Folding@Home: Simulating Folding on the Millisecond to Second Timescale

Folding@Home：在毫秒到秒的时间尺度上模拟折叠

• 批准号: 8886377
• 负责人: VIJAY S PANDE
• 金额: $ 46万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8886377
• 关键词: Address; Algorithms; Alzheimer' s Disease; Amino Acids; Area; Attention; Binding; Biological; Biological Models; Biological Phenomena; Biological Process; Biology; Cell Death; Cells; Client; Collaborations; Computing Methodologies; Confined Spaces; Coupled; Crowding; Data; Development; Disease; Environment; Foundations; Generations; Goals; Grant; Home environment; Huntington Disease; Hybrids; Kinetics; Lead; Length; Ligand Binding; Light; Malignant Neoplasms; Membrane; Methodology; Methods; Modeling; Nature; Peptides; Play; Proteins; Renaissance; Rest; Role; Series; Solutions; Solvents; Sorting - Cell Movement; Speed; Statistical Mechanics; Structure; System; Testing; Time; Uncertainty; Vocabulary; Work; base; cluster computing; innovation; insight; interest; meetings; men who have sex with men; millisecond; novel; protein complex; protein folding; protein misfolding; public health relevance; research study; simulation; theories; tool

 DESCRIPTION (provided by applicant): Due the limitations of both simulation and experiment, an ultimate understanding of protein folding will come from a coupled approach of detailed simulations extensively validated and tested by experiment. However, developing simulation methodology which can quantitatively connect with experimental kinetics still remains a great theoretical challenge, due to the long timescales involved and the difficulties and complexities of detailed, atomistic models. Here, we propose new, third generation distributed computing methods to tackle these challenges and the application of these methods to questions related to how proteins self-assemble in solution as well as in the biologically relevant contexts. While protein folding has itself been studied computationally for many years, our work differs from other approaches in (1) its use of innovative distributed computing methods for simulating long, biologically relevant time scale kinetics (on the millisecond to second timescale - dramatically longer than the previous state of the art) and for large and complex proteins (on the 100+ amino acid length scale) using detailed, fully atomistic, explicit solvent models and (2) the application of these detailed models to address questions of folding in the biological contexts of different environments in the cell. Moreover, we are able to perform a quantitative comparison to experiment, which is critical for both the testing and greater impact of our computational methods; indeed, key experimental collaborations using cutting edge methods are proposed to make direct connections to our proposed simulations. Finally, the proposed work would have an impact on our basic understanding of several protein-related diseases, such protein misfolding diseases, such as Alzheimer's Disease and Huntington's Disease. Indeed, methodology from the previous project period has already lead to advances in the simulation of peptide aggregation in Alzheimer's and Huntington's Disease. Also, by understanding the nature of folding in biological contexts, such as in the presence of membranes, in biologically confined spaces, and with crowding agents, and by directly comparing those simulations to novel experiments of folding in the cell, we would gain insight into the nature of protein folding in viv, which is the next important step in our understanding of protein folding and its connection to biology and biomedical questions.

 描述（由申请人提供）：由于模拟和实验的局限性，对蛋白质折叠的最终理解将来自于通过实验广泛验证和测试的详细模拟的耦合方法。然而，由于所涉及的时间尺度较长以及实验的困难和复杂性，开发能够定量地与实验动力学联系起来的模拟方法仍然是一个巨大的理论挑战。 详细的原子模型。在这里，我们提出了新的第三代分布式计算方法来应对这些挑战，并将这些方法应用于与蛋白质如何在溶液中以及生物学相关的环境中自组装相关的问题。虽然蛋白质折叠本身已经在计算上进行了多年的研究，但我们的工作与其他方法的不同之处在于（1）它使用创新的分布式计算方法来模拟长的、生物学相关的时间尺度动力学（在毫秒到秒的时间尺度上——比以前的现有技术水平要长得多），并且使用详细的、完全原子的、显式的方法来模拟大型和复杂的蛋白质（在100多个氨基酸长度尺度上） 溶剂模型和（2）应用 这些详细的模型来解决细胞中不同环境的生物背景下的折叠问题。此外，我们能够与实验进行定量比较，这对于我们的计算方法的测试和更大影响至关重要；事实上，建议使用尖端方法进行关键实验合作，以与我们提出的模拟建立直接联系。最后，拟议的工作将影响我们对几种蛋白质相关疾病的基本理解，例如蛋白质错误折叠疾病，例如阿尔茨海默病和亨廷顿病。事实上，上一个项目期间的方法已经在阿尔茨海默病和亨廷顿舞蹈病的肽聚集模拟方面取得了进展。此外，通过了解生物环境中折叠的本质，例如在存在膜的情况下、在生物有限的空间中以及使用拥挤剂时，并通过直接将这些模拟与细胞中折叠的新实验进行比较，我们将深入了解体内蛋白质折叠的本质，这是我们理解蛋白质折叠及其与生物学和生物医学问题的联系的下一个重要步骤。