Many chemical reactions depend not only on the atomic composition of molecules but also on their spatial arrangement, and thus enantiomers can have very different chemical behaviors. Since organisms are not chirally neutral, medical properties of drugs made from enantiomers depend on which chirality of the active ingredient is present. One enantiomer might have a beneficial effect, while the other one is harmful. This is the case for example for Ethambutol (one enantiomer treats tuberculosis, the other causes blindness), or Naproxen (one enantiomer treats arthritis pain, the other causes liver poisoning).
The chemical synthesis of molecules however typically produces molecules of both chiralities in approximately equal amounts, which creates the need to separate them. One way to do this is to use chemical reactions that are sensitive to the molecules’ chirality. Such a procedure has the disadvantage though that it is specific to one particular molecule and cannot be used for any other.
Now three physicists have shown, by experimental and numerical analysis, that there may be a universal way to separate enantiomers
- Separation of chiral colloidal particles in a helical flow field
Maria Aristov, Ralf Eichhorn, and Clemens Bechinger
Soft Matter, 2013,9, 2525-2530
They have shown this as follows.
Molecules are typically of the size of some nanometers or so, and the swimming performance for molecules of different chirality is difficult to observe. Instead, the authors used micrometer-sized three-dimensional particles made of a type of polymer (called SU-8) by a process called photolithography. The particles created this way are the simplest example of configurations of different chirality. They labeled the right-handed particles with a blue fluorescent dye, and the left-handed particles with a green fluorescent dye. This allows taking images of them by a fluorescent microscope. Below you see a microscope image of the particles
Next you need a narrow channel through which water flows under some pressure. The swirl is created by gratings in the wall of the channel. The length of this channel is about a meter, but its height and width is only of the order 150 μm. Then you let bunches of the mixed chiral particles flow through the channel and photograph them on a handful of locations. From the amount of blue and green that you see in the image, you can tell how many of each type were present at a given time. Here’s what they see (click to enlarge)
This figure is an overlay of measurements at 5 different locations as a function of time (in seconds). The green shade is for molecules with the chirality that matches the water swirl orientation, the blue shade is for those with the opposite chirality. They start out, at x=32.5mm, in almost identical concentration. Then they begin to run apart. Look at the left tail of the x=942.5 mm measurement. The green distribution is almost 200 seconds ahead of the blue one.
If you aren’t impressed by this experiment, let me show you the numerical results. They modeled the particles as rigidly coupled spheres in a flow field with friction and torque, added some Gaussian white noise, and integrated the equations. Below is the result of the numerical computation for 1000 realizations (click to enlarge)
I am seriously amazed how well the numerical results agree with the experiment! I’d have expected hydrodynamics to be much messier.
The merit of the numerical analysis is that it provides us with understanding of why this separation is happening. Due to the interaction of the fluid with the channel walls, the flow is slower towards the walls than in the middle. The particles are trying to minimize their frictional losses with the fluid, and how to best achieve this depends on their chirality relative to the swirl of the fluid. The particles whose chirality is aligned with the swirl preferably move towards the middle where the flow is faster, while the particles of the opposite chirality move towards the channel walls where the flow is slower. This is what causes them to travel at different average velocities.
This leaves the question whether this study of particles of micrometer size can be scaled down to molecules of nanometer size. To address this question, the authors demonstrate with another numerical simulation that the efficiency of the separation (the amount of delay) depends on the product of the length of the channel and the velocity of the fluid, divided by the particle’s diffusion coefficient in the fluid. This allows one to estimate what is required for smaller particles. If this scaling holds, particles of about 120 nm size could be separated in a channel of about 3cm length and 3.2 μm diameter, at a pressure of about 108 Pa, which is possible with presently existing technology.
Soft matter is not anywhere near by my area of research, so it is hard for me to tell whether there are effects at scales of some hundred nanometers that might become relevant and spoil this simple scaling, or whether more complicated molecule configurations alter the behavior in the fluid. But if not, this seems to me a tremendously useful result with important applications.