NER: Geometry and Tensegrity Based Computational Modeling of Birus Assembly Pathways

项目编号：0404116机构：佛罗里达大学主要研究者：Sitharam， meer标题：NER：基于几何和张拉整体的病毒组装途径计算建模摘要：二十面体病毒壳组装是自然界中发生的纳米级自组装的一个突出的、鲜为人知的例子。大多数相同的蛋白质单体以高效率组装成一个封闭的二十面体壳；启动和终止是自发的，装配是鲁棒、快速和经济的。所有这些要求都是理想的，但在纳米尺度的自组装工程中很难实现。拟议的项目是开发和测试一个正式的、静态的模型，能够基于几何约束和张拉整体概念回答关于病毒壳组装途径的重点问题。模型的开发和测试需要并整合计算机科学、结构生物学和机械工程这三个pi的专业知识。通过仔细定义和关注感兴趣的问题，该模型将避免昂贵的动态，而且将是完全可分析和可改进的。还将开发一种易于处理且可证明准确的形式模型的计算模拟。将给出模型假设的生化和数学证明以及与其他模型的严格比较。该模型将使用两种特定病毒结构的真实数据进行验证，这些病毒含有最少数量的单体，并经过精心挑选，以测试模型的各个方面：模型的预测将使用有关病毒的已知信息和设计在项目期间完成的实验进行生化验证。

PROPOSAL NO: 0404116INSTITUTION: University of FloridaPRINCIPAL INVESTIGATOR: Sitharam , MeeraTITLE: NER: Geometry and Tensegrity Based Computational Modeling ofBirus Assembly PathwaysAbstract:Icosahedral viral shell assembly is an outstanding, poorly understood example of nanoscale self-assembly occuring in nature. Mostly identical protein monomers assemble with high rate of efficacy into a closed icosahedral shell; onset and termination are spontaneous, and assembly is robust, rapid and economical. All of these requirements are both desirable and difficult to achieve when engineering self-assembly at the nanoscale.The proposed project is to develop and test a formal, static model capable of answering focused questions about viral shell assembly pathways, based on geometric constraints and tensegrity concepts. The model development and testing crucially requires and integrates the expertise of the 3 PIs in Computer Science, Structural Biology and Mechanical Enginnering. By carefully defining and focusing on the questions of interest, the model will avoid expensive dynamics and moreover will be fully analyzable and refinable. A tractable and provably accurate computational simulation of the formal model will also be developed. Biochemical and mathematical justifications of the model assumptions and rigorous comparisons to other models will be given. The model will be validated using real data from the structure of 2 specific viruses that contain the minimal number of monomers and are carefully chosen to test various aspects of the model: the predictions of the model will be biochemically verified using known information about the viruses and experiments that are designed to be completed in the project period.