… a fantasy of nanoscale circuit fabrication in a future technology. Imagine a family of primitive molecular-electronic components, such as conductors, diodes, and switches, is available from generic parts suppliers. Perhaps we have bottles of these common components in the freezer…. Suppose we have a circuit to implement. The first stage of the construction begins with the circuit and builds a layout incorporating the sizes of the components and the ways they might interact. Next, the layout is analyzed to determine how to construct a scaffold. Each branch is compiled into a collagen strut that links only to its selected targets. The struts are labeled so that they bind only to the appropriate electrical component molecules. For each strut, the DNA sequence to make that kind of strut is assembled, and a protocol is produced to insert the DNA into an appropriate cell. These various custom parts are then synthesized by the transformed cells.
Finally, we create an appropriate mixture of these custom scaffold parts and generic electrical parts. Specially programmed worker cells are added to the mixture to implement the circuit edifice we want. The worker cells have complex programs, developed through amorphous computing technology. The programs control how the workers perform their particular task of assembling the appropriate components in the appropriate patterns. With a bit of sugar (to pay for their labor), the workers construct copies of our circuit we then collect, test, and package for use.
SOURCE: H. Abelson, R. Weiss, D. Allen, D. Coore, C. Hanson, G. Homsy, T.F. Knight, Jr., et al., “Amorphous Computing,” Communications of the ACM 43(5):74-82, 2000.
This approach has two main drawbacks: the speed of individual assemblies, and the error rate. First, the DNA reactions can take minutes or hours, and so any individual computation by self-assembly will likely be substantially slower than using a traditional computer. The potential for self-assembly is that, like exhaustive DNA computation, it can occur in parallel, with a parallelism factor as high as 1018. In the XOR experiment, researchers observed an error rate of 2 to 5 percent. Certainly, this rate may be lowered as experience is gained in designing laboratory procedures and assembly methods; however, the error rate is likely to remain higher than that for electronic computers. For certain classes of problems, an ultraparallel though unreliable approach may be an effective way to compute a solution.
So far, DNA self-assembly has been demonstrated successfully in the laboratory, constructing relatively simple patterns (e.g., alternating bands, or the encoding of a binary string) that are visible through microscopy. It has also been used successfully for simple computations such as counting, XOR, and addition.
Moving forward, laboratory techniques must improve in sophistication to handle the more complex assemblies and reactions that will accompany large-scale computations or designs. Along with progress in the lab, further theoretical developments are possible in developing algorithms for constructing arbitrary aperiodic patterns.
Although so far DNA self-assembly has used only naturally occurring variants of DNA, a possible improvement is to employ alternative chemistries, such as peptide nucleic acid, an artificial form of DNA in which the backbone has peptide links in place of the phosphate that occurs in natural DNA.