CDI-Type I: Developing Computational Models to Enable the Experimental Self-Assembly of Modified Carbon Nanotubes into Biomimetic Synthetic Cellular Vesicles

CDI-Type I：开发计算模型以实现改性碳纳米管实验性自组装成仿生合成细胞囊泡

• 批准号: 0941260
• 负责人: Steven Little
• 金额: $ 85万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-10-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0941260&HistoricalAwards=false
• 关键词: CDI; Type; Developing; Computational; Models

PI: Steven R. Little and Anna C. BalazsInstitution: University of PittsburghProposal Number: 0941260Title: Developing Computational Models to Enable the Experimental Self-Assembly of Modified Carbon Nanotubes into Biomimetic Synthetic Cellular Vesicles. Intellectual MeritCell membranes are indispensible to a vast array of complex biological functions. Notably, they serve as selectively permeable barriers, capable of regulating the entrance and exit of a broad array of essential molecules. Recent work in the laboratory of the principle investigator suggests that a specific form of elemental carbon that exhibits a cylindrical shape (called a carbon nanotube) could resemble key proteins channels in the cell membrane responsible for this function. By modifying the size of the channel and structure of the end-group, these synthetic channels could be programmed to perform a myriad of complex functions that resemble those of their biological cousins. The PIs' goal is to develop and experimentally verify computational models for the self-assembly and function of cellular-mimetic vesicles built from these synthetic channels. Mathematical modeling will increase understanding as to how choices made in the "design space" affect the experimental self-assembly process and the overall performance of the system. An iterative process of sharing data and findings will contribute not only to the creation of synthetic "cells", but also to robust computational approaches that yield structure-property relationships for a large class of newly classified macromolecules. Broader ImpactBesides providing a platform for new drug delivery strategies, the findings from this work will scientifically impact a number of communities by improving the diversity in the next generation of researchers in the fields of materials science, chemistry, polymer physics, nanotechnology, biology and bioengineering. These research activities will also provide a unique educational experience for the students involved in the project, allowing them to see how computational modeling can provide a powerful tool for scientific discovery.

PI：Steven R. Little和安娜C. Balazs机构：剑桥大学提案编号：0941260题目：开发计算模型，使改性碳纳米管的实验自组装成为仿生合成细胞囊泡。智能MeritCell膜对于大量复杂的生物功能是不可或缺的。值得注意的是，它们作为选择性渗透屏障，能够调节大量必需分子的进入和离开。主要研究者实验室的最新工作表明，一种特殊形式的圆柱形碳元素（称为碳纳米管）可能类似于细胞膜中负责这一功能的关键蛋白质通道。通过改变通道的大小和末端基团的结构，这些合成通道可以被编程来执行无数类似于它们的生物表亲的复杂功能。 PI的目标是开发和实验验证从这些合成通道构建的细胞模拟囊泡的自组装和功能的计算模型。数学建模将增加对“设计空间”中的选择如何影响实验自组装过程和系统整体性能的理解。共享数据和研究结果的迭代过程不仅有助于创建合成“细胞”，而且有助于建立强大的计算方法，为一大类新分类的大分子产生结构-性质关系。更广泛的影响除了为新的药物输送策略提供平台外，这项工作的发现还将通过提高材料科学，化学，聚合物物理，纳米技术，生物学和生物工程领域下一代研究人员的多样性来科学地影响一些社区。这些研究活动还将为参与该项目的学生提供独特的教育体验，让他们了解计算建模如何为科学发现提供强大的工具。