Preventing Protein Aggregation by Controlling Unfolded State Dynamics

通过控制展开状态动力学来防止蛋白质聚集

• 批准号: 8399800
• 负责人: Lisa J Lapidus
• 金额: $ 25.53万
• 依托单位: MICHIGAN STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8399800
• 关键词: Affect; Alzheimer' s Disease; Amino Acid Sequence; Brain; Complex; Computer Simulation; Curcumin; Cysteine; Data; Diffusion; Disease; Drug Design; Equilibrium; Exhibits; Experimental Models; Future; Goals; Human; Hydrogenase; Lead; Measurement; Measures; Methods; Microfluidics; Modeling; Mutation; Optical Instrument; Oryctolagus cuniculus; Paper; Parkinson Disease; Patients; Peptide Sequence Determination; Peptides; Pharmaceutical Preparations; Prions; Probability; Protein Dynamics; Proteins; Public Health; Publishing; Research; Resolution; Solvents; Staging; Structure; Techniques; Testing; Tryptophan; alpha synuclein; base; design; drug candidate; inhibitor/antagonist; intermolecular interaction; molecular dynamics; monomer; nanosecond; novel; polyphenol; prevent; protein aggregation; protein folding; research study; small molecule; solute; synuclein; theories; triplet state

DESCRIPTION (provided by applicant): Unfolded proteins are highly complex objects, containing native and non-native interactions but still remain able to reconfigure diffusively. Recent results from the PI's lab show that unfolded proteins under folding conditions show a wide range of intramolecular diffusion coefficients, spanning three orders of magnitude. There is an emerging correlation between intramolecular diffusion and aggregation propensity, with aggregation-prone proteins occupying the middle of this dynamic range. To understand the relationship between aggregation and unfolded protein dynamics, this project will measure intramolecular diffusion in a variety of sequences prone to aggregation and how diffusion changes with mutation. To apply this relationship to drug design, the effect of small molecule aggregation inhibitors on diffusion will be observed. The PI uses the novel technique of quenching of the triplet state of tryptophan by cysteine, which is measured with an optical instrument with nanosecond resolution. Intramolecular diffusion coefficients can be extracted from these measured rates using a theory by Szabo, Schulten and Schulten which requires a probability distribution of equilibrium distances between the tryptophan and cysteine in the sequence. A crucial aspect of this project is the computational modeling of the probability distribution by either all-atom molecular dynamics or a polymeric model developed by the PI. Alzheimer's A? and ?-synuclein will be measured in equilibrium, and hydrogenase maturation protein and various mammalian prion proteins will be measured in a novel microfluidic mixer that rapidly dilutes denaturant in ~250 ms. PUBLIC HEALTH RELEVANCE: Aggregation-based diseases, such as Alzheimer's and Parkinson's disease, represent a large and growing threat to public health. While much research has focused on the structure of large clumps of protein found in the brains of patients with these diseases, we still do not know why they form or how to stop them. This project will explore the dynamics of these proteins before they start to aggregate and look at the effect of small molecules that might prevent aggregation.

描述（由申请人提供）：未折叠的蛋白质是高度复杂的物体，包含天然和非天然相互作用，但仍然能够扩散地重新配置。 PI 实验室的最新结果表明，折叠条件下的未折叠蛋白质显示出广泛的分子内扩散系数，跨越三个数量级。分子内扩散和聚集倾向之间存在着新兴的相关性，易于聚集的蛋白质占据了这一动态范围的中间。为了了解聚集和未折叠蛋白质动力学之间的关系，该项目将测量易于聚集的各种序列中的分子内扩散以及扩散如何随突变而变化。为了将这种关系应用于药物设计，将观察小分子聚集抑制剂对扩散的影响。 PI 采用半胱氨酸猝灭色氨酸三重态的新技术，并使用纳秒分辨率的光学仪器进行测量。可以使用 Szabo、Schulten 和 Schulten 的理论从这些测量的速率中提取分子内扩散系数，该理论需要序列中色氨酸和半胱氨酸之间的平衡距离的概率分布。该项目的一个重要方面是通过全原子分子动力学或 PI 开发的聚合物模型对概率分布进行计算建模。阿尔茨海默病A？和β-突触核蛋白将在平衡状态下进行测量，氢化酶成熟蛋白和各种哺乳动物朊病毒蛋白将在新型微流体混合器中测量，该混合器可在~250 ms内快速稀释变性剂。 公共健康相关性：阿尔茨海默病和帕金森病等聚集性疾病对公共健康构成了巨大且日益严重的威胁。虽然许多研究都集中在患有这些疾病的患者大脑中发现的大块蛋白质的结构，但我们仍然不知道它们为何形成或如何阻止它们。该项目将探索这些蛋白质在开始聚集之前的动力学，并研究可能阻止聚集的小分子的影响。