Collaborative Research: On-the-fly free energy parameterization in molecular simulations

合作研究：分子模拟中的动态自由能参数化

• 批准号: 1207432
• 负责人: Eric Vanden-Eijnden
• 金额: $ 19.84万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1207432&HistoricalAwards=false
• 关键词: Collaborative; Research; fly; free; energy

TECHNICAL SUMMARYIn this project, funded by the Condensed Matter and Materials Theory Program, a new method is proposed for extracting free energies from molecular dynamics (MD) simulations. The method is based on temperature-acceleration, wherein free energy gradients in some desired set of collective variables are sampled in a running MD simulation while simultaneously driving those collective variables over free energy barriers that would otherwise render traditional MD hopeless at such sampling. These gradients are used as inputs into an optimization that minimizes the error associated with gradients of an analytical free energy by evolving that free energy?s parameters. The method therefore takes as input an MD system, the definitions of whatever collective variables in which one would like to know the free energy, and a functional form for that free energy, and then the method produces the optimal set of parameters. The method is formulated in a general way and is therefore expected to be applicable broadly to almost any desired collective variables. This project will be devoted to developing this method particularly for applications involving deriving effective coarse-grained potentials for multiscale simulations and to the study of conformational statistics of large biomolecules. The project will also provide training and mentoring of underrepresented students in state of the art computational and numerical methodsNON-TECHNICAL SUMMARYWhether in designing new drugs or new materials, or simply trying to understand how Nature works, computer simulations are important in understanding how matter behaves at the molecular level. Bringing such molecular-level understanding into the realm of everyday perception requires statistical approaches that are not always straightforward and often quite expensive. This project proposes a new statistical method for extracting information from molecular-level simulations. The method is potentially much more efficient than existing approaches. The research undertaken in this project will develop and apply this method to test systems relevant for biological and materials applications. The project could significantly reduce the cost associated with obtaining high-quality information from simulations at the molecular level that at the intersections of chemistry, physics, and biology. The project will also provide training and mentoring of underrepresented students in state of the art computational and numerical methods. This work is supported by the Condensed Matter and Materials Theory Program.

技术摘要该项目由凝结的物质和材料理论计划资助，提出了一种新方法，用于从分子动力学（MD）模拟中提取自由能。 该方法基于温度加速器，其中在运行的MD模拟中采样了一些所需的集体变量集中的自由能梯度，同时将这些集体变量驱动到自由能屏障上，这些变量否则会使传统的MD希望在此类采样中变得绝望。 这些梯度被用作输入中的优化，该梯度通过发展自由能的参数来最大程度地减少与分析自由能梯度相关的误差。 因此，该方法将作为输入的MD系统，即人们想知道自由能的任何集体变量的定义，以及该自由能的功能形式，然后该方法产生最佳参数集。 该方法以一般方式制定，因此有望广泛适用于几乎所有所需的集体变量。 该项目将致力于开发此方法，特别是用于涉及多尺度模拟的有效粗粒电位的应用以及大型生物分子的构象统计研究。该项目还将在最先进的计算和数值方法的情况下提供代表性不足的学生的培训和指导，其中包括设计新药或新材料，或者只是试图了解自然的工作原理，计算机模拟对于理解物质的行为在理解中的行为至关重要分子水平。 将这种分子水平的理解带入日常感知领域需要统计方法，这些方法并不总是很简单，而且通常很昂贵。 该项目提出了一种新的统计方法，用于从分子级模拟中提取信息。 该方法可能比现有方法要高得多。 该项目进行的研究将开发并应用此方法将与生物和材料应用相关的系统进行测试。 该项目可以显着降低与从化学，物理学和生物学相交的分子水平上获取模拟中获得高质量信息相关的成本。该项目还将提供以最先进的计算和数值方法的代表性学生的培训和指导。这项工作得到了凝结的物质理论计划的支持。