conformational state tTG adopts is also important for mediating its effects. In particular, we and others have shown that the closed-state of tTG is important for promoting cell growth and survival, while maintaining tTG in the open-state is cytotoxic. In this review, we examine the two unique conformations of tTG and how they contribute to distinct biological processes. We will also describe how this information can be used to generate novel therapies to treat diseases, with a special focus on cancer.

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