Computational Design of Highly Efficient Cold-Adapted Enzymes with Elevated Temperature Optima

Cold-adapted enzymes from psychrophilic species are generally among the most highly optimized enzymes found in nature. They thus invariably outperform their orthologous mesophilic counterparts in terms of activity, below and around room temperature. It is therefore not so surprising that no successful attempts to enhance the activity of cold-adapted enzymes have been reported yet. Here, we address this problem in the case of a small lipase from an Arctic bacterium using computational design of enzyme variants and validation of the computational predictions by kinetic experiments. Remarkably, our results now show that it is possible to construct variants, with just a few mutations, that both markedly increase the catalytic rates over the entire examined temperature range and move the temperature optimum upward. The latter is shown to be associated with an inactivation phenomenon caused by an unproductive active site conformation that emerges at higher temperatures. Hence, the enzyme variants were aimed at destabilizing this inactive state, and the strategy turned out to work. Of particular interest here is the fact that our most efficient cold-adapted enzyme variant only has mutations that are 15–20 Å from the reaction center. This underscores the high degree of optimization of the native enzyme and thus suggests that mutation sites for further improvement may have to be sought at more distant amino acid positions.