DMS/NIGMS 1: Topological Dynamics Models of Protein Function

现在人们普遍认为，结构化的支配动力学调节功能，但我们仍然不知道如何 很少的改变（例如，突变）改变动态以改变功能。理解这种相互作用是 一个关键的一步，工程蛋白质与所需的功能，以解决疾病，和病毒的演变，以打击 地方病或未来的流行病，以及许多其他生物工程应用。尽管许多人的工作 然而，研究人员发现，序列、结构和动力学之间的联系仍然难以捉摸。这部分是 因为没有有效的方法可以精确地量化每个氨基酸位置的贡献 to structure结构and dynamics动态.我们建议通过使用创新的跨学科方法来填补这一空白， 基于数学拓扑学和物理学的蛋白质动力学建模。指导性假设是， 蛋白质的拓扑景观支配着构象动力学，它可以被位点修饰，特定的突变为了验证这一假设，我们将创建一个数学框架， 蛋白质的全局拓扑结构和构象动力学可以严格关联， 可以被量化。这项工作特别及时，原因有二：（1） 构象动力学已经建立了结构和功能之间的联系， 蛋白质组规模和（2）数学拓扑学的方法已经显示出能够 表征蛋白质结构。 这项研究推进了数学和生物学的知识，并打破了现有的障碍：（1）拓扑学 （2）蛋白质结构的定量表征，（3）将微观效应与 蛋白质的宏观性质和（4）提供一个新的框架，不仅能够揭示 蛋白质功能和进化的分子机制，基于基本的数学和物理 概念，而且还能够设计具有所需功能的新型蛋白质。这是通过（1）创建 拓扑复杂性的新措施和数学拓扑框架表征多规模蛋白质结构，通过（2）粗粒度建模和蛋白质的动态分析，以及（3）通过 将两者结合起来，建立构象动力学和拓扑结构之间的联系， 蛋白质景观这种整合的新框架将在不同的蛋白质系统上进行测试， 现有的深度扫描突变实验数据。这项工作的顺利完成可能会导致 这是一个突破，可以根据结构动力学预测和调节蛋白质功能。

It is now well accepted that structured governed dynamics modulate function, yet we still don’t know how a few changes (e.g., mutations) in sequence modify dynamics to alter function. Understanding this interplay is a key step to engineering proteins with desired function to address disease, and viral evolution to fight with endemics or future pandemics, as well as many other bioengineering applications. Despite the work of many researchers, the connection between sequence, structure and dynamics remains elusive. This is partly because there is no powerful methods that can accurately quantify each amino-acid position’s contribution to structure and dynamics. We propose to fill this gap by using an innovative, interdisciplinary method based on mathematical topology and physics based protein dynamics modeling. The guiding hypothesis is that the topological landscape of proteins governs conformational dynamics and that it can be modified with sitespecific mutations. To test this hypothesis, we will create the mathematical framework upon which the local and global topology of proteins and conformational dynamics can be rigorously associated and the evolution of the topological landscape can be quantified. This work is particularly timely for two reasons: (1) conformational dynamics have established a connection between structure and function and evolution at the proteotome scale and (2) methods from mathematical topology have shown evidence of being able to characterize protein structure. This research advances knowledge in mathematics and biology and breaks existing barriers in: (1) topology and geometry, (2) quantitative characterizations of protein structure, (3) connecting microscopic effects to the macroscopic properties of proteins and (4) providing a novel framework that enables not only to uncover the molecular mechanism of protein function and evolution based on fundamental mathematical and physical concepts, but also enables to design novel proteins with desired function. This is achieved by (1) creating novel measures of topological complexity and a mathematical topological framework for characterizing multiscale protein structure, by (2) coarse-grained modeling and dynamical analysis of proteins and (3) by combining the two to establish the connection between conformational dynamics and the topological landscape of proteins. This integrated novel framework will be tested on different protein systems with available deep scanning mutational experimental data. The successful completion of this work could lead to a breakthrough that would enable to predict and modulate protein function based on structural dynamics.