I don't know how many readers have been following this, but there's been some interesting work over the last few years in using streptavidin (a protein that's an old friend of chemical biologists everywhere) as a platform for new catalyst systems. This paper in Science (from groups at Basel and Colorado State) has some new results in the area, along with a good set of leading references. (One of the authors has also published an overview in Accounts of Chemical Research). Interestingly, this whole idea seems to trace back to a George Whitesides paper from back in 1978, if you can believe that.

(Strept)avidin has an extremely well-characterized binding site, and its very tight interaction with biotin has been used as a set of molecular duct tape in more experiments than anyone can count. Whitesides realized back during the Carter administration that the site was large enough to accommodate a metal catalyst center, and this latest paper is the latest in a string of refinements of that idea, this time using a rhodium-catalyzed C-H activation reaction.

A biotinylated version of the catalyst did indeed bind streptavidin, but this system showed very low activity. It's known, though, that the reaction needs a base to work, so the next step was to engineer a weakly basic residue nearby in the protein. A glutamate sped things up, and an aspartate even more (with the closely related asparagine showing up just as poorly as the original system, which suggests that the carboxylate really is doing the job). A lysine/glutamate double mutant gave even better results.

The authors then fine-tuned that system for enantioselectivity, mutating other residues nearby. Introducing aromatic groups increased both the yield and the selectivity, as it turned out, and the eventual winner was run across a range of substrates. These varied quite a bit, with some combinations showing very good yields and pretty impressive enantioselectivities for this reaction, which has never until now been performed asymmetrically, but others not performing as well.

And that's promise (and the difficulty) with enzyme systems. Working on that scale, you're really bumping up against individual parts of your substrates on an atomic level, so results tend, as you push them, to bin into Wonderful and Terrible. An enzymatic reaction that delivers great results across a huge range of substrates is nearly a contradiction in terms; the great results come when everything fits just so. (Thus the Codexis-style enzyme optimization efforts). There's still a lot of brute force involved in this sort of work, which makes techniques to speed up the brutal parts very worthwhile. As this paper shows, there's still no substitute for Just Trying Things Out. The structure can give you valuable clues about where to do that empirical work (otherwise the possibilities are nearly endless), but at some point, you have to let the system tell you what's going on, rather than the other way around.