Multi-scale enhanced sampling of disordered proteins

无序蛋白质的多尺度增强采样

基本信息

批准号：
9485621
负责人：
Jianhan Chen
金额：
$ 28.32万
依托单位：
UNIVERSITY OF MASSACHUSETTS AMHERST
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-01-01 至 2020-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9485621
关键词：
Affect Algorithms Automobile Driving Binding Biological Biomedical Research Biophysics Cancer Biology Cancer Intervention Cancer Prognosis Cereals Clinical Research Complex Coupled Coupling Disease Disease Pathway Equilibrium Genotoxic Stress Goals Human Intervention Kinetics Knowledge Link MDM2 gene Malignant Neoplasms Mediating Methods Modeling Molecular Molecular Conformation Mutate Mutation N-terminal Nature Outcome Patients Peptides Pharmacotherapy Phosphorylation Play Post-Translational Protein Processing Property Protein Conformation Protein p53 Proteins Protocols documentation Research Resolution Role Sampling Sequence Analysis Side Signal Transduction Structure Structure-Activity Relationship TP53 gene Techniques Temperature Testing Thermodynamics Time Transactivation Transcription Coactivator Tumor Suppression Vertebral column advanced simulation base biophysical analysis cancer statistics comparative computer studies computerized tools conformational conversion design experience experimental study malignant breast neoplasm model design mutant novel public health relevance response restraint simulation small molecule treatment response tumorigenesis

项目摘要

DESCRIPTION (provided by applicant): The tumor suppressor p53 is the most frequently mutated protein in human cancers. Clinical studies of breast cancer have suggested that the type of p53 mutation can be linked to cancer prognosis, response to drug treatment, and patient survival. It is thus crucial to understand the molecular basis of p53 inactivation by various types of mutations, so as to understand the biological consequences and assess potential cancer intervention strategies. This project contributes to this important goal by determining the structural and functional mechanisms of p53 inactivation by cancer mutants in its transactivation domain (TAD). Intriguingly, p53-TAD is an intrinsically disordered protein (IDP). Its properties are governed by a heterogeneous ensemble of conformations that does not lend itself to description using traditional methods that are geared toward describing a coherent set of similar structures. Reliable atomistic simulations have an important and transformative role to play in terms of describing IDP ensembles and their interactions. At the same time, the heterogeneous and dynamic nature of IDPs like p53-TAD also present important challenges that push the limit of the protein force field accuracy and conformational sampling capability. In this project, we wil leverage our extensive experience and recent contributions in developing advanced techniques for atomistic simulation of IDPs and pursue two parallel specific aims. In Aim 1, we will develop novel multi-scale enhanced sampling techniques for efficient and accurate atomistic simulations of IDP ensembles and their interaction. In Aim 2, we will integrate these advanced simulation techniques with NMR and other biophysical experiments to determine the structural and functional consequences of p53-TAD cancer mutations. Specifically, we will test a novel hypothesis that TAD cancer mutations can modulate unbound conformational ensembles, perturb the balance between p53 binding to negative regulator MDM2 and the general transcriptional co-activator CBP, and further alter how this balance is regulated by multisite phosphorylation of p53-TAD. Successful completion of this project will provide cutting-edge computational tools for de novo simulation of protein conformational equilibria and transitions. The proposed research also represents the first systematic study of the biophysical basis of how disease mutants affect the structure-function relationship of p53-TAD, and provides a paradigm for understanding many other IDPs that are key components of cellular regulatory networks and over-represented in major disease pathways.

描述（由申请人提供）：肿瘤抑制因子 p53 是人类癌症中最常见的突变蛋白。乳腺癌的临床研究表明，p53 突变的类型可能与癌症预后、药物治疗反应和患者生存有关。因此，了解各种类型 p53 失活的分子基础至关重要有趣的是，p53-TAD 是通过确定癌症突变体导致 p53 失活的结构和功能机制来了解其生物学后果并评估潜在的癌症干预策略。是一种本质上无序的蛋白质（IDP），其特性由异质构象集合控制，不适合使用旨在描述一组连贯的相似结构的传统方法进行描述。原子模拟在描述 IDP 整体及其相互作用方面具有重要的变革性作用，同时，p53-TAD 等 IDP 的异质性和动态性也提出了重要的挑战，突破了蛋白质力场精度的极限。在这个项目中，我们将利用我们在开发 IDP 原子模拟先进技术方面的丰富经验和最近的贡献，并追求两个并行的具体目标。在目标 1 中，我们将开发新颖的多尺度增强采样。在目标 2 中，我们将这些先进的模拟技术与 NMR 和其他生物物理实验相结合，以确定 p53-TAD 癌症突变的结构和功能后果。一种新的假设，即 TAD 癌症突变可以调节未结合的构象整体，扰乱与负调节因子 MDM2 结合的 p53 与一般转录共激活因子 CBP 之间的平衡，并进一步改变这种平衡的调节方式p53-TAD 的多位点磷酸化。该项目的成功完成将为蛋白质构象平衡和转变的从头模拟提供尖端的计算工具，也是对疾病突变体如何影响结构的生物物理基础的首次系统研究。 p53-TAD 的功能关系，并为理解许多其他 IDP 提供了范例，这些 IDP 是细胞调节网络的关键组成部分，并且在主要疾病途径中占有过多比例。