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

California Institute Of Technology, Pasadena CA

Investigators

Abstract

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.