I'm
currently investigating two topics. One is how to make the
simplest possible nanoscale molecular manufacturing system.
I think I've devised a version that can be developed with
today's technology, but can be improved incrementally to
approach the tabletop diamondoid nanofactory that is the
major milestone of molecular manufacturing. The other topic
is how proteins work. I think I've had an insight that solves
a major mystery: how protein machines can be so efficient.
And if I'm right, it means that natural protein machines
have inherent performance limitations relative to artificial
machines.
I'll talk about the proteins first.
Natural proteins can do things that we can't yet even begin
to design into artificial proteins. And although we can
imagine and even design machines that do equivalent functions
using other materials, we can't build them yet. Although
I personally don't expect proteins to be on the critical
path to molecular manufacturing, some very smart people
do, both within and outside the molecular manufacturing
community. And in any case, I want to know how everything
at the nanoscale works.
One of the major questions about
protein machines is how they can be so efficient. Some of
them, like ATP synthase, are nearly 100% efficient.
ATP synthase has a fairly complex job: it has to move protons
through a membrane, while simultaneously converting molecules
of ADP to ATP.
That's a pump and an enzyme-style chemical reaction--very
different kinds of operation--linked together through a
knobby floppy molecule, yet the system wastes almost no
energy as it transfers forces and manipulates chemicals.
A puzzle, to be sure: how can something like a twisted-up
necklace of different-sized soft rubber balls be the building
material for a highly sophisticated machine?
I've been thinking about that in
the back of my mind for a few months. I do that a lot: file
some interesting problem, and wait for some other random
idea to come along and provide a seed of insight. This time,
it worked. I have been thinking recently about entropy and
springiness, and I've also been thinking about what makes
a nanoscale machine efficient.
And suddenly it all came together.
A nanoscale machine is efficient
if its energy is balanced at each point in its action. In
other words, if a motion is “downhill” (the machine has
less energy at the end of the motion) then that energy must
be transferred to something that can store it, or else it
will be lost as heat. If a motion is “uphill” (requires
energy) then that energy must be supplied from outside the
machine. So a machine with large uphills and downhills in
its energy-vs.-position trajectory will require a lot of
power for the uphills, and will waste it on the downhills.
A machine with sufficiently small uphills and downhills
can be moved back and forth by random thermal motion, and
in fact, many protein machines are moved this way.
A month or so ago, I read an article
on ATP synthase in which the researchers claimed that the
force must be constant over the trajectory, or the machine
couldn't be efficient. I thought about it until I realized
why this was true. So the question to be answered was, how
was the force so perfectly balanced? I knew that proteins
wiggled and rearranged quite a bit as they worked. How could
such a seemingly ad-hoc system be perfectly balanced at
each point along its trajectory?
As
I said, I have been thinking recently about entropic springs.
Entropy, in this application, means that nanoscale objects
(including molecular fragments) like to have freedom to
wiggle. A stringy molecule that is stretched straight will
not be able to wiggle. Conversely, given some slack, the
molecule will coil and twist. The more slack it has, the
more different ways it can twist, and the happier it will
be.
Constraining these entropic wiggles, by stretching a string
or squashing a blob, costs energy. At the molecular scale,
this effect is large; it turns out that entropic springiness,
and not covalent bond forces, is the main reason why latex
rubber is springy. This means that any nanoscale wiggly
thing can function as an entropic spring. I sometimes picture
it as a tumbleweed with springy branches--except that there
is only one object (for example, a stringy molecule) that
wiggles randomly into all the different branch positions.
Sometimes I compare it to a springy cotton ball.
One Saturday morning I happened to
be thinking simultaneously about writhing proteins, entropic
springs, and efficient machines. I suddenly realized, as
I thought about the innards of a protein rearranging themselves
like a nest of snakes, that installing lots of entropic
springs in the middle of that complex environment would
provide lots of adjustable parameters to balance whatever
force the machine's function generated. Because of the complex
structural rearrangement of the protein, each spring would
affect a different fraction of the range of motion. Any
uphills and downhills in its energy could be smoothed out.
Natural protein machines are covered
and filled with floppy bits that have no obvious structural
purpose. However, each of those bits is an entropic spring.
As the machine twists and deforms, its various springs are
compressed or allowed to expand. An entropic spring only
has to be attached at one point; it will press against any
surface that happens to come into its range. Compressing
the spring takes energy and requires force; releasing the
spring will recover the energy, driving the machine forward.
As soon as I had that picture, I
realized that each entropic spring could be changed independently,
by blind evolution. By simply changing the size of the molecule,
its springiness would be modified. If a change in a spring
increased the efficiency of the machine, it would be kept.
The interior reconfiguration of proteins would provide plenty
of different environments for the springs--plenty of different
variables for evolution to tweak.
Always
before, when I had thought about trying to design a protein
for efficiency and effectiveness, I had thought about its
backbone--the molecular chain that folds up to form the
structure. This is large, clumsy, and soft--not suitable
for implementing subtle energy balancing.
It would be very hard (no pun intended) to design a system
of trusses, using protein backbones and their folded structure,
that could implement the right stiffness and springiness
to balance the energy in a complex trajectory. But the protein's
backbone has lots of dangling bits attached. The realization
that each of those was an entropic spring, and each could
be individually tuned to adjust the protein's energy at
a different position, made the design task suddenly seem
easy.
The task could be approached as:
1) Build a structure to perform the protein's function without
worrying about efficiency and energy balance.
Make it a large structure with a fair amount of internal
reconfiguration (different parts having different relative
orientations at different points in the machine's motion);
2) Attach lots of entropic springs all over the structure;
3) Tune the springs by trial and error until the machine
is efficient--until the energy stored by pressure on the
myriad springs exactly balances the energy fluctuations
that result from the machine's functioning.
I
proposed this idea to a couple of expert nanoscale scientists--a
molecular manufacturing theorist and a physicist. And I
learned a lot.
One of the experts said that he had not previously seen
the observation that adding lots of springs made it easier
to fine-tune the energy accurately. That was pretty exciting.
I learned that proteins do not usually disfigure themselves
wildly during their operation--interior parts usually just
slip past each other a bit. I watched some movies of proteins
in action, and saw that they still seemed to have enough
internal structural variation to cause different springs
to affect different regions of the motion trajectory. So,
that part of the idea still seems right.
I
had originally been thinking in terms of the need to balance
forces; I learned that energy is a slightly more general
way to think about the problem. But in systems like these,
force is a simple function of energy, and my theory translated
perfectly well into a viewpoint in terms of energy. It turned
out that one of my experts had studied genetic algorithms,
and he warned that there is no benefit to increasing the
number of evolvable variables in the system if the number
of constraints increases by the same number. I hadn't expected
that, and it will take more theoretical work to verify that
adding extra structures in order to stick more entropic
springs on them is not a zero-sum game.
But my preliminary thinking says that one piece of structure
can have lots of springs, so adding extra structures is
still a win.
The other expert, the physicist,
asked me how much of the effect comes from entropic springiness
vs. mechanical springiness. That's a very good question.
I realized that there is a measurable difference between
entropic springs and mechanical (covalent bond) springs:
the energy stored by an entropic spring is directly proportional
to the temperature. If a machine's efficiency depends on
fine-tuning of entropic springs, then changing the temperature
should change all the spring constants and destroy the delicate
energy balance that makes it efficient. I made the prediction,
therefore, that protein machines would have a narrow temperature
range in which they would be efficient. Then I thought a
bit more and modified this. A machine could use a big entropic
spring as a thermostat, forcing itself into different internal
configurations at each temperature, and fine-tuning each
configuration separately. This means that a machine with
temperature-sensitive springs could evolve to be insensitive
to temperature. But a machine that evolved at a constant
temperature, without this evolutionary pressure, should
be quite sensitive to temperature.
After thinking this through, I did
a quick web search for the effect of temperature on protein
activity. I quickly found [a page] containing a sketch of
enzyme activity vs. temperature for various enzymes. Guess
what--the enzyme representing Arctic shrimp has maximum
activity around
4 C, and mostly stops working just a few degrees higher.
That looks like confirmation of my theory.
http://academic.brooklyn.cuny.edu/biology/bio4fv/page/enz_act.htm
That web page, as well as another
one, says that enzymes stop working at elevated temperatures
due to denaturation--change in three-dimensional structure
brought on by breaking of weak bonds in the protein. The
[other web page] also asserts that the rate of enzyme activity,
“like all reactions,” is governed by the Arrhenius equation,
at least up to the point where the enzyme starts to denature.
The Arrhenius equation says that if an action requires thermal
motion to jump across an energy barrier, the rate of the
action increases as a simple exponential function of temperature.
But this assumes that the height of the barrier is not dependent
on temperature. If the maintenance of a constant energy
level (low barriers) over the range of the enzyme's motion
requires finely tuned, temperature dependent mechanisms,
then spoiling the tuning--by a temperature change in either
direction--will decrease the enzyme's rate.
http://www.lsbu.ac.uk/biology/enztech/temperature.html
I'll go out on a limb and make a
testable prediction. I predict that many enzymes that are
evolved for operation in constant or nearly constant temperature
will have rapid decrease of activity at higher and lower
temperatures, even without structural changes. When the
physical structure of some of these supposedly denatured
enzymes is examined, it will be found that the enzyme is
not in fact denatured: its physical structure will be largely
unchanged. What will be changed is the springiness of its
entropic springs.
If
I am right about this, there are several consequences. First,
it appears that the design of efficient protein machines
may be easier than is currently believed. There's no need
to design a finely-tuned structure (backbone). Design a
structure that barely works, fill it with entropic springs,
and fine-tune the springs by simple evolution.
Analysis of existing proteins may also become easier. The
Arrhenius equation should not apply to a protein that uses
entropic springs for energy balancing. If Arrhenius is being
misapplied, then permission to stop using it and fudging
numbers to fit around it should make protein function easier
to analyze. (The fact that ‘everyone knows’ Arrhenius applies
indicates that, if I am right about entropic springs being
used to balance energy, I've probably discovered something
new.)
Second, it may imply that much of
the size and intricate reconfiguration of protein machines
exists simply to provide space for enough entropic springs
to allow evolutionary fine-tuning of the system. An engineered
system made of stiff materials could perform an equivalent
function with equivalent efficiency by using a much simpler
method of force/energy compensation. For example, linking
an unbalanced system to an engineered cam that moves relative
to a mechanical spring will work just fine. The compression
of the spring, and the height of the cam, will correspond
directly to the energy being stored, so the energy required
to balance the machine will directly specify the physical
parameters of the cam.
The third consequence, if it turns
out that protein machines depend on entropic springs, is
that their speed will be limited. To be properly springy,
an entropic spring has to equalize with its space; it has
to have time to spread out and explore its range of motion.
If the machine is moved too quickly, its springs will lose
their springiness and will no longer compensate for the
forces; the machine will become rapidly less efficient.
Stiff mechanical springs, having fewer low-frequency degrees
of freedom, can equilibrate much faster. If I understand
correctly, my physics expert says that a typical small entropic
spring can equilibrate in fractions of a microsecond. But
stiff mechanical nanoscale springs can equilibrate in fractions
of a nanosecond.
I will continue researching this.
If my idea turns out to be wrong, then I will post a correction
notice in our newsletter archive at the top of this article,
and a retraction in the next newsletter. But if my idea
is right, then it appears that natural protein machines
must have substantially lower speeds than engineered nanoscale
machines can achieve with the same efficiency. “Soft” and
“hard” machines do indeed work differently, and the “hard”
machines are simply better.
=========
The second thing I am investigating
is the design of a nanoscale molecular manufacturing system
that is simple enough to be developed today, but functional
enough to build rapidly improving versions and large-throughput
arrays.
It may seem odd, given the ominous
things CRN has said about the dangers of advanced molecular
manufacturing, that I am working on something that could
accelerate it. But there's a method to my madness. Our overall
goal is not to retard molecular manufacturing; rather, it
is to maximize the amount of thought and preparation that
is done before it is developed. Currently, many people think
molecular manufacturing is impossible, or at least extremely
difficult, and will not even start being developed for many
years. But we believe that this is not true--we’re concerned
that a small group of smart people could figure out ways
to develop basic capabilities fairly quickly.
The primary insights of molecular
manufacturing--that stiff molecules make good building blocks,
that nanoscale machines can have extremely high performance,
and that general-purpose manufacturing enables rapid development
of better manufacturing systems--have been published for
decades. Once even a few people understand what can be done
with even basic capabilities, we think they will start working
to develop them. If most people do not understand the implications,
they will be unprepared.
By developing and publishing ways to develop molecular manufacturing
more easily, I may hasten its development, but I also expect
to improve general awareness that such development is possible
and may happen surprisingly soon. This is a necessary precondition
for preparedness.
That's why I spend a lot of my time trying to identify ways
to develop molecular manufacturing more easily.
An early goal of molecular manufacturing
is to build a nanoscale machine that can be used to build
more copies and better versions. This would answer nagging
worries about the ability of molecular manufacturing systems
to make large amounts of product, and would also enable
rapid development of molecular manufacturing technologies
leading to advanced nanofactories.
I’ve been looking for ways to simplify
the Burch/Drexler [planar assembly nanofactory]. This method
of “working backward” can be useful for planning a development
pathway. If you set a plausible goal pretty far out, and
then break it down into simpler steps until you get to something
you can do today, then the sequence of plans forms a roadmap
for how to get from today's capabilities to the end goal.
http://lizardfire.com/nanofactorySS/index.htm
The first simplification I thought
of was to have the factory place blocks that were built
externally, rather than requiring it to manufacture the
blocks internally. If the blocks can be prefabricated, then
all the factory has to do is grab them and place them into
the product in specified locations.
I went looking for ways to join prefabricated
molecular blocks and found a possible solution. A couple
of amino acids, cysteine and histidine, like to bind to
zinc. If two of them are hooked to each block, with a zinc
ion in the middle, they'll form a bond quite a bit stronger
than a hydrogen bond. That seems useful, as long as you
can keep the blocks from joining prematurely into a random
lump. But you can do that simply by keeping zinc away.
So,
mix up a feedstock with lots of molecular zinc-binding building
blocks, but no zinc. Build a smart membrane with precisely
spaced actuators in it that can transport blocks through
the membrane. On one side of the membrane, put the feedstock
solution. On the other side of the membrane, put a solution
of zinc, and the product. As the blocks come through the
membrane one at a time, they join up with the zinc and become
“sticky”--but the mechanism can be used to retain them and
force them into the right place in the product. It shouldn't
require a very complex mechanism to “grab” blocks from feedstock
(via Brownian assembly) through a hole in a membrane, move
them a few nanometers to face the product, and stick them
in place. In fact, it should be possible to do this with
just one molecular actuator per position. A larger actuator
can be used to move the whole network around.
Then I thought back to some stuff
I knew about how to keep blocks from clumping together in
solution. If you put a charge on the blocks, they will attract
a ‘screen’ of counterions, and will not easily bump each
other. So, it might be possible to keep blocks apart even
if they would stick if they ever bumped into each other.
In fact, it might be very simple. A zinc-binding attachment
has four amino acids per zinc, two on each side. Zinc has
a +2 charge. If the rest of the block has a -1 charge for
every pair of amino acids, then when the block is bound
with zinc into a product, all the charges will match up.
But if it's floating in solution with zinc, then the zinc
will still be attracted to the two amino acids; in this
case, the block should have a positive charge, since each
block will have twice as much zinc-charge associated with
it in solution as when it's fastened into the product. This
might be enough to keep blocks from getting close enough
to bind together. But if blocks were physically pushed together,
then the extra zinc would be squeezed out, and the blocks
would bind into a very stable structure.
That’s the theory, at this point.
It implies that you don't need a membrane, just something
like a tattoo needle that attaches blocks from solution
and physically pushes them into the product. I do not know
yet whether this will work. I will be proposing to investigate
this as part of a Phase 2 NIAC project. If the theory doesn't
work, there are several other ways to fasten blocks, some
triggered by light, some by pressure, and some simply by
being held in place for a long enough period of time.
It
appears, then, that the simplest way to build a molecular
manufacturing system may be to develop a set of molecular
blocks that will float separately in solution but fasten
together when pushed. At first, use a single kind of block,
containing a fluorescent particle.
Use a scanning probe microscope to push the blocks together.
(You can scan the structure with the scanning probe microscope,
or see the cluster of fluorescence with an ordinary light
microscope.) Once you can build structures this way, build
a structure that will perform the same function of grabbing
blocks and holding them to be pushed into a product. Attach
that structure to a nano-manipulator and use it to build
more structures. You'd have a hard time finding the second-level
structures with a scanning probe microscope, but again the
cluster of fluorescence should show up just fine in a light
microscope.
Once you know you can build a passive
structure that builds structures when poked at a surface,
the next step is to build an active structure--including
an externally controlled nanoscale actuator--that builds
structures. Use your scanning probe microscope with multiple
block types to build an actuator that pushes its block forward.
Build several of those in an array. Let them be controlled
independently. You still need a large manipulator to move
the array over the surface, but you can already start to
increase your manufacturing throughput. By designing new
block types, and new patterns of attaching the blocks together,
better construction machines could be built. Sensors could
be added to detect whether a block has been placed correctly.
Nanoscale digital logic could be added to reduce the number
of wires required to control the system. And if anyone can
get this far, there should be no shortage of ideas and interest
directed at getting farther.
=========
That’s an inside look at how my thinking
process works, how I develop ideas and check them with other
experts, and how what I’m working on fits in with CRN’s
vision and mission. Please contact me if you have any feedback.
Chris
* * * * * * * * * * * * * * * *
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