Information Processing by Post-translational Modification

摘要/摘要 生物体中的大多数蛋白质都是通过化学基团共价连接到 特定的氨基酸残基。这种“翻译后修饰”(PTM)允许蛋白质功能 在生理时间尺度上进行调制。PTM参与调节大多数细胞过程。 并经常在重大疾病中出现紊乱。对于一种蛋白质来说，具有多种类型的 修饰，这些修饰发生在蛋白质的多个位置上，以及不同的修饰上 结合相互作用的部位来影响蛋白质的功能。这可能会造成爆炸式的 组合修饰状态。这项提案将重点关注的肿瘤抑制基因P53 100多个修饰位点，创造了1030多个组合的潜力 这种单一蛋白质的修饰状态。这些州中几乎没有几个会在任何时候出现，除非 留下了一个悬而未决的问题，即哪些状态存在，以及它们在不同的细胞中是如何变化的 条件。我们以前的工作为解决这些问题奠定了基础。我们有 介绍了“模形式”和“模形式分布”的定量语言，它们提供了一种 描述体内PTM状态的严格生物物理学基础。我们创造了数学方法 用于分析可以测量这种分布的质谱学(MS)方法和 已经确定了它们的基本极限。我们已经证明了“自下而上”和“结合”的必要性。 “中下”MS，蛋白质首先以多肽形式消化，总体上是“自上而下”的MS 蛋白质。这些不同类型的MS数据限制了蛋白质的形态分布在高- 多维的“模式区”。我们已经开发了可供公众访问的软件来评估 地区。我们发现，P53结合了其脉动表达动态和PTM状态 充当中心蜂窝枢纽并协调多条下游路径以响应多个 上游条件。在这里，我们以这些发现为基础，通过一个经过测试的多学科小组 合作者，他们的专长横跨数学、计算、细胞生物学和质谱学。 我们的目标是开发MS方法来估计典型细胞蛋白质的模板区域并使用 这些方法揭示了p53是如何结合动态和模式来处理信息的。通过 聚焦于这样一个具有挑战性的范例，我们希望在了解p53本身的同时 开发可广泛应用于PTMS中的其他细胞蛋白质的概念和方法 发挥核心作用。

Summary/Abstract Most proteins in an organism are reversibly modified by covalent attachment of chemical groups to specific amino-acid residues. Such “post-translational modification” (PTM) allows protein function to be modulated on a physiological time-scale. PTMs are involved in regulating most cellular processes and frequently disordered in major diseases. It is not uncommon for a protein to have many types of modification, for these to occur on multiple sites across the protein and for modifications on different sites to interact combinatorially to influence protein function. This can create an explosion of combinatorial modification states. The tumor suppressor p53, on which this proposal will focus, has more than 100 sites of modification, creating the potential for more than 1030 combinatorial modification states on this single protein. Very few of these states will be present at any time but that leaves open the question of which states are present and how they vary under different cellular conditions. Our previous work has laid a foundation for addressing these questions. We have introduced the quantitative language of “modforms” and “modform distributions”, which provide a rigorous biophysical basis for describing PTM states in vivo. We have created mathematical methods for analyzing the mass-spectrometry (MS) approaches which can measure such distributions and have determined their fundamental limits. We have shown the necessity of combining “bottom-up” and “middle-down” MS, in which proteins are first digested in peptides, with “top-down” MS on whole proteins. These different types of MS data constrain a protein's modform distribution within a high- dimensional “modform region”. We have developed publicly-accessible software for estimating such regions. We have discovered that p53 integrates its pulsatile expression dynamics and its PTM state to act as a central cellular hub and orchestrate multiple downstream pathways in response to multiple upstream conditions. Here, we build on these findings with a tested multi-disciplinary group of collaborators, whose expertise spans mathematics, computation, cell biology and mass spectrometry. Our goal is to develop MS methods to estimate modform regions of typical cellular proteins and to use those methods to unravel how p53 combines dynamics and modforms to process information. By focusing on such a challenging exemplar, we expect to learn a great deal about p53 itself while developing concepts and methods that can be widely applied to other cellular proteins in which PTMs play a central role.