Fernández María Rosario, Batlle Cristina, Gil-García Marcos, Ventura Salvador
a Institut de Biotecnologia i de Biomedicina and Departament de Bioquímica i Biologia Molecular , Universitat Autonoma de Barcelona , Bellaterra (Barcelona) , Spain.
Prion. 2017 Jan 2;11(1):31-39. doi: 10.1080/19336896.2017.1282020.
Despite the significant efforts devoted to decipher the particular protein features that encode for a prion or prion-like behavior, they are still poorly understood. The well-characterized yeast prions constitute an ideal model system to address this question, because, in these proteins, the prion activity can be univocally assigned to a specific region of their sequence, known as the prion forming domain (PFD). These PFDs are intrinsically disordered, relatively long and, in many cases, of low complexity, being enriched in glutamine/asparagine residues. Computational analyses have identified a significant number of proteins having similar domains in the human proteome. The compositional bias of these regions plays an important role in the transition of the prions to the amyloid state. However, it is difficult to explain how composition alone can account for the formation of specific contacts that position correctly PFDs and provide the enthalpic force to compensate for the large entropic cost of immobilizing these domains in the initial assemblies. We have hypothesized that short, sequence-specific, amyloid cores embedded in PFDs can perform these functions and, accordingly, act as preferential nucleation centers in both spontaneous and seeded aggregation. We have shown that the implementation of this concept in a prediction algorithm allows to score the prion propensities of putative PFDs with high accuracy. Recently, we have provided experimental evidence for the existence of such amyloid cores in the PFDs of Sup35, Ure2, Swi1, and Mot3 yeast prions. The fibrils formed by these short stretches may recognize and promote the aggregation of the complete proteins inside cells, being thus a promising tool for targeted protein inactivation.
尽管人们付出了巨大努力来破译编码朊病毒或朊病毒样行为的特定蛋白质特征,但对它们的了解仍然很少。特征明确的酵母朊病毒构成了一个理想的模型系统来解决这个问题,因为在这些蛋白质中,朊病毒活性可以明确地归因于其序列中的一个特定区域,即朊病毒形成结构域(PFD)。这些PFD本质上是无序的,相对较长,并且在许多情况下复杂度较低,富含谷氨酰胺/天冬酰胺残基。计算分析已经在人类蛋白质组中鉴定出大量具有相似结构域的蛋白质。这些区域的组成偏差在朊病毒向淀粉样状态的转变中起着重要作用。然而,仅靠组成很难解释如何形成特定的接触,从而正确定位PFD,并提供焓力来补偿在初始组装中固定这些结构域所产生的巨大熵成本。我们推测,嵌入PFD中的短的、序列特异性的淀粉样核心可以执行这些功能,因此在自发聚集和接种聚集过程中充当优先成核中心。我们已经表明,在预测算法中实施这一概念可以高精度地对假定的PFD的朊病毒倾向进行评分。最近,我们提供了实验证据,证明在Sup35、Ure2、Swi1和Mot3酵母朊病毒的PFD中存在这种淀粉样核心。由这些短片段形成的纤维可能识别并促进细胞内完整蛋白质的聚集,因此是一种有前途的靶向蛋白质失活工具。