ITR/AP: A Motion Planning Approach for Protein Folding Simulation

ITR/AP：蛋白质折叠模拟的运动规划方法

• 批准号: 0113974
• 负责人: Nancy Amato
• 金额: $ 30万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0113974&HistoricalAwards=false
• 关键词: ITR; AP; Motion; Planning; Approach

This project will develop a framework for studying protein folding that is based on techniques recently developed in the robotics motion planning community. In particular, this work uses Probabilistic Roadmap (PRM) motion planning techniques which have proven to be very successful for problems involving high-dimensional configuration spaces. The key advance that PRMs offer protein science is the ability to efficiently explore large conformational transitions of realistic models of proteins. The work involves research in both protein science and information technology. The project has two main research goals related to protein science. First, PRMs are expected to provide a computational method to predict the folding kinetics of proteins, when the native structure is already known. This makes PRMs ideal for investigating classical problems in protein folding kinetics such as kinetic intermediates, kinetic traps, parallel vs. series folding routes, and general folding mechanism questions related to potential energy landscapes and zippers processes. Second, PRM, used in conjunction with a new ENPOP parameter optimization strategy, has the potential to improve energy models both high-resolution and low-resolution models for predicting biomolecule conformations. The project has two main research goals related to information technology. Both are motivated by the massive computational requirements of the simulations needed to investigate the protein folding questions. First, new strategies and optimization techniques for PRMs will be needed to support the efficient extraction of high quality paths from the roadmaps for problems with hundreds of dof. Second, since PRMs are known to be amenable to parallel implementation, they will utilize high-performance computing. This will include the development and application of an adaptive parallel version of the C++ STL (Standard Templates library) called STAPL. With STAPL, the simulations can be optimized and run on various parallel and distributed systems and yield a performance approaching that of code manually optimized for each platform

该项目将开发一个研究蛋白质折叠的框架，该框架基于机器人运动规划社区最近开发的技术。特别是，这项工作使用概率路线图（PRM）的运动规划技术，已被证明是非常成功的高维配置空间的问题。PRM为蛋白质科学提供的关键进步是能够有效地探索蛋白质现实模型的大构象转变。这项工作涉及蛋白质科学和信息技术的研究。 该项目有两个与蛋白质科学相关的主要研究目标。首先，PRM有望提供一种计算方法来预测蛋白质的折叠动力学，当天然结构是已知的。这使得PRM非常适合研究蛋白质折叠动力学中的经典问题，如动力学中间体，动力学陷阱，平行与串联折叠路线，以及与势能景观和拉链过程相关的一般折叠机制问题。第二，PRM，结合一个新的ENPOP参数优化策略，有可能提高能量模型的高分辨率和低分辨率模型预测生物分子构象。 该项目有两个与信息技术有关的主要研究目标。 两者都是出于研究蛋白质折叠问题所需的模拟的大量计算需求。首先，需要新的策略和PRM优化技术来支持从数百个自由度的问题的路线图中有效提取高质量路径。 其次，由于PRM被认为是服从并行实现，他们将利用高性能计算。 这将包括开发和应用C++ STL（标准模板库）的自适应并行版本，称为STAPL。使用STAPL，可以优化模拟并在各种并行和分布式系统上运行，并产生接近针对每个平台手动优化的代码的性能