DNA Computing

Seminar on :

Seminar Outline

Introduction: Why to switch to DNA Computing?Structure of DNA(DeoxyRibo Nucleic Acid).Bio-Chemical Operations on DNA, useful in

Computing.Adleman's Experiment.Advantages and Disadvantages of DNA Computing.Future Scenario.

Why Switch to DNA ComputingIn last few decades Electronics have invaded all walks of

life. Modern chips have 1 million Transistors per mm2.Miniaturization of Electronics Devices can not

continue – the laws of physics and nature will catch up soon to impose limit on Silicon Chips.

Uniqueness of DNA: Why DNA is computational Element?

Extremely dense information.

Enormous Parallelism.

Highly energy efficient.

Structure of DNA

Double Helical structure.A (Adenine)always opposite to T (Thymine)G (Guanine) always opposite to C (Cytosine) by Hydrogen bonds, inter Molecular attraction.How Kidney cell knows that its a kidney cellAnd functions it has to perform?A double stranded DNA within a single cell is

fully self-contained. has the ability to repair itself;

provide backup; create new patterns;

DNA Replication

Bio-Chemical Operations on DNA

Extraction: Given a test tube T and strand s, it is possible to extract all the strands in T that contain ‘s’ as substring.(Polymerase chain Reaction PCR).

Annealing: It is possible to pair (anneal) and separate (melt) two antiparallel and complementary single strands.

Separation By Sequence: Allows to remove all DNA strands that contain a desired sequence.(by generating complement strands).Known as Watson- Crick Model. Also Append, Detect.

Bio-Chemical Operations cont.Nucleases : Nucleases cut nucleic acids. use

restriction Enzymes. e.g., echerichia coli restriction enzyme cut DNA after G in sequence.

Ligases: Bind molecules together. Covalently bond two strands into single.

Electrophoresis: The negatively charged DNA move towards anode with, shorter strands moving more quickly than longer.

Separation By Length: Using Electrophoresis, contents of test tube can be separated by increasing length.

Adleman’s ExperimentA Computer scientist at the University of South

California.

In 1994, Adleman solved Directed Hamilton Path Problem (recognized as Travelling Salesman Problem) using DNA.

The Problem: A directed Graph G=(V,E)|V|=n, |E|=m and two distinguished vertices.

Vin = s and Vout= t.Verify whether there is a path (s,v1,v2,….,t)

Which is sequence of “one-way” edges that begins in Vin and ends in Vout.

Which Enters all Vertices. And enters every vertex exactly once.

ExampleHere Vin= s and Vout= t.

Hamilton Path is (s,2,4,6,3,5,t).

s 4

53

62

t

Algorithm of Adleman1. Generate Random paths2. From all paths created in step 1, keep only those that start at s

and end at t.3. From all remaining paths, keep only those that visit exactly n

vertices.4. From all remaining paths, keep only those that visit each vertex

at least once.5. if any path remains, return “yes”; otherwise, return “no”.

Step 1.Random Path GenerationVertex Representation:

Each vertex in graph is associated with a random 20-mersequence of DNA denoted by Sv.

For each such sequence generate its complement Sv.

For ex. Representation of vertices 2,4 : S2 = GTCACACTTCGGACTGACCTS2=AGGTCAGTCCGAAGTGTGAC S4= TGTGCTATGGGAACTCAGCGS4=CGCTGAGTTCCCATAGCACA

Edge representation: With this construction, Suv = Svu.(Not for Vin, Vout).each edge is of 20-mer but if any of s or t involves its 30.

5’ S2 3’ 5’ S4 3’

Edge(2,4)

Step 2:Keep Only those that start at s and end at t

Product of step 1 is amplified by PCR(Polymerase Chain Reaction: one way to amplify DNA) using primers Ss and St.

By this, only those molecules encoding paths that begin with vertex s and end with vertex t were amplified.

Step3:Keep Only those that visit exactly n vertices.DNA is negatively charged.Place DNA in a gel matrix at the negative end. (Gel

Electrophoresis)Longer strands will not go as far as the shorter

strands.In our example we want DNA that is 7 vertice times 20

base pairs, or 140 base pairs long.

Step 4: Keep Only those that visit each vertex at least once

From the double stranded DNA product of step3, generate single stranded DNA.

Incubate the single stranded DNA with S2 conjugated to the magnetic beads.

Only single stranded DNA molecules that contained the sequence S2 annealed to the bound S2 and were retained. Process is repeated for every vertex.

Do this using Affinity Purification.

s 2 t4 6 3 5

5

compliment Magnetic bead

Advantages and DNA ComputersParallelism: A Test Tube of DNA can contain trillions of DNA

strands . So each operation is carried out on all strands in test tube Parallel!!!

Low Power dissipation: 2 x 1019 operations per joule.

Clean, Cheap and Available.Gigantic Memory Capacity: The 1 gram of DNA can hold

about 1x1014 MB of data.Bio-Ware: why not turn the living cell itself into a

computer, powered by its own metabolism.Suitable for N-P Hard problems: experiments have

proved that DNA Computers are suitable for solving complex combinatorial problems. to break Data Encryption Standard(DES).

Disadvantages : Danger of Errors Possible

Undesired Annealing:Partial Matches: A strand u could anneal with one that’s

similar to ū, but it is not the right one.Undesired matches between two shifted strands

What would happen if a ‘good’ path were lost during one of the extraction operations in step4?

-FALSE NEGATIVE!-Adleman’s suggestion: to amplify the content of the test tube.

Hydrolyses: DNA Molecules Fracture and Gradually turns into water.

Disadv. Cont. Size and Error Restrictions

The computation time required to solve problems with a DNA computer does not grow exponentially, but amount of DNA required DOES.(for 200 cities will take wt of earth.)

DNA computing involves a relatively large amount of error.As size of problem grows, probability of receiving incorrect

answer eventually becomes greater than probability of receiving correct answer.

Information Untransmittable: We can not make two strands communicate with each other.

Future ScenarioDNA Manipulation technology has rapidly improved

in recent years, and future advances may make DNA computers more efficient.

DNA computers are unlikely to feature word processing, emailing and solitaire programs.

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. Hence better applicable in only some promising areas.

References:Leonard M. Adleman, “Computing With DNA”

Scientist southern California American Aug. 1998 Balaji Akula and James Cusick “Biological Computing

Fundamentals and Futures” Walters Kluwer Corporate Legal Services New York, NY

N. Lewis, P. Weinberger, 1995 “DNA Computing” JASON The Mitre Corporation,

Fulk, Kevin, 2003, “Biological Computing, ISRC Future Technology Topic Brief”, Viewed on April 2009, http://www.uhisrc.com/FTB/Biocomputing/FTBBioComp.pdf.

It will take years to develop a practical, workable DNA computer.

But…Let’s all hope that this DREAM comes true!!!

Thank You!Any Questions?