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Coarse-Graining of Complex Liquids: Structure and Dynamics

复杂液体的粗粒化：结构和动力学

基本信息

批准号：
1362500
负责人：
Marina Guenza
金额：
$ 29.2万
依托单位：
University of Oregon Eugene
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2014
资助国家：
美国
起止时间：
2014-07-15 至 2019-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1362500&HistoricalAwards=false
关键词：
Coarse Graining Complex Liquids Structure

项目摘要

Marina Guenza at the University of Oregon Eugene is supported by an award from the Chemical Theory, Models and Computational Methods program focusing on understanding the relation between molecular structure and macroscopic properties of synthetic polymeric materials and large biological molecules. Computer simulations are useful to provide information about the microscopic molecular structure of a liquid, but describing the macroscopic properties that are measured experimentally exceeds the computational capabilities of traditional simulations. New computational strategies are being developed here to accelerate simulations and connect the molecular structure to the macroscopic properties for different temperatures and other thermodynamic conditions. This provides an important tool to study the properties of novel materials and biological molecules such as proteins, DNAs, and RNAs.This project uses a coarse-graining theory with the desirable property that structural and thermodynamic consistency are maintained throughout coarse-graining. Novel applications include the search for macromolecular structures that self-assmble in a soft crystal lattice of desired geometry. An original approach is used for the coarse-grained dynamics of biological macromolecules, specifically protein, DNA, and RNA, that is based on the Langevin equation for the dynamics of macromolecules in solution. This method also accounts for the presence of local conformational barriers and for internal hydrophobic regions. Theoretical predictions are compared to experimental data from collaborators at the University of Oregon.

俄勒冈大学尤金分校的玛丽娜·古扎获得了化学理论、模型和计算方法项目颁发的奖项的支持，该奖项的重点是了解合成聚合物材料和生物大分子的分子结构和宏观性质之间的关系。计算机模拟有助于提供有关液体微观分子结构的信息，但描述实验测量的宏观性质超出了传统模拟的计算能力。这里正在开发新的计算策略来加速模拟，并将分子结构与不同温度和其他热力学条件下的宏观性质联系起来。这为研究蛋白质、DNA和RNA等新型材料和生物分子的性质提供了重要工具。该项目使用了粗粒化理论，该理论具有在整个粗粒化过程中保持结构和热力学一致性的理想特性。新的应用包括寻找在所需几何形状的软晶格中自组装的大分子结构。一种新颖的方法被用于生物大分子的粗粒度动力学，特别是蛋白质、DNA和RNA，该方法基于溶液中大分子动力学的朗之万方程。这种方法还解释了局部构象势垒的存在和内部疏水性区域的存在。理论预测与俄勒冈大学合作者的实验数据进行了比较。