review articles
Doi: 10.1145/2380656.2380675
The challenge of programming molecules
to manipulate themselves.
b Y DaViD Dot Y
theory of
algorithmic
self-assembly
seLF-asseMBLY is the process by which small
components automatically assemble themselves
into large, complex structures. Examples in nature
abound: lipids self-assemble a cell’s membrane, and
bacteriophage virus proteins self-assemble a capsid
that allows the virus to invade other bacteria. Even a
phenomenon as simple as crystal formation is a process
of self-assembly. How could such a process be described
as “algorithmic?” The key word in the first sentence is
automatically. Algorithms automate a series of simple
computational tasks. Algorithmic self-assembly systems
automate a series of simple growth tasks, in which the
object being grown is simultaneously the machine
controlling its own growth.
Although large tracts of the theory presented in
this article are applicable to non-molecular systems,
much of the motivation arises from nanoscale self-assembly (as an engineering field, as opposed to the
study of natural self-assembly systems). The broad
goal of nanoscience is to manipulate molecules with
nanoscale precision. Ambitious long-term applications
include microscopic, chemical-detect-ing robots that move toward and metabolize pollutants, or the integration
of human tissue with an implanted
medical device.
Why should computer science have
anything to do with nanoscience, beyond the obvious role of developing
software-modeling tools? Luca Cardel-li, in a panel discussion at the 2011
Conference on DNA Computing and
Molecular Programming, observed
that while the computing revolution
was about the systematic manipulation
of information, nanoscience is about
the systematic manipulation of matter.
Nanoscience provides a novel justification for studying computation. Many
of the traditional forms of manual control are simply not possible at small
scales. Automating the growth of molecular structures is not merely faster
or more convenient than building such
structures by hand. Our hands, and the
machines they operate, are simply too
large to manipulate individual molecules. We must learn to program molecules to manipulate themselves.
DNA is the molecule of choice in
many labs, not for its biological properties but for its information-bearing
properties. It is easy to synthesize, and
its physical properties are well understood. DNA origami45 is currently the
most successful laboratory technique
for self-assembling DNA. A long scaffold DNA strand is folded into a shape
by mixing it with hundreds of shorter
staple strands, each of which binds to
key insights
the idea of “molecules that can perform
computation” is transforming the way
we engineer self-assembling molecular
systems.
a small number of simple types
of molecules can grow into large,
sophisticated nanoscale structures
automatically.
understanding the fundamental abilities
and limitations of these systems is
crucial for guiding experimental work.
many known theoretical results have
drawn on the theorems, techniques, and
paradigms of computer science.