Study protein folding mechanism using a roadmap-based approach

使用基于路线图的方法研究蛋白质折叠机制

• 批准号: 7880613
• 负责人: Shuanghong Huo
• 金额: $ 24.98万
• 依托单位: CLARK UNIVERSITY (WORCESTER, MA)
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7880613
• 关键词: Address; Algorithms; Amino Acid Sequence; Amyloidosis; Antineoplastic Agents; Binding; Cleaved cell; Communities; Complex; Computer Simulation; Development; Diffusion; Disease; Drug Design; Genomics; Goals; Graph; Homologous Gene; Kinetics; Lead; Learning; Light; MDM2 gene; Maps; Methods; Names; Pathway interactions; Peptide Sequence Determination; Physical condensation; Process; Protein Conformation; Proteins; Reaction; Relative (related person); Robotics; Slide; Structure; TP53 gene; Testing; Thermodynamics; base; human disease; link protein; novel; protein folding; protein structure function; public health relevance; tool

DESCRIPTION (provided by applicant): Our long-term objective is to map the genomic sequence onto protein structure and function. To achieve this goal, understanding the details of protein folding process is essential. Although the concept of a protein energy landscape has been established, one of the key challenges confronting the biophysical community is to obtain the direct information on protein folding process in atomic detail. We propose to develop a general computational approach based on our novel roadmap-based method to understand this process. Our general roadmap-based approach will give relative folding rates, locate folding pathways, obligatory intermediate states, off-pathway intermediates, transition states, and verify the cooperativity between binding and folding. Our approach will utilize a roadmap (or a graph) to capture most important features of protein conformation space and energy landscape as proposed in Aim 1, in turn, rich thermodynamic and kinetic information will be extracted from the roadmap and further analyzed by graph-based tools as proposed in Aim 2. We have recently obtained promising results in predicting protein folding pathways using our novel graph- theoretical approach enhanced reaction-path algorithm, which is part of our roadmap-based approach. We expect our roadmap-based approach will yield a comprehensive picture of folding mechanism. The proposed applications in Aim 3 will focus on several small proteins, which will allow us to learn fundamental principles regarding the following aspects of protein folding mechanism: (a) unifying features in protein folding; (b) hidden intermediate; (c) "downhill" folding; (d) cooperativity between binding and folding. Information concerning folding process is not only indispensible in mapping the genomic sequence onto protein structure and function, but also important in amyloid diseases and other human diseases associated with intrinsically disordered proteins. A deeper understanding of protein folding process can ultimately lead to better computational models for drug design. PUBLIC HEALTH RELEVANCE: Understanding protein folding process in atomic detail is indispensible in mapping the genomic sequence onto protein structure and function. Protein folding/unfolding and misfolding are implicated in amyloid diseases and other human diseases associated with intrinsically disordered proteins. A deeper understanding of protein folding process can ultimately lead to better computational models for drug design.

描述（由申请人提供）：我们的长期目标是将基因组序列映射到蛋白质结构和功能上。为了实现这一目标，了解蛋白质折叠过程的细节是必不可少的。虽然蛋白质能量景观的概念已经建立，但生物物理学界面临的关键挑战之一是获得蛋白质折叠过程的原子细节的直接信息。我们建议基于我们新颖的基于路线图的方法开发一种通用的计算方法来理解这一过程。我们的一般基于路线图的方法将给出相对折叠率，定位折叠途径，强制性中间状态，非通路中间状态，过渡状态，并验证结合和折叠之间的协同性。我们的方法将利用路线图（或图表）来捕捉目标1中提出的蛋白质构象空间和能量景观的最重要特征，反过来，从路线图中提取丰富的热力学和动力学信息，并通过目标2中提出的基于图表的工具进一步分析。我们最近在使用我们新颖的图理论方法增强反应路径算法预测蛋白质折叠途径方面获得了有希望的结果，这是我们基于路线图的方法的一部分。我们期望我们的路线图为基础的方法将产生折叠机制的全面图片。Aim 3中提出的应用将集中在几种小蛋白质上，这将使我们能够了解蛋白质折叠机制的以下方面的基本原理：(a)蛋白质折叠的统一特征；(b)隐藏中间体；(c)“下坡”折叠；(d)装订与折叠的协同性。关于折叠过程的信息不仅是将基因组序列定位到蛋白质结构和功能上所必需的，而且在淀粉样蛋白疾病和其他与内在无序蛋白质相关的人类疾病中也很重要。对蛋白质折叠过程的深入了解最终可以为药物设计提供更好的计算模型。