Molecular Information Processing

Molecular information processing is a complex and rapidly growing area ranging from nanoscale circuitry in organic materials, through nanobiophotonics (e.g. bacteriorhodopsin) to DNA computing and membrane computing. Whereas one extreme deals with finding efficient molecular devices for classical information processing, and another deals with novel paradigms for solving hard combinatorial problems, it is now clear that one main technical innovative value of molecular information processing is the fact that it is embedded (or immersed) in the molecular world. There it can mediate complex parallel and real time processes of analysis, synthesis and interprocess communication, for which the computational or interface resources via conventional computers would be prohibitive. Thus Adleman’s solution of SAT problems with DNA computers have given way to DNA self-assembly [1] and DNA mediation machines which through sequences of hybridisation reactions can process molecular signals (linking molecular events to amplification processes in programmable ways.

Very recently, Zhang et al. [2] reported such an ingenious signal-processing autocatalytic network in which the autocatalyst is a short oligonucleotide that in the course of reaction events triggers the release of itself and a prefabricated “copy” from a metastable complex as feedstock . A sequence overhang in this complex enables the binding of the autocatalyst that causes a strand displacement releasing a signal oligonucleotide (detected by a fluorescence assay). The resulting complex is still metastable and contains two molecules of the autocatalyst. Strand displacement has generated a short stretch of unpaired bases in the complex that now are in an exposed state. They cause nucleation of a longer single stranded sequence acting as a 2nd feedstock source. Nucleation is followed by another strand displacement reaction releasing the two autocatalysts. Although the implementation is currently “leaky” – viz. there is a fraction of metastable complexes undergoing a spontaneous dissociation not triggered by the autocatalyst – the underlying scheme has great potential. It overcomes the above issue of product inhibition typically observed in chemical self-replicating systems in which the autocatalytic product is longer and thus more strongly binding to the template than its precursors. Product inhibition in such systems usually limits the autocatalytic growth to stay in the parabolic regime. Exponential growth is however required for any implementation of evolutionary computation in solution. Self-replication means autocatalysis plus the generation and transfer of information [3]. Zhang’s scheme relates to a case of  “catabolic autocatalysis” encoded in genetic molecules similar to the autocatalytic cleavage of cyclic deoxyribozymogens described by Ellington [4]. As with any autonomous enzymatic reaction, ligation causes product inhibition, which is absent in cleavage (making short from long) for entropic reasons. So this approach does not provide a general solution to the problem of synthetic replication. Nonetheless, the toehold DNA manipulations utilized by Zhang [2] do provide a powerful way to manipulate molecular information, so that we intend to use them as an option in connection with reversible gelation as part of the complex electronic cell cycle.

1.  Paul W. K. Rothemund "Folding DNA to create nanoscale shapes and patterns" Nature 440, 297-302 (2006)
2. Zhang, D.Y. et al. Engineering Entropy-Driven Reactions and Networks Catalyzed by DNA. Science 31 1121 
3.  G. von Kiedrowski, "Minimal Replicator Theory I: Parabolic Versus Exponential Growth", Bioorganic Chemistry Frontiers 1993, 3, 113-146.
4.  Matthew Levy, and Andrew D. Ellington, "Exponential growth by cross-catalytic cleavage of deoxyribo¬zymo¬gens" PNAS  2003, 100, 11, 6416-6421.