Local encoding of computationally designed enzyme activity.

One aim of computational protein design is to introduce novel enzyme activity into proteins of known structure by predicting mutations that stabilize transition states. Previously, we showed that it is possible to introduce triose phosphate isomerase activity into the ribose-binding protein of Escherichia coli by constructing 17 mutations in the first two layers of residues that surround the wild-type ligand-binding site. Here, we report that these mutations can be "transplanted" into a homologous ribose-binding protein, isolated from the hyperthermophilic bacterium Thermoanaerobacter tengcongensis, with retention of catalytic activity, substrate affinity, and reaction pH dependence. The observed 10(5)-10(6)-fold rate enhancement corresponds to 70% of the maximally known transition-state binding energy. The wild-type sequences in these two homologues are almost perfectly conserved in the vicinity of their ribose-binding sites, but diverge significantly at increasing distance from these sites. The results demonstrate that the computationally designed mutations are sufficient to encode the observed enzyme activity, that all the observed activity is encoded locally within the layer of residues directly in contact with the substrate and that, in this case, at least 70% of transition state stabilization energy can be achieved using straightforward considerations of stereochemical complementarity between enzyme and reactants.

Duke Scholars

Author Homme Wytzes Hellinga Biochemistry