The most convincing argument that it must be possible to make sophisticated nanoscale machines is that life already does it – cell biology is full of them. But whereas the machines proposed by Drexler are designed from rigid materials drawing on the example of human-scale mechanical engineering, nature uses soft and flexible structures made from proteins. At the temperatures at which protein machines operate, random thermal fluctuations – Brownian motion – cause the structures to be constantly flexing, writhing and vibrating. How is it possible for a mechanism to function when its components are so wobbly?
It’s becoming more and more clear that the internal flexibility of proteins and their constant Brownian random vibration is actually vital to the way these machines operate. Some fascinating evidence for this view was presented at a seminar I went to yesterday by Jeremy Smith, from the University of Heidelberg.
Perhaps the most basic operation of a protein-based machine is the binding of another molecule – a ligand – to a specially shaped site in the protein molecule. The result of this binding is often a change in shape of the protein. It is this shape change, which biologists call allostery, which underlies the operation both of molecular motors and of protein signalling and regulation.
It’s easy to imagine ligand binding as being like the interaction between a lock and a key, and that image is used in elementary biology books. But since both ligand and protein are soft it’s better to think of it as an interaction between hand and glove; both ligand and protein can adjust their shape to fit better. But even this image doesn’t convey the dynamic character of the situation; the protein molecule is flexing and vibrating due to Brownian motion, and the different modes of vibration it can sustain – its harmonics, to use a musical analogy – are changed when the ligand binds. Smith was able to show for a simple case, using molecular dynamics simulations, that this change in the possible vibrations of the protein molecule plays a major role in driving the ligand to bind. Essentially, what happens is with the ligand bound the low frequency collective vibrations become lowered further in frequency – the molecule becomes effectively softer. This leads to an increase in entropy, which provides a driving force for the ligand to bind.
A highly simplified theoretical model of allosteric binding solved by my colleague up the road in Leeds, Tom McLeish , has just been published in Physical Review Letters (preprint, abstract, subscription required for full published article). This supports the notion that the entropy inherent in thermally excited vibrations of proteins plays a big role in ligand binding and allosteric conformational changes. As it’s based on rather a simple model of a protein it may offer food for thought for how one might design synthetic systems using the same principles.
There’s some experimental evidence for these ideas. Indirect evidence comes from the observation that if you lower the temperature of a protein far enough there’s a temperature – a glass transition temperature – at which these low frequency vibrations stop working. This temperature coincides with the temperature at which the protein stops functioning. More direct evidence comes from rather a difficult and expensive technique called quasi-elastic neutron scattering, which is able to probe directly what kinds of vibrations are happening in a protein molecule. One experiment Smith described directly showed just the sort of softening of vibrational modes on binding that his simulations predict. Smith’s seminar went on to describe some other convincing, quantitative illustrations of the principle that flexibility and random motion are vital for the operation of other machines such as the light driven proton pump bacteriorhodopsin and one of the important signalling proteins from the Ras GTPase family.
The important emerging conclusion from all this is this: it’s not that protein-based machines work despite their floppiness and their constant random flexing and vibrations, they work because of it. This is a lesson that designers of artificial nanomachines will need to learn.