Coarse-Graining DNA Energy Landscapes for the Analysis of Hybridization Kinetics

DNA最为人所知的是生命的基因存储媒介。然而，其独特的结构性质使其在工程纳米结构和器件方面具有吸引力。值得注意的是，合成DNA系统可以通过适当设计组成DNA链的碱基(A、C、G和T)的序列，自组装成执行动态机械任务的复杂对象。当混合时，通过在互补碱基(A与T，C与G)之间形成“碱基对”，链以规定的方式“杂交”。DNA纳米技术探索和开发这些能力，用于纳米机器人、纳米制造、生物分子计算、生物传感、纳米电子学和纳米医学。从原理上讲，DNA链的平衡和动力学性质可以用其“自由能景观”的特征来表征。可能的平衡构造对应于地貌中的深谷，两种构造之间的转化率取决于分隔它们的山谷和山脊的性质。折叠DNA链的动态定义了一条有点类似于球在风景上滚动的路径。要分析具有运动部件的功能DNA系统，重要的是识别主导实验的大尺度景观特征。不幸的是，在实际问题中，现有的物理模型定义的景观具有细粒度的细节，模糊了大尺度的特征。例如，DNA系统的理论景观通常包含比宇宙中原子更多的态，尽管实验表明，少数特征主导着景观。该项目将开发有效探索无法明确列举的大型景观的算法，包括模拟物理上有意义的“宏观状态”的时间演变的粗粒化方法，而不必模拟完整的“微状态”景观。这些宏观预测将指导和解释对DNA系统的实验研究，这些实验研究对当前的纳米机器人和生物传感工作具有根本意义。定制的荧光仪器将在单分子水平上探测自由能景观。虽然我们在DNA纳米技术方面的专业知识推动了我们在合成DNA方面的实验，但新的粗粒化理论、计算算法和实验方法将同样适用于自然RNA分子的分析(例如人类端粒酶RNA的突变，它被认为通过改变构象开关的自由能景观而导致先天性角化不良)。我们的研究目标是与致力于培养本科生、研究生和博士后的教育计划相结合的，这些研究小组目前涉及应用与计算数学、应用物理、生物化学、生物工程、生物学、化学、化学工程、计算机科学、计算与神经系统和物理学。此外，还开展了一项外展计划，将当地的高中理科学生带到加州理工大学探索DNA纳米技术，以小组形式与实验室成员会面，并激发他们在科学和工程领域从事职业的热情。我们还将继续免费分发我们分析和设计软件的源代码的政策。

DNA is best known as the genetic storage medium for life. However, its unique structural properties make it attractive for engineering nanoscale structures and devices. Remarkably, synthetic DNA systems can be programmed to self-assemble into complex objects implementing dynamic mechanical tasks by appropriately designing the sequence of bases (A,C,G and T) comprising the constituent DNA strands. When mixed, the strands "hybridize" in prescribed ways by forming "base-pairs" between complementary bases (A with T, C with G). DNA nanotechnology explores and develops these capabilities for applications in nanorobotics, nanofabrication, biomolecular computation, biosensing, nanoelectronics and nanomedicine. In principle, equilibrium and kinetic properties of a DNA strand can be characterized by the features of its "free energy landscape". Likely equilibrium structures correspond to deep valleys in the landscape, and the rate of conversion between two structures depends on the nature of the valleys and ridges separating them. The dynamics of a folding DNA strand define a path somewhat analogous to a ball rolling over the landscape. To analyze functional DNA systems with moving parts, it is important to identify large-scale landscape features that dominate experiments. Unfortunately, in practical problems, existing physical models define landscapes with fine-grained detail that obscures the large-scale features. For example, DNA systems commonly have theoretical landscapes containing more states than there are atoms in the universe, though experiments suggest that a small number of features dominate the landscape. The project will develop algorithms for efficiently exploring large landscapes that cannot be enumerated explicitly, including coarse-graining approaches to simulate the temporal evolution of physically meaningful "macrostates" without having to simulate full "microstate" landscapes. These macrostate predictions will guide and interpret experimental studies of DNA systems of fundamental interest to current nanorobotics and biosensing efforts. Custom-built fluorescence instruments will probe free energy landscapes at the level of single molecules. While our expertise in DNA nanotechnology motivates our experiments on synthetic DNA, the new coarse-graining theory, computational algorithms, and experimental methods will be equally applicable to analysis of natural RNA molecules (such as the mutant of human telomerase RNA that is thought to cause dyskeratosis congenita by altering the free energy landscape of a conformational switch). Our research objectives are integral with an education program dedicated to training undergraduates, graduate students, and postdocs in distinctly interdisciplinary research groups that currently involve Applied & Computational Mathematics, Applied Physics, Biochemistry, Bioengineering, Biology, Chemistry, Chemical Engineering, Computer Science, Computation & Neural Systems, and Physics. This is coupled with an outreach program that brings local high school science students to Caltech to discover DNA nanotechnology, meet with lab members in small informal groups, and generate enthusiasm for pursuing careers in science and engineering. We will also continue our policy of freely distributing the source code for our analysis and design software.