Collaborative: SI2-SSE - A Plug-and-Play Software Platform of Robotics-Inspired Algorithms for Modeling Biomolecular Structures and Motions

协作：SI2-SSE - 用于生物分子结构和运动建模的机器人启发算法的即插即用软件平台

• 批准号: 1440581
• 负责人: Amarda Shehu
• 金额: $ 21.73万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-02-01 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1440581&HistoricalAwards=false
• 关键词: Collaborative; SI2; SSE; Plug; Play; Collaborative; SI2; SSE; Plug; Play

This project aims to develop a novel plug-and-play platform of open-source software elements to advance algorithmic research in molecular biology. The focus is on addressing the algorithmic impasse faced by computational chemists and biophysicists in structure-function related problems involving dynamic biomolecules central to our biology. The software platform resulting from this project provides the critical software infrastructure to support transformative research in molecular biology and computer science that benefits society at large by advancing our modeling capabilities and in turn our understanding of the role of biomolecules in critical mechanisms in a living and diseased cell.The project addresses the current impasse on the length and time scales that can be afforded in biomolecular modeling and simulation. It does so by integrating cutting-edge knowledge from two different research communities, computational chemists and biophysicists focused on detailed physics-based simulations, and AI researchers focused on efficient search and optimization algorithms. The software elements integrate sophisticated energetic models and molecular representations with powerful search and optimization algorithms for complex modular systems inspired from robot motion planning. The plug-and-play feature of the software platform supports putting together novel algorithms, such as wrapping Molecular Dynamics or Monte Carlo as local search operators within larger robotics-inspired exploration frameworks, and adding emerging biomolecular representations, models, and search techniques even beyond the timeline of this project.

该项目旨在开发一个新型的开放式软件元素插件平台，以推动分子生物学中的算法研究。重点是解决结构功能与生物学中心的动态生物分子相关的相关问题中计算化学家和生物物理学家面临的算法僵局。该项目产生的软件平台提供了关键的软件基础架构，以支持分子生物学和计算机科学方面的变革性研究，从而通过提高我们的建模能力，并理解我们对生物分子在生命机制中的作用和疾病中的关键机制中的作用，从而使社会的最新型号和时间尺度上的时间缩放为生物尺度，从而使生物尺度上的型号和仿真型号。通过整合来自两个不同研究社区的尖端知识，计算化学家和生物物理学家的尖端知识，重点是基于物理学的模拟，而AI研究人员则专注于有效的搜索和优化算法。软件元素将复杂的能量模型和分子表示与强大的搜索和优化算法相结合，用于从机器人运动计划中启发的复杂模块化系统。软件平台的插件功能支持将新颖的算法汇总在一起，例如包装分子动力学或蒙特卡洛作为较大机器人技术启发的探索框架中的本地搜索操作员，并添加新兴的生物分子表示，模型和搜索技术甚至超出了该项目的时间表。