Robust rare event simulation for protein folding and disease-related aggregation

蛋白质折叠和疾病相关聚集的稳健罕见事件模拟

基本信息

批准号：
9316663
负责人：
Aaron Dinner
金额：
$ 33.36万
依托单位：
UNIVERSITY OF CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-08-01 至 2020-07-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): This proposal describes the development and application of rare event methods that will open the door to treating classes of biomolecular problems that are challenging for existing methods owing to their multipathway character. These include problems in protein folding and aggregation that remain outstanding, despite enormous progress in those areas in recent years. The key idea is to rigorously characterize the error behavior of the methods (in particular in the low temperature limit) to derive criteria tat can be used to adaptively refocus sampling for maximal efficiency. The properties of the methods that we seek are as follows: (i) they will be capable of operating with more than a few reaction coordinates to allow treating problems without obvious choices of descriptors, (ii) they will efficiently sample reaction mechanisms that proceed via a complex network of transitions rather than a single dominant pathway, (iii) they will be fully non-equilibrium, i.e., they will generate reactive trajectories and the statistical properties of those trajectories including rates and other dynamical quantities such as time correlation functions, and (iv) the results that they provide will not depend on the particular choice of reaction coordinates (though the convergence rate typically will) or on any Markov assumptions. The proposed methods will be applied to two protein folding problems that are beyond present enhanced sampling methods. The first system is beta3s, a 20-residue designed three-stranded antiparallel beta-sheet miniprotein. We choose this system because data on its folding and unfolding exists from extensive physically weighted molecular dynamics simulations, and analyses by several groups show that it has a well-defined native state and complex dynamics that are characteristic of much larger proteins. The second system is much less well characterized, but improved means for modeling it can provide information of major biomedical significance: we will map the states and transitions accessible to monomers and oligomers of alpha-synuclein, a 140-residue intrinsically disordered protein that is linked to a number of neurodegenerative diseases, including Parkinson's Disease and Dementia with Lewy Bodies.

描述（由申请人提供）：该提案描述了罕见事件方法的开发和应用，这将为治疗由于其多途径特性而对现有方法具有挑战性的各类生物分子问题打开大门。其中包括蛋白质折叠和聚集方面的问题，尽管近年来这些领域取得了巨大进展，但这些问题仍然突出。关键思想是严格表征方法的误差行为（特别是在低温限制下），以得出可用于自适应重新聚焦采样以获得最大效率的标准。我们寻求的方法的属性如下：（i）它们将能够使用多个反应坐标进行操作，以允许在没有明显选择描述符的情况下处理问题，（ii）它们将有效地对通过以下方式进行的反应机制进行采样：一个复杂的转变网络而不是单一的主导途径，（iii）它们将完全不平衡，即它们将产生反应轨迹和这些轨迹的统计特性，包括速率以及其他动力学量，例如时间相关函数，以及（iv）它们提供的结果不取决于反应坐标的特定选择（尽管收敛速度通常会）或任何马尔可夫假设。所提出的方法将应用于超出现有增强采样方法的两个蛋白质折叠问题。第一个系统是 beta3s，一种由 20 个残基设计的三链反平行 β-片层微型蛋白。我们选择这个系统是因为其折叠和展开的数据来自广泛的物理加权分子动力学模拟，并且多个小组的分析表明它具有明确的天然状态和复杂的动力学，这是较大蛋白质的特征。第二个系统的特征要少得多，但改进的建模方法可以提供具有重大生物医学意义的信息：我们将绘制α-突触核蛋白单体和寡聚体可访问的状态和转变，α-突触核蛋白是一种具有 140 个残基的本质无序蛋白质，一些神经退行性疾病，包括帕金森病和路易体痴呆。