DNA or Molecular computing basically implies the use of DNA and biological components for computational purposes. It has been a long seen dream of bio-nanotechnologist to achieve the ultimate goal of computing utilizing DNA. In DNA computing, instead of creation of millions of proteins that bind along the DNA sequence in order to express a gene, researchers have thought of a new approach. They are using the concept of DNA pairing into computers as a mode of working.
DNA acts as a storage device already in natural biological systems. Though the utilization of its computational usages is very limited inside the cells. Some examples of computational applications of DNA include gene regulation, regulation of other metabolic processes in which DNA plays a regulatory role etc. In gene regulation, various sites like promoters, repressors and protein that are enhancing in nature are regulated by DNA in order to activate or deactivate a gene that determines the expression of a gene. During gene regulation, basically a new protein is produced for almost each new logical operation which is sort of a waste of resources since large amount of data and information is being exploited for creation of one single protein for each operation. However, the space within the DNA genome may be very large; this space is used for computation purposes viz. encoding specific proteins and providing binding sites for the recently produced proteins.
DNA has many interesting and significant properties that have remarkably contributed in development of DNA computing. Among them all, the complementary base pairing property of DNA is at the top which makes it unique. DNA strands when single, always bind to the strands that are complementary in nature to the first DNA strand. Provided there are normal conditions that are required and essential for base-pairing, a given single strand of DNA always tends to bind to its complementary sequence only; no matter if there are millions of similar sequence strands in the mixture. This unique property of DNA makes it stand out from rest of the biological macromolecules and present itself as a novel molecule to be used for computational purposes.
Another property of DNA that is remarking, is the ability of replication. The much known and accepted theory of semi conservative replication of DNA states that a DNA molecules gets separated into strands (denaturation) and then a single strand of DNA, under appropriate condition, synthesizes another strand that is complementary to it; the second strand of DNA does the same; thus creating two copies of the same DNA. Using Polymerase Chain Reaction (PCR), specific desired strands of DNA can be selected and then millions of copies of the DNA can be created.
Aldeman, in 1994, showed that DNA can be used to create a molecular computer and during his demonstration, he solved a travelling salesman's problem by it. Ehud Shapiro and his co-workers have made a DNA turing machine, a device that reads a list of data and performs operations based on the values at each point along the list. Structurally, the device consists of a DNA strand that carries the list of instructions, a fine collection of DNA strands that are used to encode the operations, and two enzymes that play a key role in performing the computation. In Aldeman's experiment, two types of single-stranded DNA, each 20 nucleotides long were selected. While on the one hand, the first type corresponds to each allowed path through a node, carrying 10 base pairs that outlines the incoming path and 10 base pairs outlining the outgoing path, on the other hand, the second type of DNA strand corresponded to each of the paths between nodes.
The application of DNA computing devices is increasing and so is advancements in this field. Satisfiable problems that attempt to perform the operation on the basis of Boolean logic are being solved on the grounds of molecular/DNA computing. DNA computing is cheap but better than the conventional computing methods as once the computational components are assembled, all of the possible solutions can be examined and as each computational component is of the size of a molecule, the computations are cheap in nature and highly cost & energy efficient. Although, it can be expected that at a further point of time in future, the problems would have been scaled larger and then manipulating large quantities of DNA will be required that could cause a problem to molecular computing.
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