This document discusses DNA computing, which uses DNA, biochemistry and molecular biology to perform parallel computations. DNA computing can solve complex problems quickly using massive parallelism. It has several advantages over traditional computing like low energy usage and efficient storage. Common methods for DNA computing involve using DNA logic gates analogous to silicon gates. DNAzymes and enzymes are also used to build logic circuits. Challenges include error rates, size restrictions, and developing a universal representation method. Potential applications are in medicine, with future uses in encryption and genetic programming.

1. DNA Computing
Malvi Prakash Golwala
12/01/2016

2. Introduction
• Form of computing which uses DNA, biochemistry and molecular
biology
• Similar to parallel computing; uses different DNA molecules to try
many different possibilities at once
• Lower energy consumption; uses ATP to allow litigation/heat the
strand for disassociation

3. Introduction
• Does not provide capabilities to study computationally solvable
problems using different models
• Overlaps with DNA nanotechnology which uses the specificity of
Watson-Crick base pairing and other DNA properties to make novel
structures out of DNA
• Can be done without the use of structures created by DNA
nanotechnology

4. History
1994: Leonard
Adelman
2002: Weizmann
Institute of
Science, Israel
2004: Ehud
Shapiro

5. Methods
• Most DNA computers are built with basic logic gates: AND, OR, NOT
associated with digital logic from a DNA basis
• DNA bases include DNA enzymes, deoxynucleotides, enzymes, DNA
tiling and PCR

6. DNAzymes
• They are used to build logic gates analogous to silicon logic gates
• Catalytic DNA catalyze reactions upon interaction with an appropriate
input like a matching oligonucleotide
• DNAzyme changes its conformation when it binds to a matching
oligonucleotide and the fluorogenic substrate bound to it gets cleaved
off
• Commonly used DNAzymes are E6 and 8-17 because they allow
cleaving of a substrate in any arbitrary location

7. Enzymes
• Usually like a simple Turing machine: analogous hardware in the form
of an enzyme, software, DNA
• Parallel Computing:
• Large problems divided into small ones which are solved simultaneously
• Bit-level, instruction-level, data, task parallelism

8. Advantages
• Parallel computing
• Incredibly light weight
• Low power
• Solves complex problems quickly
• Generate a set of potential solutions
• Efficient handling of massive amounts of storage and working
memory
• Cheap, clean, readily available materials

9. Shape Design:Robinson and Kallenbach methods
• Forked replicative intermediates or four-stranded
recombinational structures of the type proposed
by Holliday in 1964 as nucleic acid junctions,
i.e., structures in which three or more
double helices emanate from a single
point
• A set of rules have been formulated
(by Robinson, Kallenback and Seeman) to
minimize sequence symmetry and to ensure
stability of junction structures

10. Principles of Designing DNA Shapes
• Watson-Crick Pairing:
• A::T, G:::C
• A fourth rank junction composed of
four hexadecameric fragments
• This fragment has four arms each,
designated as being composed of
eight base pairs

11. Principles of Designing DNA Shapes Contd…
• Robin Holliday Model/Holliday Junction
• After Robin Holliday, 1964
• Mobile junction between four strands of DNA
• Can slide up and down due to this feature
• Based on a particular type of genetic exchange in yeast known as
homologous recombination

12. Principles of Designing DNA Shapes Contd…
• Robin Holliday Model
• Single-stranded breaks occur at
the same point, one strand of
each parental DNA
• Free ends of each broken strand
then migrates to the other DNA
helix, where the invading strand
is joined to the free ends they
encounter

13. Applications
• DNA Cube
• Considered most important
• Shows 6 different cyclic strands; strands are linked to each other twice on
every edge; it’s a hexa-catenane
• Every edge contains 20 nucleotide pair of DNA; length 68A
• Each edge has a cleavage site for restriction endonuclease; used to establish
validity of synthesis

14. Applications Contd…
• DNA Cube
• Two ends of two quadrilaterals were
ligated to form a belt-like molecule
• This will be needed to get denatured
and reconstituted to purify from side
products
• The belt like molecule was then
cyclized to form the cube-like molecule

15. DNA Cube Formation

17. Applications – Other shapes and functions
• Double-Crossover molecules (DX)
• Consists of two double helices interlocked by exchange of oligonucleotide
strands at two separate crossover points
• DX complexes have four termini one at each end of the two strands
• Five varieties (DAO, DAE, DPE, DPOW and DPON) that differ from one another
in the geometry of the strand exchange and the topology of the strand paths
through the tile

18. Applications – Other shapes and functions
• Double-Crossover molecules (DX)
• Shapes possible: parallel (DPE, DPOW, DPON) and antiparallel (DAE, DAO)
• Further differentiated w.r.t the number of double helical half turns between
their crossover points
• Even: DPE, DAE
• Odd: DAO, DPOW, DPON
• DPOW and DPON molecules differ by having the extra-half turn that
corresponds to a major or minor groove spacing

19. Applications – Other shapes and functions
• Double-Crossover molecules (DX)

20. Applications – Other shapes and functions
• Crossing Over forming Triple Helix
• Triple helix with anti-parallel crossover and odd or even helical half turns
• Classified into:
• TAO: anti-parallel triple helix with odd number of helical turns
• TAE: anti-parallel triple helix with even number of helical turns
• TAO forms by annealing of four DNA single strands and it has four sticky ends
at four corners
• TAE tile has 6 sticky ends formed by six strands, three on the left and three on
the right

21. Applications – Other shapes and functions
• Six TAE tiles joined diagonally

22. Electrical Analogies for Biological Circuits
• Electronic and biological circuits (DNA, proteins), both have
components, connectors and power supplies
• Even if DNA sequence of a gene is identified, it cannot be transcribed
without appropriate promoter. Even if the promoter is available,
introns DNA patterns may modulate transcription, producing an
alternatively splice mRNA and therefore different proteins
• The functional value of these biomolecules are subject to change in a
variety of factors. The study of this is DNA computing

23. Scope and Future Trends
• A DNA computer is made up of specific DNA strands. The select
combination of DNA strands essentially solves a problem
• DNA itself operates as a building block.
• They can be tiny enough to be inside human body where they can
perform tasks such as identifying diseased cells or releasing insulin as
required for diabetic patient
• In medicine: Currently, in development is a DNA computer that
actually operates within human cells

24. Scope and Future Trends Contd…
Using a mechanism known as RNA interference, little molecules of RNA
stop a gene from creating a protein
The hope is that this technology will eventually allow for DNA
computer to select diseased cells and then exclusively treat diseased
cells while leaving healthy cells intact

25. Challenges
• To produce a DNA computer that can actually handle complex and
decision making processes
• Making of DNA in a way that it can provide the same success at
solving problems as current silicon based systems
• DNA’s nano-sized particles make this difficult challenge to overcome
• Time consuming laboratory procedures
• No universal method of representation

26. Challenges
• Error restrictions
• Size restrictions
• Reliability: due to errors in pairing of DNA strands
• Different problems need different approaches
• Requires human assistance
• DNA in vitro decays through tie, so lab procedures can not take long
• No efficient implementation has been produced for testing,
verification and general experimentation

27. Future of DNA Computing
• Algorithm used by Adelman for travelling salesman was simple. As
technology becomes more refined, more efficient, new and more
complex algorithms may be discovered
• DNA computers are unlikely to feature word processing, emailing and
solitaire programs
• But, they will be very powerful tools for areas of encryption, genetic
programming, language systems and algorithms or by airlines waiting to map
more efficient routes