Evolutionary and genetic processes fascinate many organic chemists, and with good reason. They’ve provided us with the greatest set of chemical catalysts we know of: enzymes, which are a working example of molecular-level nanotechnology, right in front of us. A billion years of random tinkering have accomplished a great deal, but (being human) we look at the results and wonder if we couldn’t do things a bit differently, with other aims in mind than “survive or die”.
This has been a big field over the years, and it’s getting bigger all the time. There are companies out there that will try to evolve enzymes for you (here’s one of the most famous examples), and many academic labs have tried their hands at it as well. The two main routes are random mutations and structure-based directed changes – and at this point, I think it’s safe to say that any successful directed-enzyme project has to take advantage of both. There can be just too many possible changes to let random mutations do all the work for you (20 to the Xth power gets out of hand pretty quickly, and that’s just the natural amino acids), and we’re usually not smart enough to step in and purposefully tweak things for the better every time.
Here’s a new paper that illustrates why the field is so interesting, and so tricky. The team (a collaboration between the University of Washington and the ETH in Zürich) has been trying to design a better retro-aldolase enzyme, with earlier results reported here. That was already quite an advance (15,000x rate enhancement over background), but that’s still nowhere near natural enzymes of this class. So they took that species as a starting point and did more random mutations around the active site, with rounds of screening in between, which is how we mere humans have to exert selection pressure. This gave a new variant with another lysine in the active site, which some aldolases have already. Further mutational rounds (error-prone PCR and DNA shuffling) and screening let to a further variant that was over 4000x faster than the original enzyme.
But when the team obtained X-ray structures of this enzyme in complex with an inhibitor, they got a surprise. The active site, which had already changed around quite a bit with the addition of that extra lysine, was now a completely different place. A new substrate-binding pocket had formed, and the new lysine was now the catalytic residue all by itself. The paper proposes that the mechanistic competition between the possible active-site residues was a key factor, and they theorize that many natural enzymes may have evolved through similar paths. But given this, there are other questions:
The dramatic changes observed during RA95 evolution naturally prompt the question of whether generation of a highly active retro-aldolase required a computational design step. Whereas productive evolutionary trajectories might have been initiated from random libraries, recent experiments with the same scaffold dem- onstrate that chemical instruction conferred by computation greatly increases the probability of identifying catalysts. Although the programmed mechanisms of other computationally designed enzymes have been generally reinforced and refined by directed evolution, the molecular acrobatics observed with RA95 attest to the functional leaps that unanticipated, innovative mutations—here, replacement of Thr83 by lysine—can initiate.
So they’re not ready to turn off the software just yet. But you have to wonder – if there were some way to run the random-mutation process more quickly, and reduce the time and effort of the mutation/screening/selection loop, computational design might well end up playing a much smaller role. (See here for more thoughts on this). Enzymes are capable of things that we would never think of ourselves, and we should always give them the chance to surprise us when we can.