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DNA molecules can be used to process information, using a bonding process between DNA pairs known as hybridisation. Called molecular programming , this approach applies concepts and designs customary to computing to nano-scale approaches appropriate for working with DNA. This was first achieved by Bernard Yurke and colleagues in , who created from DNA strands a pair of tweezers that opened and pinched.

One possible application is that such a nano-robot DNA walker could progress along tracks making decisions and signal when reaching the end of the track, indicating computation has finished. Just as electronic circuits are printed onto circuit boards, DNA molecules could be used to print similar tracks arranged into logical decision trees on a DNA tile, with enzymes used to control the decision branching along the tree, causing the walker to take one track or another.

DNA walkers can also carry molecular cargo, and so could be used to deliver drugs inside the body.

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DNA is also versatile, cheap and easy to synthesise, and computing with DNA requires much less energy than electric powered silicon processors. Its drawback is speed: it currently takes several hours to compute the square root of a four digit number, something that a traditional computer could compute in a hundredth of a second. Another drawback is that DNA circuits are single-use, and need to be recreated to run the same computation again.

Organic Computing (Publikation bei kassel university press)

Perhaps the greatest advantage of DNA over electronic circuits is that it can interact with its biochemical environment. Computing with molecules involves recognising the presence or absence of certain molecules, and so a natural application of DNA computing is to bring such programmability into the realm of environmental biosensing, or delivering medicines and therapies inside living organisms. DNA programs have already been put to medical uses, such as diagnosing tuberculosis. However, more effort is required before we can inject smart drugs directly into living organisms.

Taken broadly, DNA computation has enormous future potential.


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Its huge storage capacity, low energy cost, ease of manufacturing that exploits the power of self-assembly and its easy affinity with the natural world are an entry to nanoscale computing, possibly through designs that incorporate both molecular and electronic components. However, more effort is required before we can inject smart drugs directly into living organisms.

Taken broadly, DNA computation has enormous future potential. Its huge storage capacity, low energy cost, ease of manufacturing that exploits the power of self-assembly and its easy affinity with the natural world are an entry to nanoscale computing, possibly through designs that incorporate both molecular and electronic components.


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Since its inception, the technology has progressed at great speed, delivering point-of-care diagnostics and proof-of-concept smart drugs — those that can make diagnostic decisions about the type of therapy to deliver. There are many challenges, of course, that need to be addressed so that the technology can move forward from the proof-of-concept to real smart drugs: the reliability of the DNA walkers, the robustness of DNA self-assembly, and improving drug delivery.

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But a century of traditional computer science research is well placed to contribute to developing DNA computing through new programming languages, abstractions, and formal verification techniques — techniques that have already revolutionised silicon circuit design, and can help launch organic computing down the same path. Image credit: Shutterstock. This article was originally published on The Conversation.

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