Lecture: DNA nanostructuresGoals: show strategies

and examples

of

bottom-up

assembly

of

DNA-based

nanostructures

Construction with “Smart Bricks”

The bricks

that

make

a nano-object

can already

have

the information necessary

to

self- assemble

bottom-up if

placed

in the right conditions, without

any

other

external

intervention

by

some ‘large

scale’

agent.

Static structures based on the DNA linear helixThese

are structures

made

by

design. They

exploit the Watson-Crick

pairing

to

make

a doube-helix

from

separate parts.

For

example, there

are techniques

that

can attach

new

objects

to

DNA, allowing to

assemble

objects

with

funcions

that

are not

normally

assembled.

DNA serves

as

the coupling

signal.

Tomkins

et

al. ChemBioChem

2001

“Asymmetrical

Protein-DNA

dumbbells”

organic

synthesis

of modfied

oligonucleotides that

can be

derivatized

with

proteins

Christof Niemeyer: the preparation

of

DNA-protein

hybrids

and the creation

of objects.

Exploiting

the tetravalent Streptavidin, it

is

possible

to

attach

more oligonucleotide molecules

to

the same

bridging

streptavidin. Different

geometries

can be

obtained

(a small

ring or branched

structures). As

another

example, streptavidin can be

immobilized

on a long

RNA via a complementary probing

oligonucleotide

bound

to

the streptavidin.

Building on a surfaceSurface

localization

is

a facile method

to

imobilize

a nanoobject

in a precise

location in space. You

can then

study

the object, or use

it.

The presence

of

the surface

leads

to

a serious

change

in the behavior

of

molecules, as

these

are not

free to

move around

any

more and they

have

a wall

next

to

them

(excluded

volume effecs). The reduced

dimensionality

also

increases

the effective

molecular concentrations.

Two examples of the use of DNA to make protein layers or to localize proteins specificallyin order to make a proten microarray.

DNA detection thanks to the formation of large adducts beginning from colloidal nanoparticles (Chad Mirkin and Paul Alivisatos)The color of

colloidal

particles

depends

on their

size

(other

parameters

left

untouched) due to

plasmon resonance. Solutions

of

10-20

nm

gold

nanoparticles

are red, while

larger

aggregates

are bluish.This

provides

with

a strategy

towards

a colorimetric

assay

of

the presence

of

a sequence

of

DNA.

Scanometric detection of DNA hybridization (Chad Mirkin)According

to

the same

strategy, colloidal

gold

nanoparticles can be

tethered

to

a probe sequence

on the surface

only

if

a DNA sequence

complementary

both

to

the surface

bound

probe and to

the nanoparticle-bound

probe is

present. A ‘sandwich’

is

obtained. If

nanoparticles of

different

size

are used, a colorimetric

response

can be

obtained

also

for

signals

such

as

sequence

polymorphism

and they

can be

localized

on only

one

spot on the surface.

Afer

binding, the gold nanoparticles can be

developed through

Ag+

reduction: Silver nanopaticles

then

fuse and lead

to

a visible

stain

on the surface. A common and cheap flatbed

scanner can be

used

to

read

the signal

of

only

a few

analyte

molecules

recognized

by

the DNA microarray.

DNA Computing: DNA vs. Silicon(http://arstechnica.com/reviews/2q00/dna/dna-2.html)

Transistor-based computers typically handle operations in a sequential manner. Of

course

there

are multi-processor

computers, and modern

CPUs

incorporate some parallel

processing, but

in general, in the basic

von Neumann architecture

computer, instructions

are handled

sequentially. Typically, increasing

performance of

silicon

computing

means

faster

clock cycles

(and larger

data paths), where

the emphasis

is

on the speed

of

the CPU and not

on the size

of

the

memory.

For

DNA computing, though, the power

comes

from

the memory

capacity

and parallel processing. For

example, let's look at the read

and write

rate of

DNA. In

bacteria, DNA can be

replicated

at a rate of

about

500 base pairs

a second. 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

you

can allow

many

copies

of

the replication

enzymes

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. But

look

what

happens

after

each

replication

is

finished

-

the number

of

DNA strands increases

exponentially

(2^n 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.

The Adleman experiment

Suppose that

I live in LA, and need

to

visit

four

cities: Houston, Chicago, Miami, and NY, with

NY being

my

final

destination. The airline

I’m taking

has

a specific

set of

connecting

flights

that

restrict

which

routes

I can take (i.e. there

is

a flight from

L.A. to

Chicago, but

no flight from

Miami to

Chicago). What

should

my

itinerary

be

if

I

want

to

visit

each

city only

once?

Starting

from

L.A.

you

need

to

fly

to

Chicago, Dallas, Miami and then

to

N.Y.

Any

other

choice

of

cities

will

force

you

to

miss a destination, visit

a city twice, or not make

it

to

N.Y.

For

six, seven, or even

eight

cities, the problem

is

still

manageable. However, as the number

of

cities

increases, the problem

quickly

gets

out of

hand. Assuming

a

random

distribution

of

connecting

routes, the number

of

itineraries

you

need

to check

increases

exponentially. So you

will

need

a computer ...or perhaps

DNA.

Adleman

first generated

all

the possible

itineraries

and then

selected

the correct itinerary. This

is

the advantage

of

DNA. It’s small

and there

are combinatorial

techniques

that

can quickly

generate many

different

data strings. Since

the enzymes

work on many

DNA molecules

at once, the selection

process

is

massively

parallel.

Specifically, the method

based

on Adleman’s experiment

would

be

as

follows:1 Generate all

possible

routes.

2 Select

itineraries

that

start with

the proper

city and end with

the final

city.

3 Select

itineraries

with

the correct

number

of

cities.4 Select

itineraries

that

contain

each

city only

once.

All

of

the above

steps

can be

accomplished

with

standard molecular

biology techniques.

Part I: Generate all possible routes

Strategy: Encode

city names

in short DNA sequences. Encode

itineraries

by connecting

the city sequences

for

which

routes

exist.

DNA can simply

be

treated

as

a string

of

data. For

example, each

city can be represented

by

a "word" of

six

bases:

Los Angeles: GCTACGChicago: CTAGTADallas: TCGTACMiami: CTACGGNew York: ATGCCG

The entire

itinerary

can be

encoded

by

simply

stringing

together

these

DNA sequences

that

represent

specific

cities. For

example, the route

from

L.A

-> Chicago -

> Dallas -> Miami -> New York would

simply

be GCTACGCTAGTATCGTACCTACGGATGCCG, or equivalently

it

could

be

represented

in double

stranded

form

with

its

complement

sequence.

Itineraries

can then

be

produced

from

the city encodings

by

linking

them

together

in proper

order. For

example, you

can encode the routes between cities by

encoding

the compliment

of

the second

half

(last three

letters) of

the departure

city and the first half

(first three

letters) of

the arrival

city. For

example

the route

between

Miami (CTACGG) and NY (ATGCCG) can be

made

by

taking

the second half

of

the coding

for

Miami (CGG) and the first half

of

the coding

for

NY (ATG).

This

gives

CGGATG. By

taking

the complement

of

this

you

get, GCCTAC, which not only uniquely represents the route from Miami to NY, but will connect the DNA representing Miami and NY by hybridizing itself to the second half of the code representing Miami (...CGG) and the first half of the code representing NY (ATG...). For

example:

Random

itineraries

can be

made

by

mixing city encodings

with

the route

encodings. Finally, the DNA strands can be connected together by an enzyme called ligase. What

we

are left

with

are strands

of

DNA representing

itineraries

with

a

random

number

of

cities

and random

set of

routes. For

example:

We

can be

confident

that

we

have

all

possible

combinations

including

the correct one

by

using

an

excess

of

DNA encodings, say

1013

copies

of

each

city and each route

between

cities.

Part II: Select itineraries that start and end with the correct cities

Strategy: Selectively

copy and amplify

only

the section

of

the DNA that

starts

with

LA and ends

with

NY by

using

the Polymerase

Chain Reaction.

After

Part I, we

now

have

a test tube full of

various

lengths

of

DNA that

encode possible

routes

between

cities. What

we

want

are routes

that

start with

LA and end

with

NY. To

accomplish

this

we

can use

a technique

called

Polymerase

Chain Reaction

(PCR), which

allows

you

to

produce many

copies

of

a specific

sequence

of

DNA. So to

selectively

amplify

the itineraries

that

start and stop with

our

cities

of interest, we

use

primers

that

are complimentary

to

LA and NY. What

we

end up with

after

PCR is

a test tube full of

double

stranded

DNA of

various

lengths, encoding itineraries

that

start with

LA and end with

NY.

Part III: Select itineraries that contain the correct number of cities.

Strategy: Sort

the DNA by

length

and select

the DNA whose

length

corresponds

to 5 cities.

Our

test tube is

now

filled

with

DNA encoded

itineraries

that

start with

LA and end with

NY, where

the number

of

cities

in between

LA and NY varies. We

now

want

to

select

those

itineraries

that

are five

cities

long. To

accomplish

this

we

use

Gel Electrophoresis

We

can then

simply

cut out the band of

interest to

isolate DNA of

a specific

length. Since

we

known

that

each

city is

encoded

with

6 base pairs

of

DNA, knowing

the

length

of

the itinerary

gives

us

the number

of

cities. In this

case we

would

isolate the DNA that

was

30 base pairs

long (5 cities

times

6 base pairs).

Part IV: Select itineraries that have a complete set of cities

Strategy: Successively

filter

the DNA molecules

by

city, one

city at a time

by

affinity purification: the compliment

of

the sequence

in question

to

a substrate

like

a

magnetic

bead.

The beads

are then

mixed

with the DNA. DNA, which

contains

the sequence

you're after

then hybridizes

with

the complement

sequence

on the beads. These beads

can then

be

retrieved

and the DNA isolated.

So we

now

affinity

purify

fives

times, using

a different

city complement

for

each

run. If an

itinerary

is

missing

a city, then

it

will

not

be

"fished

out" during

one

of

the runs

and

will

be

removed

from

the candidate pool. What

we are left with are the are itineraries that start in LA, visit each city once, and end in NY. This

is

exactly

what

we

are

looking

for. If

the answer

exists

we

would

retrieve

it

at this

step.

Reading out the answer: simply

sequence

the DNA strands.

However, since

we

already

have

the sequence

of

the city encodings

we

can use

an

alternate method

called

graduated PCR. Here

we

do a series

of

PCR amplifications

using

the primer

corresponding

to

L.A., with

a different

primer

for

each

city in succession. By

measuring

the various

lengths

of

DNA for

each

PCR product

we

can piece

together

the final

sequence

of

cities

in our

itinerary. For

example, we

know

that

the DNA itinerary

starts

with

LA and is

30 base pairs

long, so if

the PCR product

for

the LA and Dallas primers

was

24 base pairs

long, you

know

Dallas is

the fourth

city in the itinerary

(24 divided

by

6). Finally, if

we

were

careful

in our

DNA manipulations

the only

DNA left

in our

test tube should

be

DNA itinerary

encoding

LA, Chicago, Miami, Dallas, and NY. So if

the succession

of

primers

used

is

LA & Chicago, LA & Miami, LA & Dallas, and LA & NY, then

we

would

get

PCR products

with

lengths

12, 18, 24, and 30 base pairs.

CaveatsAdleman's experiment

solved

a seven

city problem, but

there

are two

major

shortcomings

preventing

a large

scaling

up of

his

computation. The complexity

of the traveling

salesman problem

simply

doesn’t disappear

when

applying

a different

method

of

solution

-

it

still

increases

exponentially. For

Adleman’s method, what scales

exponentially

is

not

the computing

time, but

rather

the amount

of

DNA: more

than

a few

people have

pointed

out that

using

his

method

to

solve a 200 city HP problem

would

take an

amount

of

DNA that

weighed

more than

the earth. Another

factor

that

places

limits

on his

method

is

the error

rate for

each

operation. Since these

operations

are not

deterministic

but

stochastically

driven

(we

are doing

chemistry

here), each

step

contains

statistical

errors, limiting

the number

of iterations

you

can do successively

before

the probability

of

producing

an

error

becomes

greater

than

producing

the correct

result. For

example

an

error

rate of

1% is

fine for

10 iterations, giving

less

than

10% error, but

after

100 iterations

this

error

grows

to

63%.

CONCLUSION:

So will

DNA ever

be

used

to

solve a traveling

salesman problem

with

a higher number

of

cities

than

can be

done

with

traditional

computers? Well, considering

that

the record is

a whopping

13,509 cities, it

certainly

will

not

be

done

with

the procedure described

above. It

took

this

group

only

three

months, using

three

Digital

AlphaServer

4100s (a total of

12 processors) and a cluster of

32 Pentium-II

PCs. The solution

was possible

not

because

of

brute force

computing

power, but

because

they

used

some

very

efficient

branching rules. This

first demonstration

of

DNA computing

used

a rather

unsophisticated

algorithm, but

as

the formalism

of

DNA computing

becomes

refined, new

algorithms

perhaps

will

one

day

allow

DNA to

overtake

conventional computation

and set a new

record.

On the side of

the "hardware" (or should

I say

"wetware"), improvements in biotechnology are happening at a rate similar

to

the advances

made

in the

semiconductor industry. For

instance, look at sequencing; what

once took

a graduate student

5 years

to

do for

a Ph.D

thesis

takes

Celera

just one

day. With

the

amount

of

government

funded

research

dollars

flowing

into

genetic-related

R&D

and with

the large

potential

payoffs

from

the lucrative pharmaceutical

and medical-related

markets, this

isn't surprising. Just look at the number of advances in DNA-related technology that happened in the last five years: "DNA chips," the Human

Genome

Project is

producing

rapid

innovations

in sequencing

technology. The future of

DNA manipulation

is

speed, automation, and miniaturization.

Static structures based on branched forms of DNA

“DNA is every designer’s dream, being at the same time the blueprint of the structure and the structure itself”

[N.C. Seeman]

Structural DNA nanotechnology (as Ned Seeman puts it)“A key motivation

for

constructing

objects

from

DNA is

to

generate rational

means

for

constructing

periodic

matter. At least

three

properties

are necessary

for

the components

of systems

where

this

is

possible: (a) The predictable

specificity

of intermolecular

interactions

between

components; (b) the local

structural

predictability

of intermolecular

products; and (c) the structural

rigidity

of the components”

The Holliday

junction

Making

things

with

the blocked Holliday

junction C

hurc

h of

S. F

ranc

is -

Evo

ra, P

ortu

gal

Making

non- natural

objects

with

nantural materials

“The nucleic-acid ‘system’ that operates in terrestrial life is optimized (through evolution) chemistry incarnate. Why not use it ... to allow human beings to sculpt something new, perhaps beautiful, perhaps useful, certainly unnatural.” Roald

Hoffmann, su American Scientist, 1994

DNA is

perfect

as

a nanotech

brick: 2 nm

diameter, 3.4 nm

pitch, 50 nm

persistence length, a fully

nanoscale object

.

Sticky

ends

cohesion

is

probably

the best example

of

programmable

molecular

recognition: you

can have

a lot

of

different

possible

sticky

ends

(4N

for

N-long

ends) and the cohesion

product

is

the normal

double

helix

(structural

predictability). Solid

phase

oligonucleotide synthesis

makes

molecular

programming

attainable. Molecular

interaction

can be

programmed

to

be

specific.

WHY NUCLEIC ACIDS? Can you

achieve

the same

using

antigens and antibodies, for

instance? You

could

probably

get

a similar

affinity, but

the relative orientation

of

partners

would

have

to

be

defined

for

each

partner. This

is

why

nucleic

acids

are quite

unique, they

provide

a readily

available

programmable

system for

organizing

molecular

assembly.

Why building with DNA?

A general

route

towards

crystallization

of

molecules?

From linear to branched DNA: the Holliday juncion as a nanoconstruction brick

DNA Duplex, most

of

the nucleic

acids

is

in linear

form

An intermediate in recombination

J1 JUNCTIONJ1 = Holliday

junction

with

a

modified

sequence

that

prevents the branch-point

migration

that

is

fundamental

in biological recombination

A STABLE STRUCTURE

Important

for:

1-

studying

the structure

of

the Holliday

junction

2-

a brick

for

structural

DNA nanotechnology

Nadrian

C. Seeman

(Seeman, N. C. (1982) J. Theor. Biol. 99, 237-247)

Physical ligation

Designing a parallelogram

Informatics ligation

Nadrian

C. Seeman

also

developed

sequence

selection

software

•10% non-denaturing

gel• 4°C

1.1+2+3+4+5+62.1+2+3+4+53.1+2+3+44.1+2+35.1+56.4M. pBR322 marker

434

267234213192184

123

1048980

645751

6 5 4 3 2 1 M

PAGE characterization of a parallelogram

2

1

3

4

5

6

375-350

1 2 3 4 5 6M32P labelling

•10% native PAGE, RT

•Lanes

1-6: only

one

oligo

is labelled

in each

•Lane M: HOT marker –

25 bp ladder

HOT ATP + strand

HOT (5’) strand

+ ADP

T4 DNA kinasi

Do the 6 oligos assemble in one object?

A bidimenional array1D –

2D by

changing

sticky-ends

(Mao e Seeman, JACS 1999)

AFM of

the 2D array of parallelograms

Design and preparation of supramolecular constructs

Double-crossover structures (introduced in 1993): the design and realization

of

rigid

tiles

for

making

DNA mosaics.These

structures, inspired

from

meiosis

intermediates, are made

by

two

parallel

double helices

rigidly

joined

thanks

to

the exchange

of

strands. Some strands

belong

to

one

helix

at the beginning

and then

switch

helix.

There

are different

types

of

DX as

a function

of

the geometry

and topology

of

the strand

exchange.

Some of

the DX possible

on paper

are not

stable, though.By

equipin

DX with

sticky

ends, they

can be

assembled

into

1D or 2D polymeric

structures.

Similarly, 3 double

helices

can be

paired, making

2 reciprocal

exchanges

between

each

couple

of

helices. These

are named triple crossover (TX), and are bigger

than

DX. Other

possible

variations: DX+J, where

an

hairpin

sticks

out from

the center of

a DX and it

can be

made

perpendicular

to

the DX

plane.

A scheme

for

the TX

Periodic structures with controlled spacing can be made by assembling DX tiles through sticky ends. They can also extend out of the plane.Tiles are assembled in a non-computational manner to make simple and repetitive structures with a small number of different tiles. Alternatively, a larger variety of tiles can be assembled in an ‘algorithmic’

manner thus making computation while they

assemble. The computational rules are defined in the base sequence of the sticky ends..

This is an intrinsically more efficient method to do computation than the one proposed by Adleman: by proper coding of the sticky ends, only the assembly that follows the coded rules can take place (and not a myriad of products). Once tiles are formed and assembled, they are ligated. Ligation generates long oligonucleotides that contain the solution to the problem (that you read by sequencing the oligo).

(Li et al. JACS 2003)

Very thin arrays of constant thickness

These TX linear arrangements can be functionalized at desired locations and serve as spacing templates for proteins or nanoparticles. Such molecular wire is mechanically very rigid.

You can achieve strings of gold beads by using streptavidin-

coated gold nanoparticles.

Making tubes with DNA tiles

The group

of

Reif made

the assembly

of

TX tiles

with

a diedral angle different

from

180°: a curvature in the tile

plane

is

produced

ad eventally

a DNA tube

will

emerge. (Reif, PNAS 2004)

An alternative way to make tubes (N. Seeman)

Seeman

could

design and make

a large

hollow

tile

of

DNA made

by

a helix bundle. This

can be

assembled

along

its

axis through

stiky

ends

to

make

a tube. (Seeman, 2005 NanoLetters).

Ribbonds or 2D lattices of DNA with the 4-by-4 junction

The base tile

is

made

of

4 J1 junctions

joined

with

a central

strand

that

participates

in each

junction. 5

oligos

make

the trick.

Sticky

ends

are located

at the ends

of

the chains, so self-assembly

is

possible.

Giunzioni J1

(Yan

et

al. Science 2003)

nastri

Array 2D

Depending

on the way to

join the tiles, the assembly

results

in a ribbon/tubeor

in a flat

2D lattice: one

joining

strategy

sums

the small

deformation

of

the tile

and the assembly

plane

curves

in a tube (A), while

the alternative assembly

cancels

the deformations

out and makes

a large

flat

2D array

of

tiles

(B)

A

B

Proteins can be specificaly located on the arrays (you could make nano- circuits)

Biotins

are bound

at the center of

the oligonucleotide that

participates

in all

4 J1.

Streptavidin is

added

in solution

so i can locate of

the biotins.

The DNA ribbons

can be

metallized

to

make conductive

nanowires

with

a diameter

of

about

40 nm

and the length

of

a few

micrometers.

One

4-by-4 silver-coated

ribbon

laid

on top of

microelectrodes

in an

attempt

to

measure

its

electrical

properties.

(Shih

et

al. Nature 2004)

A self-assembling octahedron made with a 1.7 kb DNA moleculeA 1669 nt single-stranded

DNA molecule

self-assembles

together

with

5

40 n long oligonucleotides to

make

an

octahedron. The three- dimensional

object

can be

assembled

with

a piece

of

Dna that

can be

replicated

with

a DNA polymerase! It

could

host

a 14 nm

sphere; from

the opening of

its

faces, a 8 nm

sphere

could

enter.

DX

PX12

PX

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A recent examle

shows the degree of complexity that can be achieved:A molecular fabric made through the selfA molecular fabric made through the self--assembly of crossovers on a assembly of crossovers on a natural DNAnatural DNAPaul Rothemund, Nature 16 March 2006 (vol

440, pages 297-302 )

According to this approach, a DNA molecule can be sewn together to make any desired form through a certain number of synthetic oligonucleotides.

Results are astonishing: DNA origami can reproduce any desired shape in the nanoscale!

Rothemund, Nature, vol

440, pages 297-302

100 nm

100 nm

1 µm 1 µmscale 1:2x1014

The first DNA motor: Bernard Yurke

e Andrew Turberfield

(2000)A motor made

of

oligonucleotides that

reorganize

as

a response

to

the introduction

of

an

oligonucleotide in solution. It

is

the opening and closing

of

a molecular

tweezer. The movement

is

visualized

thanks

to

FRET.

The strategy

to

extract

a component

from

the structure

is

worth

noticing

and has

been

re-used

many

times

since. A protruding

single-stranded

tail

is

exploited

in order

to

nucleate a new, more stable

double

helix

that

then

strips

off one

oligo

from

the nanostructure

(recycling

the motor). This

takes

place

at room

temperature, without

the neeed

of

disassembling

anything

else.

Main

disadvantages

of

the most

common DNA nanodevices

1.

Production of

waste

DNA•

Degradation

of

the performance over

time

2.

Need

of

bi-macromolecular

events•

Concentration-dependent

performance

•

Performance depends

on bulky

molecules•

Opening and closing

signals

through

expensive

molecules

Design of

a triplex-based

DNA motor

Marco Brucale et

al.

Design / 2

•

the generated waste(salt) does not interfere with the functioning of the motor up to 1M or more.

Static

characterizations

CD

spectrum

at different

pH.

Absorbance

at 260nm

at different pH.

Electrophoretic

mobility

for a construct

with

or without

the TFO

Dynamic

characterizations

/ 1

Fluorescnece emission of A+B* alternating the pH between 5 and 9

•

The emission

intensity

depends

exclusively

on the separation

between donor

and acceptor

• No degradation

of

the performance with

the successive additions

E

Q

EQ

Dynamic

characterizations

/ 2

At high dilution

• Same performance!

Putting the device on a surface

Si

O

O

O SH

R1

SS(L)-Oligo

A

pH 9.0 buffer16h

Si

O

O

O SS(L)

glas

s

glas

s

Si

O

O

O SS(L)

Oligo

B*

pH 5.0 buffer16h gl

ass

MPTS

95% EtOH5% H2

O pH 4.516h

2h 150°C0.05 torr

MPTS gas phase

a)

b)

glas

s

Single molecule characterization by scanning confocal fluorescence microscopy on the surface

Dynamic Single-Molecular DNA structures

Single molecule fluorescence studies confirm that the structure can assume both conformations when immobilized on a surface.

Take-home message: with DNA you can design and make nanostructures with the desired shape and mechanical properties. They can be static or dynamic, can be made of DNA only or decorated with a large variety of other functional nano-objects.

Seeman e coll.: a molecular machine based on the B → Z transition.A DNA segment

of

particular

sequence

can

have

a B to

Z transition. If

this

is

located between

two

DX (which

carry

fluorophors)

then

their

motion

can be

studied. Disadvantages: it

is

difficult

to

cycle

the motor

back and forth.

A molecular machine based on a DNA quadruplex

[ W. Tan et al, 2002]

A DNA biped

that

walks

along

a sidewalk

Using

the same

strategy

that

Yurke

and turberfield

employed

to

strip off oligos

from

a structure, Ned

Seeman

implemented

a walker

that

can move

controllably

along

a track, by

sticking

and releasing

its

feet

from

posts. Each

motion

requires

the addition

of

an

oligonucleotide. The waste

can be

removed

by

proper

oligonucleotide functionalization.

(Sherman e Seeman, NanoLetters 2004)[animazione]

An autonomous DNA motor: it runs as long as there is fuel

An autonomous molecular machine: a DNAzyme cuts the RNA oligonucleotide that keeps a structure extended after it binds to it. After the cut, the fragments separated and the structure is ready to host another copy of the same RNA oligo, effectively ‘breathing’ as long as there are oligos that can bind and get cut.

[ C. Mao et al, 2004]

Interesting

videos:

DNA structural

nanotechHao

Yan

Paul Rothemund