Binding kinetics of harmonically confined random walkers

A mean-field theory for characterizing the closing rates of DNA origami hinges

The evolution of dynamic DNA nanostructures has propelled DNA nanotechnology into a robust and versatile field, offering groundbreaking applications in nanoscale communication, drug delivery, and molecular computing. Yet, the full potential of this technology awaits further enhancement through optimization of kinetic properties governing conformational changes. In this work, we introduce a mean-field theory to characterize the kinetic behavior of a dynamic DNA origami hinge where each arm bears complementary single-stranded DNA overhangs of different lengths, which can latch the hinge at a closed conformation. This device is currently being investigated for multiple applications, being of particular interest the development of DNA-based rapid diagnostic tests for coronavirus. Drawing from classical statistical mechanics theories, we derive analytical expressions for the mean binding time of these overhangs within a constant hinge. This analysis is then extended to flexible hinges, where the angle diffuses within a predetermined energy landscape. We validate our model by comparing it with experimental measurements of the closing rates of DNA nanocalipers with different energy landscapes and overhang lengths, demonstrating excellent agreement and suggesting fast angular relaxation relative to binding. These findings offer insights that can guide the optimization of devices for specific state lifetimes. Moreover, the framework introduced here lays the groundwork for further advancements in modeling the kinetics of dynamic DNA nanostructures.

Optimizing Binding among Bimolecular Tethered Complexes

Tethered motion is ubiquitous in nature, offering controlled movement and spatial constraints to otherwise chaotic systems. The enhanced functionality and practical utility of tethers has been exploited in biotechnology, catalyzing the design of novel biosensors and molecular assembly techniques. While notable technological advances incorporating tethered motifs have been made, a theoretical gap persists within the paradigm, hindering a comprehensive understanding of tethered-based technologies. In this work, we focus on the characterization of the binding kinetics of two tethered molecules functionalized to a hard surface. Using a mean-field approximation, the binding time of such bimolecular system is determined analytically. Furthermore, estimates of the grafting site separation and polymer lengths which expedite binding are provided. These estimates, along with the analytical theories and frameworks established here, have the potential to improve efficacy in self-assembly methods in DNA nanotechnology and can be extended to more biologically specific endeavors including targeted drug-delivery and molecular sensing.

Prediction and Control in DNA Nanotechnology

DNA nanotechnology is a rapidly developing field that uses DNA as a building material for nanoscale structures. Key to the field's development has been the ability to accurately describe the behavior of DNA nanostructures using simulations and other modeling techniques. In this Review, we present various aspects of prediction and control in DNA nanotechnology, including the various scales of molecular simulation, statistical mechanics, kinetic modeling, continuum mechanics, and other prediction methods. We also address the current uses of artificial intelligence and machine learning in DNA nanotechnology. We discuss how experiments and modeling are synergistically combined to provide control over device behavior, allowing scientists to design molecular structures and dynamic devices with confidence that they will function as intended. Finally, we identify processes and scenarios where DNA nanotechnology lacks sufficient prediction ability and suggest possible solutions to these weak areas.