Quantcast


CURATOR
A pinboard by
Abhishek Behera

Ph.D. Student, Indian Institute of Technology, Bombay

PINBOARD SUMMARY

Design novel molecular systems capable of performing intelligent tasks

We aim to discover algorithms at the molecular level, that enables living systems to exhibit sophisticated behavior. For example we hope to explain how an artificial cell might carry out complex tasks such as inferring it environment and deciding appropriate action with a soup of chemicals as it only computational resource. We also hope to explore the technological reach of these ideas and find novel applications through the design of smart system of molecules that would do useful in-vivo operations. So far we have designed chemical systems that can solve in-silico, classification tasks such as handwritten digit recognition and inference tasks such as computing the posterior given partial observations. Building a physically realizable chemical reaction system is beset with several technological challenges. While we try to design systems that would operate under these technological constraints, we are also working towards identifying and expanding the class of reaction systems that would be physically realizable. We also hope to make fundamental contributions to machine learning. In particular we hope that chemical reaction networks would prove to be a successful alternative to existing models for machine learning and that some of our in-silico implementations of molecular algorithms would give rise to previously unknown machine learning algorithms.

4 ITEMS PINNED

On the biophysics and kinetics of toehold-mediated DNA strand displacement.

Abstract: Dynamic DNA nanotechnology often uses toehold-mediated strand displacement for controlling reaction kinetics. Although the dependence of strand displacement kinetics on toehold length has been experimentally characterized and phenomenologically modeled, detailed biophysical understanding has remained elusive. Here, we study strand displacement at multiple levels of detail, using an intuitive model of a random walk on a 1D energy landscape, a secondary structure kinetics model with single base-pair steps and a coarse-grained molecular model that incorporates 3D geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Two factors explain the dependence of strand displacement kinetics on toehold length: (i) the physical process by which a single step of branch migration occurs is significantly slower than the fraying of a single base pair and (ii) initiating branch migration incurs a thermodynamic penalty, not captured by state-of-the-art nearest neighbor models of DNA, due to the additional overhang it engenders at the junction. Our findings are consistent with previously measured or inferred rates for hybridization, fraying and branch migration, and they provide a biophysical explanation of strand displacement kinetics. Our work paves the way for accurate modeling of strand displacement cascades, which would facilitate the simulation and construction of more complex molecular systems.

Pub.: 11 Sep '13, Pinned: 30 Jul '17