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

该项目旨在开发一个新的即插即用的开源软件元素平台，以促进分子生物学中的算法研究。重点是解决计算化学家和生物物理学家在结构功能相关问题上面临的算法僵局，这些问题涉及对我们生物学至关重要的动态生物分子。这个项目产生的软件平台提供了关键的软件基础设施，以支持分子生物学和计算机科学的变革性研究，通过提高我们的建模能力，进而使我们了解生物分子在活细胞和疾病细胞中关键机制中的作用，从而造福整个社会。该项目解决了目前在生物分子建模和模拟中可以提供的长度和时间尺度上的僵局。它通过整合来自两个不同研究社区的尖端知识来做到这一点，计算化学家和生物物理学家专注于详细的基于物理的模拟，而人工智能研究人员专注于高效的搜索和优化算法。这些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，适用于受机器人运动规划启发的复杂模块化系统。软件平台的即插即用功能支持将新颖的算法组合在一起，例如将分子动力学或蒙特卡洛包装为更大的机器人启发的勘探框架内的本地搜索操作符，以及添加甚至超出本项目时间表的新兴生物分子表示、模型和搜索技术。

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.