CAREER: Develop a Hybrid Adaptive Particle-Field Simulation Method for Solutions of Macromolecules and a New Computational Chemistry Course for Lower-Division Undergraduates

职业：开发用于大分子解决方案的混合自适应粒子场模拟方法以及低年级本科生的新计算化学课程

• 批准号: 2337602
• 负责人: Bilin Zhuang
• 金额: $ 61.89万
• 依托单位: Harvey Mudd College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2028-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2337602&HistoricalAwards=false
• 关键词: CAREER; Develop; Hybrid; Adaptive; Particle

With support from the Chemical Theory, Models and Computational Methods (CTMC) program in the Division of Chemistry, Dr. Bilin Zhuang of Harvey Mudd College is developing a hybrid simulation method to simulate large molecules in solution. All-atom simulations have become an indispensable tool for studying interactions between molecules, but they are very costly for systems of large molecules in solution, such as polymers and protein assemblies. To enable these simulations, Dr. Zhuang and her research group will work to develop a simulation method that can greatly reduce the number of solvent molecules described with molecular detail while capturing the correct solute-solvent interactions and dynamics. This method is expected to provide a convenient and accelerated tool for simulating large molecules in solution ranging from simple ions to proteins. Achieving these goals will also involve training undergraduates and high school students in computational research and developing a new computational chemistry course for first-year undergraduate students. The new course will 1) introduce the broad usage of computation in chemistry from molecular modeling to data sciences, 2) engage students in active discovery through collaborative research-oriented projects, and 3) create introductory-level teaching resources that use computation to facilitate student learning. This is seen as filling a need as such courses are still scarce in the chemistry teaching community. The new hybrid adaptive particle-field simulation method being developed in this research is expected to make a meaningful contribution to the toolbox of available computational chemistry tools for chemists in all subdisciplines. The simulation method will exploit the equivalence between particle-based and field-based representations in statistical mechanics, allowing one to treat molecules in selected regions of space with more molecular detail (particle-like) and in other regions with fewer molecular details (field-like). The particle-like and field-like regions may adapt to the conformation of the large molecule on the fly, with no abrupt boundary between the regions. The PI has derived the partition function for the proposed method and will achieve the research objectives by implementing and validating the simulation scheme and applying the method to investigate polyelectrolyte brushes and peptide hydrogels.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在化学理论，模型和计算方法（CTMC）计划的支持下，Harvey Mudd College的Bilin Zhuang博士正在开发一种混合模拟方法，以模拟溶液中的大分子。 全原子模拟已成为研究分子之间相互作用的必不可少的工具，但是对于溶液中的大分子系统（例如聚合物和蛋白质组件）来说，它们非常昂贵。为了启用这些模拟，Zhuang博士和她的研究小组将致力于开发一种模拟方法，该方法可以大大减少用分子细节描述的溶剂分子的数量，同时捕获正确的溶质溶剂 - 溶剂 - 溶剂相互作用和动力学。预计该方法将提供一种方便且加速的工具，用于模拟从简单离子到蛋白质的溶液中的大分子。 实现这些目标还将涉及培训本科生和高中生在计算研究中，并为第一年的本科生开发新的计算化学课程。新课程将1）从分子建模到数据科学，2）通过协作研究的项目吸引学生积极发现的广泛计算用法，以及3）创建介绍性级别的教学资源，利用计算来促进学生学习。 这被认为满足了需求，因为化学教学社区仍然很少。 在这项研究中开发的新的混合自适应颗粒场模拟方法有望为所有子学科中化学家的可用计算化学工具的工具箱做出有意义的贡献。 模拟方法将利用统计力学中的基于粒子的和基于域的表示之间的等效性，从而使一个具有更分子细节（粒子样）的空间区域和其他分子细节（类似野外）的区域的分子处理。 粒子状和野外区域可能会适应大分子的构象，而区域之间没有突然的边界。 PI已为提出的方法得出了分区功能，并将通过实施和验证模拟方案并应用方法来研究多电解质刷和肽水凝胶来实现研究目标。这项奖项反映了NSF的法定任务，并通过评估该基金会的知识绩效和广泛的影响来评估NSF的法定任务，并被认为是值得的。