DNA based computer : present & future

CREDIT SEMINAR
DNA BASED COMPUTER : PRESENT STATUS
AND FUTURE PROSPECTS
PRESENTED BY,
KINJAL MONDAL
(A-2017-30-006)
DEPARTMENT OF
AGRICULTURAL BIOTECHNOLOGY

CONTENTS
1. INTRODUCTION
2. BASICS OF DNA
3. PRINCIPLES OF DNA COMPUTING
4. BASIC OPERATIONS ON DNA FOR COMPUTATION
5. INFORMATION STORAGE AND PROCESSING CAPABILITIES
6. EFFICIENCY
7. COMPARISON AMONG DNA AND CONVENTIONAL ELECTRONIC COMPUTERS
8. PRESENT STATUS OF DNA COMPUTER
9. FUTURE PROSPECTS OF DNA COMPUTER
10. ADVANTAGES AND DISADVANTAGES OF DNA COMPUTER
11. CONCLUSION
12. REFERENCES

1. INTRODUCTION
DNA computing also known as molecular
computing is a new approach to massively parallel computation
based on groundbreaking work by Adleman.
A DNA computer is basically a collection of
specially selected DNA strands whose combinations will employ
bio-molecular manipulation to solve computational problems, at
the same time exploring natural processes as computational
models.

1.1 HISTORY OF EVOLUTION OF DNA COMPUTING
 In 1994, Leonard Adleman at the Laboratory of Molecular Science solved a class of
intractable computational problems in which the computing time can grow
exponentially with problem size (Non-deterministic Polynomial time complete
problems).
 In 1995, Boneh et. al published paper on cracking DES using molecular computer.
 In 1997, Rochester U. team developed logic gates using DNA.

I believe things like DNA computing will
eventually lead the way to a “molecular revolution,”
which ultimately will have a very dramatic effect on the world.
L. Adleman
Leonard Adleman in 1994 solved the travelling salesman problem (TSP) also known as the ``
Hamiltonian Path`` problem.

Nevertheless, his work is significant for the concept of DNA computer as,
I. It illustrates the possibilities of using DNA to solve a class of problems that is
difficult to solve using traditional computing methods
II. It`s an example of molecular computation with a potential size limit, that
may never be reached by the semi-conductor systems
III. It demonstrates that computing with DNA can work in a massively parallel
fashion

1.2 MOTIVATION FOR DNA COMPUTING
 DNA computing is of twofold: one is theoretical and the other is practical.
 Starting from observing the structure and dynamics of DNA, the theoretical research
began to propose formal models of DNA computers for performing theoretical
operations.
 The practical side of DNA computing has progressed at a much slower rate, mainly due
to the fact that the laboratory work is very time consuming and includes several
constraints.

 DNA computing is an interdisciplinary field where biologists, computer scientists,
mathematicians, chemists etc. find a lot of interesting problems which can be applied
to both the theoretical and practical areas of DNA computing.
 The information density of DNA is much greater than that of silicon: 1 bit can be stored
in approximately one cubic nanometer. Other storage media, such as videotapes can
store 1 bit in 1012 cubic nanometer.
 In principle, there could be billions upon trillions of DNA molecules undergoing
chemical reactions for performing computations simultaneously.

1.3 APPLICATIONS OF DNA COMPUTING
 Applications making use of ``classic`` DNA computing schemes where the use of massive parallelism holds
an advantage over traditional computing schemes, including potential polynomial time solutions to hard
computational problems.
 Applications making use of the ``natural`` capabilities of DNA, including those that make use of
informational storage abilities and those that interact with existing and emerging biotechnology.
 Contributions to fundamental research within both computer science and the physical sciences, especially
concerning exploring the limitations of computability and to understanding and manipulating bimolecular
chemistry.
 Classical DNA computing techniques have already been theoretically applied to a real life problem:
breaking the Data Encryption Standard (DES). Although this problem has already been solved using
conventional techniques in a much shorter time than proposed by the DNA methods, the DNA models are
much more flexible, potent, and cost effective.

• DNA chips
• Genetic programming
• Pharmaceutical applications
• Cracking of coded messages
• DNA fingerprinting

2. BASICS OF DNA
2.1 FUNDAMENTAL CHARACTERISTICS OF DNA
 DNA (deoxyribonucleic acid) is a helical and anti-parallel double stranded sequence of 4
nucleotides.
 Each nucleotide consists of a pentose sugar (2-deoxyribose), a phosphate group (-PO4) and a
nitrogen containing base among the 4 bases : Adenine (A), Guanine (G), Thymine (T) and
Cytosine (C).
 Individual nucleotides are connected by phosphodiester bonds to form polynucleotides.
 According to the principle of Watson-Crick complementarity, nucleotides A are bound with a
hydrogen bridge to the T on the other thread and similarly, C bind themselves to G. This
principle allows for DNA replication and for limited possibilities of repairing the genetic
information when one threads gets damaged.
 Each DNA strand has 2 different ends that determine its polarity : the 3`-end and the 5`-end.

DNA based computer : present & future

2.2UNIQUENESS OF DNA COMPUTER
 DNA with its unique data structure, and ability to perform many parallel operations allows to
look at a computational problem from a different point of view.
 Although transistor based multi-processor computers and modern CPUs incorporate some
parallel processing, but in general, in the basic Von Neumann Architecture computers,
instructions are managed sequentially.
 A Von Neumann machine, which is what all modern CPUs are basically repeat the same `` Fetch
and Execute Cycle`` over and over again.
 A DNA computer fetches an instruction for the appropriate data in the main memory and
executes the instruction really fast.

 DNA computers, however are non-Von Neumann, stochastic machines that approach computation in a
different way from ordinary computers for the purpose of solving a different class of problems.
 DNA computers work biochemically to solve complex problems using dynamic programming
algorithms in parallel fashion. The power comes from the memory capacity and parallel processing.
 DNA computations may use a billion times less energy than an electronic computer while storing data
in a trillion times less space.
 The data density of DNA is impressive. A strand of DNA is encoded with four bases, i.e., A, T, C, and G
and they are spaced every 0.35 nanometers along the DNA molecule, giving DNA a remarkable data
density of nearly 18 Mbits per inch. In two dimensions, if we assume one base per square nanometer,
the data density is over one million Gbits per square inch that is about 7 Gbits per square inch in a
typical high performance hard drive.

3. PRINCIPLES OF DNA COMPUTING
 A programme on a DNA computer is executed as a series of synthesizing, extracting,
modifying and cloning the DNA strands.
 Instead of using electrical impulses to represent bits of information, the DNA
computer uses the chemical properties of DNA molecules by examining the patterns
of combination or growth of the molecules or strings.
 DNA can do this through the manufacture of enzymes, which are biological catalysts
that could be called the ``software``, used to execute the desired calculation.
 Enzymes do not function sequentially, working on one DNA at a time. Rather, many
copies of the enzyme can work on many DNA molecules simultaneously in a massively
parallel fashion.

 DNA computers work by encoding the problem to be solved in the language of DNA:
the base-four number system, consisting the base-four values A, T, C and G which is
more than enough considering that an electronic computer needs only two digits, i.e.
0 & 1 for the same purpose.
 Just like a CPU has a basic suite of operations like addition, bit-shifting, logical
operators (AND, OR, NOT, NOR) etc. that allow it to perform even the most complex
calculations, DNA has cutting, copying, pasting, repairing, and many others.
 In a DNA computer, computation takes place in test tubes or on a glass slide coated in
24K gold and the correct sequences are filtered out using the genetic engineering
tools.

4. BASIC OPERATIONS ON DNA FOR COMPUTATION
As concerning the operations that can be performed on DNA
strands, the proposed models of DNA computation are based on various
combinations of the following primitive bio-operations :
• Synthesizing : a desired polynomial-length strand used
in all models.
• Mixing : combine the contents of two test tubes into a
third one to achieve union.

• Melting: break apart a double-stranded DNA into its single-stranded Complementary components by heating
the solution. Melting in vitro is also known under the name of denaturation.
• Annealing: bond together two single-stranded complementary DNA sequences by cooling the solution.
Annealing in vitro is known as hybridization.

•Amplifying (copying): make copies of DNA strands
by using the Polymerase Chain Reaction PCR.
The DNA polymerase enzymes perform several
functions including replication of DNA. The
replication reaction requires a guiding DNA
single-strand called template, and a shorter
oligonucleotide called a primer, that is annealed to it.

• Separating the strands by length using
a technique called gel electrophoresis
that makes possible the separation of
strands by length.

Cutting : DNA double-strands at specific sites by using commercially available restriction
enzymes. One class of enzymes, called restriction endonucleases, will recognize a specific
short sequence of DNA, known as a restriction site. Any double-stranded DNA that contains the
restriction site within its sequence is cut by the enzyme at that location.
• Extracting : those strands that contain a given pattern as a substring by
using affinity purification.

• Ligating: paste DNA strands with compatible sticky ends
by using DNA ligases. Indeed, another enzyme called
DNA ligase, will bond together, or ``ligate'', the end of a
DNA strand to another strand.
• Substituting: substitute, insert or delete DNA sequences
by using PCR site-specific oligonucleotide mutagenesis.

• Marking single strands by hybridization: complementary sequences are attached to the strands,
making them double-stranded. The reverse operation is unmarking of the double-strands by
denaturing, that is, by detaching the complementary strands. The marked sequences will be double
stranded while the unmarked ones will be single-stranded.
• Destroying the marked strands by using exonucleases, or by cutting all the marked strands with a
restriction enzyme and removing all the intact strands by gel electrophoresis. (By using enzymes
called exonucleases, either double-stranded or single-stranded DNA molecules may be selectively
destroyed. The exonucleases chew up DNA molecules from the end inward, and exist with specificity
to either single-stranded or double-stranded form.)
• Detecting and Reading: given the contents of a tube, say ``yes'' if it contains at least one DNA
strand, and ``no'' otherwise. PCR may be used to amplify the result and then a process called
sequencing is used to actually read the solution.

5. INFORMATION STORAGE AND PROCESSING CAPABILITIES
 DNA computing is a far denser packing of molecular information compared with
silicon-based computers.
 A single bacterium cell measures just a micron square - about the same size as a single
silicon transistor but holds more than a megabyte of DNA memory and has all the
computational structures to sense and respond to its environment.
 It has been estimated that a gram of DNA can hold as much information as a trillion
CDs. So DNA molecules would be like mega-memory.

 DNA computers could store a bit, 0 or 1, of data in one
cubic- nanometer, one trillionth the size of the conventional
computer‘s electronic storage. Thus a DNA computer could
store massive quantities of information in the space a standard
computer would use to store much less.
 It would be about twice as fast as the fastest supercomputer,
performing more than 2,000 instructions per second.
 1000 litres of water could contain DNA with more memory
than all the computers ever made, and a pound of DNA would
have more computing power than all the computers ever made.

6. EFFICIENCY
 In both the solid-surface glass-plate approach and the test tube approach, each DNA strand represents
one possible answer to the problem that the computer is trying to solve.
 The strands have been synthesized by combining the building blocks of DNA, called nucleotides, with
one another, using techniques developed for biotechnology.
 Electronic computers have two positions (on or off), whereas DNA has four (C, G, A or T). Restriction
enzymes cut the two strands of double-stranded DNA at different positions leaving overhangs of single-
stranded DNA. Two pieces of DNA may be re- joined if their terminal overhangs are complementary.
Using these operations, fragments of DNA may be inserted or deleted from the DNA.
 In each experiment, the DNA is tailored so that all conceivable answers to a particular problem are
included. Researchers then subject all the molecules to precise chemical reactions that imitate the
computational abilities of a traditional computer.

 If the experiment works, the DNA computer weeds out all the wrong answers, leaving
one molecule or more with the right answer.
 Each molecule of DNA is roughly equivalent to a little computer chip. Conventional
computers represent information in terms of 0‘s and 1‘s, physically expressed in terms
of the flow of electrons through logical circuits, whereas DNA computers represent
information in terms of the chemical units of DNA.
 Computing with an ordinary computer is done with a program that instructs electrons to
travel on particular paths; with a DNA computer, computation requires synthesizing
particular sequences of DNA and letting them react in a test tube or on a glass plate.

 By forcing DNA molecules to generate different chemical states, which can then be examined to
determine an answer to a problem by combination of molecules into strands or the separation of strands,
the answer is obtained.
 Most of the possible answers are incorrect, but one or a few may be correct, and the computer‘s task is to
check each of them and remove the incorrect ones using restrictive enzymes. The DNA computer does
that by subjecting all of the strands simultaneously to a series of chemical reactions that mimic the
mathematical computations an electronic computer would perform on each possible answer.
 The first applications were ``brute force`` solutions in which random DNA molecules were generated,
and then the correct sequence was identified. Recent works have shown how DNA can be employed to
carry out a fundamental computer operation, addition of two numbers expressed in binary (Bancroft) and
several other problems like, Max-Clique Problem, Graph-Colouring Problem, Satisfiability Problem,
Bounded Post Corresponding problem etc.

7. COMPARISON OF DNA AND CONVENTIONAL ELECTRONIC COMPUTERS
7.1 SIMILARITIES
1. Transformation of Data : Both DNA computers and electronic computers use Boolean logic (AND, OR, NAND, NOR)
to transform data. The logical command "AND" is performed by separating DNA strands according to their sequences, and
the command "OR" is done by pouring together DNA solutions containing specific sequences. For example, the logical
statement "X or Y" is true if X is true or if Y is true. To simulate that, the scientists would pour the DNA strands
corresponding to "X" together with those corresponding to ``Y``.
2. Manipulation of Data : Electronic computers and DNA computers both store information in strings, which are
manipulated to do processes. Vast quantities of information can be stored in a test tube. The information could be encoded
into DNA sequences and the DNA could be stored. To retrieve data, it would only be necessary to search for a small part of
it - a key word, for example by adding a DNA strand designed so that its sequence sticks to the key word wherever it
appears on the DNA.

3. Computation Ability : All computers manipulate data by addition and subtraction. A DNA computer should be
able to solve a satisfiability problem with 70 variables and 1,000 AND-OR connections. To solve it, assign
various DNA sequences to represent 0‘s and 1‘s at the various positions of a 70 digit binary number. Vast
numbers of these sequences would be mixed together, generating longer molecules corresponding to every
possible 70-digit sequence

7.2 DIFFERENCES
1. Size :
 A memory bank containing more than a pound of DNA molecules suspended in about 1,000 quarts of fluid, in a bank about a
yard square. Such a bank would be more capacious than all the memories of all the computers ever made.
 The first ever-electronic computer took up a large room whereas the first DNA computer
Adleman) was 100 microliters. Adleman dubbed his DNA computer the TT-100,
for test tube filled with 100 microliters, or about one-fiftieth of a teaspoon of
fluid, which is all it took for the reactions to occur.
2. Representation of Data :
 DNA computers use Base 4 in the form of A, T, C and G
to represent data, whereas electronic computers use Base 2 in the form of 1‘s and 0‘s.
 Using this four letter alphabet, DNA stores information that is manipulated by living
organisms in almost exactly the same way computers work their way through strings of
1‘s and 0‘s.

3. Parallelism :
 In bacteria, DNA can be replicated at a rate of about 500 base pairs a second. Biologically this is quite fast (10 times faster
than human cells) and considering the low error rates, an impressive achievement. But this is only 1000 bits/sec, which is a
snail's pace when compared to the data throughput of an average hard drive.
 But when many copies of the replication enzymes are allowed to work on DNA in parallel, first of all, the replication
enzymes can start on the second replicated strand of DNA even before they're finished copying the first one. So already the
data rate jumps to 2000 bits/sec.
 The number of DNA strands increases exponentially (2n after n iterations). With each additional strand, the data rate
increases by 1000 bits/sec. So after 10 iterations, the DNA is being replicated at a rate of about 1Mbit/sec; after 30
iterations it increases to 1000 GBits/sec. This is beyond the sustained data rates of the fastest hard drives.

4. Material :
 Generally, a variety of enzymes such as restriction nuclease and ligase are considered as the hardware of DNA Computers,
encoded double-stranded or single-stranded DNA molecules as software and data are stored in the sequences of base pairs.
As for conventional electronic computers, electronic devices compose hardware. Software and data are stored in the
organized structure of electronic devices represented by the electrical signals.
 The other difference between DNA Computers and conventional electronic computers in material is the reusability. The
materials used in DNA Computer are not reusable. Whereas an Electronic computer can operate indefinitely with
electricity as its only input, a DNA computer would require periodic refuelling and cleaning.

5. Methods of Calculation :
 Conventional computers represent information physically expressed in
terms of the flow of electrons through logical circuits. Builders of DNA
computers represent information in terms of the chemical units of DNA.
 The basic manipulations used for DNA Computation include Anneal,
Melt, Ligate, Polymerase Extension, Cut, Destroy, Merge, Separate by
Length which can also be combined to high level manipulations such
as Amplify, Separate by Subsequence, Append, Mark, Unmark. And the
most famous example of a higher-level manipulation is the polymerase chain reaction (PCR).

8. PRESENT STATUS OF DNA COMPUTER
In 2001, Prof. Shapiro of the Weizmann Institute and his team introduced the first autonomous programmable DNA
computing device. This computer can perform 330 trillion operations per second, more than 100,000 times the speed of the
fastest PC.
In 2005, a team of researchers at Columbia University Medical Center in New York and the University of New
Mexico developed a prototype DNA computer, named MAYA-II - Molecular Array of YES and AND logic gates, that played
a complete game of tic-tac-toe. A display screen - background - shows that the computer –
red squares - has won the game against a human opponent - blue. MAYA-II is
composed of more than 100 DNA circuits. Its predecessor, MAYA-I was developed by
the research team in 2003. With limited moves, the first MAYA could only play an
incomplete game of tic-tac toe. MAYA-II consists of nine cell-culture wells arranged in
a pattern that resembles a tic-tac-toe grid. Each well contains a solution of DNA material
that is coded with "red" or "green“ fluorescent dye.

In May 2010, IBM and the California Institute of Technology, have actually built a computer chip utilizing synthesized DNA
molecules. In the same year, University of Jerusalem and University of Belgium reported the construction of a DNA based
computational platform that uses a library of catalytic nucleic acids (DNAzymes) for assembly of a universal set of logic gates.
While a desktop PC is designed to perform one calculation very fast, DNA strands produce billions of potential answers
simultaneously. This makes the DNA computer suitable for solving "fuzzy logic" problems that have many possible solutions rather
than the either/or logic of binary computers. In the future, some speculate, there may be hybrid machines that use traditional silicon for
normal processing tasks but have DNA co-processors that can take over specific tasks they would be more suitable for.
MAYA II Japanese DNA computer for gene analysis

9. FUTURE PROSPECTS OF DNA COMPUTER
Current protocols in DNA computation are not good enough for
computational applications. It may be that with current technology and
understanding, a precise enough characterization of DNA chemistry and physics
is not possible for building DNA computers. But, continued exploration of
current protocols and techniques may eventually result in a new body of
methods that are specifically adapted to computing with DNA.
The University of Wisconsin is experimenting with chip-based DNA
computers. Instead, their powerful computing power will be used for areas of
encryption, genetic programming, language systems, and algorithms or by
airlines wanting to map more efficient routes.

These DNA computers can be used in fluids, such as a sample of blood or in the body, and make
decisions at the level of a single cell. DNA computers could conceivably be implanted in the body to both
diagnose and kill cancer cells or monitor and treat diabetes by dispensing insulin when needed.
DNA computers are unlikely to feature word processing,
emailing and solitaire programs. Another important issue is the lack
of the ``killer application``. Part of this is certainly associated with
the problems that DNA computing has experienced, and the hope is
that once the problems are resolved, the applications will come.
DNA computer is application specific, having a potential to replace the high-end research oriented
computers in future.

10. ADVANTAGES AND DISADVANTAGES OF DNA COMPUTER
10.1 ADVANTAGES
 Perform millions of operations simultaneously (Parallel Computing).
 Generate a complete set of potential solutions and conduct large parallel searches.
 Capable of storing billions of times more data
 Over 100 times faster than fastest computer
 Minimal storage requirements.
 Minimal power requirements.

 They are inexpensive to build, being made of common biological materials.
 The clear advantage is that we have a distinct memory block that encodes bits.
 Using one template strand as a memory block also allows us to use its compliment. as
another memory block, thus effectively doubling our capacity to store information.
 More powerful than the world's most powerful supercomputer.
 DNA computers smaller than any computer.

10.2 DISADVANTAGES
 Generating solution sets, even for some relatively simple problems, may require impractically large
amounts of memory (lots and lots of DNA strands are required).
 Many empirical uncertainties, including those involving: actual error rates, the generation of optimal
encoding techniques, and the ability to perform necessary bio-operations conveniently in vitro (for
every correct answer there are millions of incorrect paths generated that are worthless).
 DNA computers could not (at this point) replace traditional computers.
 They are not programmable and the average dunce can not sit down at a familiar
keyboard and get to work.
 It requires human assistance.

11. CONCLUSION
The field of DNA computing and DNA Computer remains alive and promising, even as
new challenges emerge. Most important among these are the uncertainty, because of the DNA
chemistry, in the computational results, and the exponential increase in number of DNA
molecules necessary to solve problems of interesting size.
Despite these issues, definite progress has been made both in quantifying errors, and in
development of new protocols for more efficient and error-tolerant DNA computing.
In addition, new paradigms based on molecular evolution have emerged from
molecular biology to inspire new directions in DNA computing.

12. REFERENCES
Amir Abbaszadeh Sori. 2014. DNA Computer; Present and Future. International Journal of Engineering
Research and Applications, ISSN : 2248-9622, Vol. 4, Issue 6( Version 2), pp.228-232
Braich R S, Chelyapov N, Johnson C, Rothemund P W K and Adleman L. 2013. Solution of a 20-variable 3-
sat problem on a DNA computer. Science, 296:499–502
Sarker A, Ahmed T, Rashid S M M, Anwar S, Jaman L, Tara N, Alam M M and Babu H M H. 2011.
Realization of Reversible Logic in DNA Computing. IEEE 11th International Conference on Bioinformatics and
Bioengineering (BIBE)
Green S, Lubrich D, and Turberfield A. 2006. DNA Hairpins : Fuel for Autonomous DNA Devices.
Biophysical Journal, 91(8):2966–2975
Ehud Shapiro and Yaakov Benenson. 2006. Bringing DNA Computers to Life. Scientific American,
17(3):40– 47

Qian L and Winfree E. 2009. A Simple DNA Gate Motif for Synthesizing Large-scale
Circuits. DNA computing, pages 70–89
Qian L and Winfree E. 2011. Scaling up Digital Circuit Computation with DNA Strand
Displacement Cascades. Science, 332(6034):1196–1201
Van Noort D. 2004. Towards a re-programmable DNA computer, DNA9, LNCS 2943,
Berlin Heidelberg, pp: 190-196
Watada J, Kojima S, Ueda S and Ono O. 2006. DNA computing approrch to optimal
decision problem. International Journal of Innovative Computing, Information and Control,
2(1): 273-282

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