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：
9379858
负责人：
Jianhan Chen
金额：
$ 26.84万
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/9379858
关键词：
Affect Algorithms Automobile Driving Binding Biological Biophysics Cancer Biology Cancer Intervention Cancer Prognosis Clinical Research Complex Coupled Coupling Disease Disease Pathway Equilibrium Genotoxic Stress Goals Grain 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 applied biomedical research 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（由应用提供）：肿瘤抑制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突变的类型可以与癌症的预后，对药物治疗的反应和患者生存有关。因此，至关重要的是了解各种类型的p53失活的分子基础突变，以了解生物学后果和评估潜在的癌症干预策略。该项目通过确定癌症突变体在其反式激活结构域（TAD）中灭活p53失活的结构和功能机制来促进这一重要目标。有趣的是，p53-TAD是一种本质上无序的蛋白质（IDP）。它的特性受构象的异质整体的控制，这些构象不适合使用传统方法来描述，这些方法旨在描述一组连贯的相似结构。可靠的原子模拟在描述IDP合奏及其相互作用方面起着重要而变革性的作用。同时，IDP（如p53-TAD）的异质和动态性质也提出了重要的挑战，以突破蛋白质力场精度和构象采样能力的极限。在这个项目中，我们将利用我们的丰富经验和最近在开发IDP的原子模拟的先进技术方面的贡献，并购买两个平行的特定目标。在AIM 1中，我们将开发新型的多尺度增强采样技术，以有效，准确地对IDP合奏及其相互作用进行精确的原子模拟。在AIM 2中，我们将将这些先进的仿真技术与NMR和其他生物物理实验整合在一起，以确定p53-Tad癌症突变的结构和功能后果。具体而言，我们将检验一个新的假设，即TAD癌突变可以调节未结合的构成集合，扰动p53与负调节剂MDM2和一般转录共激活器CBP之间的平衡，并进一步改变了这种平衡如何受P53-TAD的多场磷酸化调节。该项目的成功完成将为蛋白质构象等效和过渡的从头模拟提供尖端的计算工具。拟议的研究还代表了疾病突变体如何影响p53-TAD的结构功能关系的生物物理基础的首次系统研究，并提供了理解许多其他IDP的范式，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过度代表性。