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.

在化学系化学理论、模型和计算方法（CTMC）项目的支持下，哈维穆德学院的 Bilin Zhuang 博士正在开发一种混合模拟方法来模拟溶液中的大分子。 全原子模拟已成为研究分子间相互作用不可或缺的工具，但对于溶液中的大分子系统（例如聚合物和蛋白质组装体）而言，它们的成本非常高。为了实现这些模拟，庄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-溶剂相互作用和动力学。该方法有望提供一种方便且加速的工具，用于模拟溶液中从简单离子到蛋白质的大分子。 实现这些目标还包括对本科生和高中生进行计算研究培训，并为一年级本科生开发新的计算化学课程。新课程将 1) 介绍计算在从分子建模到数据科学的化学领域的广泛应用，2) 通过合作研究型项目让学生积极发现，3) 创建入门级教学资源，利用计算来促进学生的学习学习。 这被认为满足了需求，因为此类课程在化学教学界仍然稀缺。 本研究中开发的新型混合自适应粒子场模拟方法预计将为所有分支学科的化学家的可用计算化学工具箱做出有意义的贡献。 该模拟方法将利用统计力学中基于粒子和基于场的表示之间的等效性，允许人们以更多的分子细节（类粒子）处理选定的空间区域中的分子，以及在具有更少的分子细节（场-场）的其他区域中处理分子。喜欢）。 粒子状和场状区域可以适应飞行中大分子的构象，区域之间没有突然的边界。 PI 导出了所提出方法的配分函数，并将通过实施和验证模拟方案以及应用该方法研究聚电解质刷和肽水凝胶来实现研究目标。该奖项反映了 NSF 的法定使命，并被认为值得通过以下方式支持：使用基金会的智力价值和更广泛的影响审查标准进行评估。