A mathematical framework for interpreting the molecular code of the tumor suppressor p53

解释肿瘤抑制因子 p53 分子密码的数学框架

• 批准号: 445690853
• 负责人: Dr. Marjan Faizi
• 金额: --
• 依托单位: Department of Systems Biology
• 依托单位国家: 德国
• 项目类别: WBP Fellowship
• 财政年份: 2020
• 资助国家: 德国
• 起止时间: 2019-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/445690853?language=en
• 关键词: mathematical; framework; interpreting; molecular; code

Post-translational modifications (PTMs) of proteins play a fundamental role in cellular signaling and regulation due to their fast dynamics and therefore are essential for dynamic cellular information processing. A single protein molecule can have multiple modification sites and thus can exhibit different patterns of co-occurring PTMs (hereafter called "modforms"). These patterns of PTMs act as a "molecular code" on that protein and confers information about the cellular condition that can be read by downstream processes. The tumor suppressor p53 is a key cellular regulator that harbors over 100 modification sites enabling it to integrate diverse stress signals and in response to activate or suppress hundreds of genes leading to different cell fate decisions. The overall aim of this project is to understand PTM encoding using the transcription factor and tumor suppressor p53 as an important biological example in cellular signaling and regulation.Elucidating PTM encoding and knowing the actual PTM state of a protein is essential to understand cellular information processing, however, the problem becomes more complicated considering that there is not only one but a population of molecules present in a cell leading to a distribution of different modforms. Current mass spectrometry methods that are used to estimate the modform distribution do not provide sufficient data/information to reconstruct the modform distribution of heavily modified proteins such as p53. Assuming, for instance, that p53 has approximately 100 modification sites and that all are binary (such as phosphorylation where an amino acid residue is either phosphorylated or not) then the protein exhibits 2^100 ≈ 10^30 possible modforms. This means that the solution of reconstructing the modform distribution exists in a space of dimension 2^100. I aim to develop a novel method that circumvents the high dimensional solution space to estimate a region in which the modform distribution must lie. Ideally, exploring the modform region will then help to detect which sites are most likely modified. These predictions shall guide future experiments with the goal to identify prevalent modified sites that determine cell fate outcome. Understanding the complicated PTM coding of p53 will have important implications for cell fate decision making and the understanding of cancer development and therapies.

蛋白质的翻译后修饰（PTMs）由于其快速的动力学特性而在细胞信号传导和调控中起着重要作用，因此对于动态细胞信息处理是必不可少的。单个蛋白质分子可以具有多个修饰位点，因此可以表现出不同模式的共同存在的PTM（下文称为“修饰形式”）。这些PTM模式充当该蛋白质上的“分子密码”，并赋予下游过程可以读取的细胞状况信息。肿瘤抑制因子p53是一种关键的细胞调节因子，具有超过100个修饰位点，使其能够整合不同的应激信号，并响应激活或抑制数百个基因，导致不同的细胞命运决定。本项目的总体目标是利用转录因子和肿瘤抑制因子p53作为细胞信号传导和调节的重要生物学实例来理解PTM编码。阐明PTM编码和了解蛋白质的实际PTM状态对于理解细胞信息处理是必不可少的，然而，考虑到细胞中不仅存在一种分子，而且存在一群分子，导致不同形态的分布，问题变得更加复杂。用于估计modform分布的当前质谱方法不能提供足够的数据/信息来重建重度修饰的蛋白质如p53的modform分布。例如，假设p53有大约100个修饰位点，并且都是二元的（例如磷酸化，其中一个氨基酸残基要么被磷酸化，要么不被磷酸化），那么该蛋白质就有2^100 <$10^30种可能的修饰形式。这意味着重构模态分布的解存在于2^100维空间中。我的目标是开发一种新的方法，绕过高维的解决方案空间，估计区域中的modform分布必须位于。理想情况下，探索modform区域将有助于检测哪些网站最有可能被修改。这些预测将指导未来的实验，目标是确定决定细胞命运结果的普遍修饰位点。了解p53的复杂PTM编码将对细胞命运决策以及对癌症发展和治疗的理解具有重要意义。