Self-assembly of Charged Biopolymers in Solution

Andrea Liu由理论与计算化学计划和材料理论计划共同支持，开展与DNA和F-肌动蛋白等硬性生物聚合物有关的理论研究。这些生物高聚物链在水溶液中带很高的负电荷，因此相互排斥很强。然而，当加入多价带正电荷的离子或阳离子交联蛋白时，DNA和F-肌动蛋白都可以形成复合体。这项研究考虑了广义连接体如何与带电的生物聚合物形成络合物。主要目的是阐明稀聚体的结构，并计算稀聚体、密束和孤立链之间的相平衡。此外，还将研究静止溶液和剪切溶液中的成束动力学。这些问题是由生物现象引起的，如DNA缩合和肌动蛋白细丝网络和肌动蛋白束的自组装。这个项目中的物理化学植根于统计力学，这将允许识别和探索由带电的链和连接物的最小模型所产生的现象的范围。预计该研究计划将提供一个有用的工具，用于培训研究型学生掌握数值和分析技术，并向他们介绍现代凝聚态物理化学中的生物系统和主题。众所周知，细胞内形成了由带电细丝组成的交联网络，细胞上的剪切力引起了导致新陈代谢变化的反应。这项研究将加强对这些和其他生物应用的理解，旨在开发能够解释广泛的可观察现象的简单模型，如DNA缩合。

Andrea Liu is supported jointly by the Theoretical and Computational Chemistry Program and the Materials Theory Program to carry out theoretical research pertaining to stiff biopolymers such as DNA and F-actin. These biopolymer chains are highly negatively charged in aqueous solution, and therefore repel one another strongly. However, both DNA and F-actin can form complexes when multivalent positively-charged ions or cationic crosslinking proteins are added. This research considers how generalized linkers can form complexes with charged biopolymers. The primary objective is to elucidate the structure of dilute aggregates and calculate the phase equilibrium between dilute aggregates, dense bundles, and isolated chains. In addition, the kinetics of bundle formation will be examined in both quiescent and sheared solution. These problems are motivated by biological phenomena such as DNA condensation and self-assembly of actin filament networks and bundles. The physical chemistry in this project is rooted in statistical mechanics, which will allow the identification and exploration of the range of phenomena that can result from a minimal model of charged chains and linkers. The research program is expected to provide a useful vehicle for training research students in numerical and analytical techniques, and for introducing them to biological systems and topics in modern condensed phase physical chemistry. It is known that crosslinked networks of charged filaments form inside cells, and that shearing forces on the cells cause responses that lead to metabolic changes. The understanding of these and other biological applications will be enhanced by this research, which aims to develop simple models that are able to explain a wide range of observable phenomena such as DNA condensation.