Name: Andrew Phillips 2009-11-21 18:34
Recently, a range of information-processing circuits have been implemented in DNA by using strand displacement as their main computational mechanism. Examples include digital logic circuits and catalytic signal amplification circuits that function as efficient molecular detectors. As new paradigms for DNA computation emerge, the development of corresponding languages and tools for these paradigms will help to facilitate the design of DNA circuits and their automatic compilation to nucleotide sequences. We present a programming language for designing and simulating DNA circuits in which strand displacement is the main computational mechanism. The language includes basic elements of sequence domains, toeholds and branch migration, and assumes that strands do not possess any secondary structure. The language is used to model and simulate a variety of circuits, including an entropy-driven catalytic gate, a simple gate motif for synthesizing large-scale circuits and a scheme for implementing an arbitrary system of chemical reactions. The language is a first step towards the design of modelling and simulation tools for DNA strand displacement, which complements the emergence of novel implementation strategies for DNA computing.
1. Introduction
Nucleic acids have a number of desirable properties for engineering artificial biochemical circuits. Their sequences can be precisely controlled in order to encode distinct signals while avoiding cross-talk between molecules, and Watson–Crick base pairing can be used to engineer interactions between specific molecules at well-defined rates. Previous efforts in designing biochemical circuits with DNA have tended to make use of additional restriction enzymes (Benenson et al. 2001, 2003), or structural features such as hairpins within the molecules to perform computation (Sakamoto et al. 2000; Benenson et al. 2004; Yin et al. 2008). While this allows the implementation of somewhat ingenious molecular devices (Yurke et al. 2000; Venkataraman et al. 2007), simpler designs have recently been proposed for the construction of large-scale, modular circuits. In particular, a range of information-processing circuits have recently been implemented in DNA by using strand displacement as the main chemical process to perform computation. Examples include various digital logic circuits (Seelig et al. 2006) together with catalytic signal amplification circuits that function as efficient molecular detectors (Zhang et al. 2007). The use of DNA strand displacement to perform computation enables the construction of simple, fast, modular composable and robust circuits, as demonstrated in Zhang et al. (2007).
1. Introduction
Nucleic acids have a number of desirable properties for engineering artificial biochemical circuits. Their sequences can be precisely controlled in order to encode distinct signals while avoiding cross-talk between molecules, and Watson–Crick base pairing can be used to engineer interactions between specific molecules at well-defined rates. Previous efforts in designing biochemical circuits with DNA have tended to make use of additional restriction enzymes (Benenson et al. 2001, 2003), or structural features such as hairpins within the molecules to perform computation (Sakamoto et al. 2000; Benenson et al. 2004; Yin et al. 2008). While this allows the implementation of somewhat ingenious molecular devices (Yurke et al. 2000; Venkataraman et al. 2007), simpler designs have recently been proposed for the construction of large-scale, modular circuits. In particular, a range of information-processing circuits have recently been implemented in DNA by using strand displacement as the main chemical process to perform computation. Examples include various digital logic circuits (Seelig et al. 2006) together with catalytic signal amplification circuits that function as efficient molecular detectors (Zhang et al. 2007). The use of DNA strand displacement to perform computation enables the construction of simple, fast, modular composable and robust circuits, as demonstrated in Zhang et al. (2007).