CAREER: Robust Molecular Computation: Error-Correcting Reaction Networks and Leakless DNA Circuits

University Of Texas At Austin, Austin TX

Investigators

Abstract

Computer science and electrical engineering have mastered electronic computation, yet there is an important domain of computation that remains poorly understood: chemical information processing. Computation due to chemical reactions is prevalent in biology - for example, every cell in our body must perform sophisticated information processing on internal and external chemical signals. Analogously, it is important to learn how to rationally engineer biochemical pathways that are capable of decision-making. Unlike silicon chips, molecular computers could operate inside cells and control their activity. Programmable chemical reactions could be useful for a range of applications in manufacturing, chemical sensing, and medicine. For example, "smart drugs" that target drug activity to disease cells and activate in response to specific molecular clues would have minimal side effects and improve therapeutic outcomes. This proposal addresses a key algorithmic challenge in chemical information processing: how to compute robustly despite the disordered and error-prone nature of the chemical environment. Mathematical models (chemical reaction networks) provide the clarity of thought to explicate universal principles of proofreading chemical algorithms, while a laboratory realization (using engineered DNA molecules) provides the necessary grounding. The success of this proposal will lead not only to new theoretical understanding but to a new generation of functional molecular devices. Specifically, this proposal will address a long-standing challenge in medical diagnostics: enzyme-free sequence-specific detection of DNA. Enzyme-free systems have the potential to be adapted to "in-the-field" operation, where sophisticated laboratory equipment is out of reach. The research program proposed is tightly coupled to educational and outreach activities. This proposal will fund the development of college courses and instructional material, which will train students in applying the proven principles of computer science and electrical engineering to the new domain of molecular computation. The primary educational goal is to encourage the next generation of scientists to break through traditional disciplinary barriers and create the scientific and engineering fields of tomorrow. Further, the project will contribute to early STEM education through gamification. The proposed work uses the formal model of chemical reaction networks to rigorously explore the principles of robust chemical computation. Chemical reaction networks formalize the computation that results from molecules interacting in a well-mixed solution obeying chemical kinetics. The work described could yield chemical algorithms for decreasing error exponentially as more molecules are involved in the computation, as well as for fast and entirely error-free computation of simple functions. Additionally, the impossibility results obtained, such as the fundamental tradeoffs between computational power and robustness, will help avoid pursuing untenable goals. Complementary to deriving general laws for the computational power of chemical kinetics, another thrust of this proposal addresses the problem of leak (spurious reactions) for a commonly used molecular primitive from DNA nanotechnology (strand displacement reactions). Leak makes it difficult to distinguish positive signal and background, which results in reduced sensitivity, as well as significantly decreased computation speed. This proposal outlines the first principled approach to proofreading in strand displacement systems that could achieve arbitrarily low levels of leak.