ФИЗИКО-ХИМИЧЕСКИЕ ОСНОВЫ НАНОТЕХНОЛОГИИ Профессор Н.Г. Рамбиди

ДНК-компьютинг

Структура ДНК

Розалинда Франклин

Морис Уилкинс

Джеймс Ватсон и Френсис Крик We wish to suggest a structure for the salt of deoxi-ribose nucleic acid (D.N.A.). This structure has novel features which are of considerable biological interest

Nucleotide (DeoxyriboNucleic Acid) DNA Structure N O NH2 Base P O O- Phosphate O CH2 OH Sugar (deoxyribose) 5‘ 4‘ 1‘ 3‘ 2‘ Nucleotide (DeoxyriboNucleic Acid)

DNA Structure - Single Strand 5‘ A 4 Bases Adenine (A) Thymine (T) Cytidine (C) Guanine (G) T C Distinctive ends 5‘ (5-prime) end 3‘ end Sequence 5‘-ATCG-3‘ 3‘ G

DNA Structure – Double Strand 3‘ A G C 5‘ Annealing G lines up with C 3 hydrogen bonds A lines up with T 2 hydrogen bonds 3‘ G 5‘ A T C Watson-Crick complement 5‘-ATCG-3‘ 3‘-TAGC-5‘ "Double Helix" 2 intertwined strands hydrogen bonds (weak) covalent bond (strong)

DNA Structure (3) base pairing Complimentary base pairing accounts for the Chargaff’s rule (A=T, G=C).

DNA Structure (4) – double helix Watson-Crick complement

Вторичная структура ДНК

Структурные варианты ДНК

ДНК – электронная микроскопия

Сложные структуры ДНК

Ферменты – принцип «ключ-замок»

Механизм ферментативной реакции

Репликация ДНК

Вычисления на основе ДНК

A different approach What DNA computing is: What DNA computing isn’t: a completely new method among a few others (e.g., quantum computing) of general computation alternative to electronic/semiconductor technology uses biochemical processes based on DNA What DNA computing isn’t: not to confuse with bio-computing which applies biological laws (evolution, selection) to computer algorithm design.

Why try new stuff ? Will need a dramatically new technology to overcome some CMOS limitations and offer new opportunity. Certain types of problems (learning, pattern recognition, fault-tolerant system, large set search algorithms) are intrinsically very difficult to solve even with fast evolution of CMOS. Hope of achieving massive parallelism.

Conventional vs. Biological Computing Component materials Inorganic, e.g. silicon Biological, e.g. DNA Processing scheme Sequential and limited massively parallel Massively parallel Current max. operations 1012 Op.s per sec. 1014 Op.s per sec. Quantum effects a problem? Yes No Toxic components? Energy efficient?

Historical timeline Research Commercial 1950’s … 1994 1995 2000 2005 R.Feynman’s paper on sub microscopic computers L.Adleman solves Hamiltonian path problem using DNA. Field started D.Boneh paper on breaking DES with DNA Lucent builds DNA “motor” DNA computer architecture ? Commercial 1970’s … 1996 2000 2015 DNA used in bio application Affymetrix sells GeneChip DNA analyzer Human Genome Sequenced Commercial computer ?

Проблема коммивояжера

Структура проблемы «Коммивояжер» { Vin,1,2,3..N, Vout } fixed Vin ,Vout P{1,2,3..N} N! paths

First special DNA computer Special problem: given N points, find a path visiting each and every point only once, and starting and ending at a given locations. (hamiltonian path problem) Solved with a DNA computer by Leonard Adleman in ‘94 for N=6 Basic approach: code each point as an 8 unit DNA string, code each possible path, allow DNA bonding, suppress DNA with incorrect start/end points.

Travelling salesman 1. Locations and complements: x0 x2 x4 x1 x3 x5 p01 p02 p13 1. Locations and complements: X0 = ACTTgcag; X0’ = TGAAcgtc X1 = TCGGactg; X1’ = AGCCtgac X2 = CCGAatgc; X2’ = GGCTtacg …… 2. Paths coded using Xn’: p01 = cgtcAGCC; p12 = tgacGGCT p02 = cgtcGGCT …. locations DNA paths DNA ACTTgcag cgtcAGCC TCGGactg tgac…. p01 <-- Solution Bonding & Filtering x0 x1

Procedure Generate random paths Hybridization & Ligation through the graph Hybridization & Ligation Keep only those paths that begin with vin and end with vout PCR with vin and vout If the graph has n vertices, then keep only those paths that enter exactly n vertices Gel electrophoresis Keep only those paths that enter all of the vertices of the graph at least once. Antibody bead separation With vi If any paths remain, say “Yes”; otherwise, say “No.” Gel electrophoresis & Sequecing

DNA Operators The bio-lab technology. Hybridization Ligation Polymerase Chain Reaction (PCR) Gel electrophoresis Affinity separation (Bead) Enzymes: restriction enzyme…

Hybridization & Ligation base-pairing between two complementary single-strand molecules to form a double stranded DNA molecule Ligation Joining DNA fragments together Solution generation step!

DNA Hybridization & Ligation AGCTTAGGATGGCATGG AATCCGATGCATGGC + CGTACCTTAGGCT Hybridization AGCTTAGGATGGCATGG AATCCGATGCATGGC CGTACCTTAGGCT Ligation AGCTTAGGATGGCATGGAATCCGATGCATGGC CGTACCTTAGGCT Dehybridization AGCTTAGGATGGCATGGAATCCGATGCATGGC + CGTACCTTAGGCT

PCR (Polymerase Chain Reaction) Mullis: Nobel Prize (1993) Amplifies (produces identical copies of) selected dsDNA molecules. Make 2n copies (n : number of iteration) Solution filtering or amplification step!

The Invention of PCR Invented by Kary Mullis in 1983. First published account appeared in 1985. Awarded Nobel Prize for Chemistry in 1993.

Did He Really Invent PCR? The basic principle of replicating a piece of DNA using two primers had already been described by Gobind Khorana in 1971: Kleppe et al. (1971) J. Mol. Biol. 56, 341-346. Progress was limited by primer synthesis and polymerase purification issues. Mullis properly exploited amplification.

It is hard to exaggerate the impact of the polymerase chain reaction It is hard to exaggerate the impact of the polymerase chain reaction. PCR, the quick, easy method for generating unlimited copies of any fragment of DNA, is one of those scientific developments that actually deserves timeworn superlatives like "revolutionary" and "breakthrough."  - Tabitha M. Powledge

PCR Cycles Denature DNA (950 C) Anneal Primers (Usually 50 – 65 0C) Extend Primers (720 C) Repeat

Gel electrophoresis Bead Separation Molecular size fraction technique Bead Separation Detect the specific DNA Solution detection or filtering step!

Gel Electrophoresis

Bead Separation (1) Magnetic Beads Magnet Complementary

Bead Separation (2) Biotin (Vitamin H)

Restriction enzyme Cut the specific DNA site. Solution detection or filtering step! A A G C T T T T C G A A OH 3’ A 5’ P A C G T T EcoRI T T C G A A P 5’ 3’ OH

Results Adleman estimated the speed of his graph problem calculation at 1014 operations/sec ! Energy efficiency: 2x1019 operations per joule This approach seems appropriate for a small range mostly combinatorial problems or problems that can be cast as such (e.g., encryption/decryption) The range of problems is still very limited Correctness of the computation highly depends on the fidelity of the process

Sources of errors a) Common operation in handling DNA is filtering: DNA filter 5% error rate Heterogenous mix Single DNA solution Leads to high output error rate b) Chain Reaction for DNA amplification. error ATTGA.. ATGGA.. Rare type of error, but does present a problem

Sources of errors (cont’d) c) Binding error. Expect binding between complements C G Formation of double helix T A G C A C T A error causes bulges, missed bonds -- translates into output errors Error resilient computation techniques required: classic error correction with redundant representation careful data encoding - trade off density for resiliency varying environment conditions may improve performance Question: are errors always bad ? In this case, an occasional mutation may lead to improved learning

What’s up to date Research still in very early stages but promise is big First groundbreaking work by Adleman at USC only 6 years ago No commercialization in sight within ~10 years Main work on settling for a logic abstraction model, ways of using DNA to compute Research sponsored by universities (Princeton, MIT, USC, Rutgers, etc) and NEC, Lucent Bell Labs, Telcordia, IBM One way or another, DNA computing will have a significant impact