Local encoding of computationally designed enzyme activity

Abstract

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.

Figure 1

Triose phosphate isomerase designs. (a), proposed mechanism of the interconversion of dihydroxyacetone phosphate (DHAP) to glyceraldehyde 5-phosphate (GAP), indicating the three residues that critical for catalysis (b), comparison of the folds of dimeric wild-type yeast triose phosphate isomerase (left), and monomeric E. coli ribose-binding protein (right), showing location of the substrate (yellow/red) and catalytic residues (blue/grey). (c), superposition of the wild-type yeast triose phosphate isomerase with active site residues (green) onto the designed active site in E. coli ribose-binding protein (blue). The superposition was generated using the three carbon atoms of the enediolate. Note that the enediolate conformations differ in the phosphate position. (d), schematic comparing the yeast triose phosphate isomerase and E. coli active sites. Note that the pro-R proton at C1 is abstracted in the yeast enzyme to form a cis-enediol(ate) intermediate whereas the design is modeled to abstract the pro-S proton at C1.

Figure 2

Comparison of the sequences of the E. coli and T. tengcongensis ribose-binding proteins. (a), linear sequence comparison indicating conservation pattern (gray, neutral changes; green, charge reversals; red, charge↔polar; yellow, charge↔non-polar; blue, polar↔non-polar). The mutations for constructing novoTIMs are shown in the middle line (bold, primary complementary surface; white letter on black field, catalytic residues; other, secondary complementary surface). (b), mapping of the sequence differences on the structure of the E. coli ribose-binding protein (color coding as for panel a; transplanted region indicated by stippled line).

Figure 3

Structure-based comparison of sequence identities by scoring the number of identical residues in 3Å-concentric shells centered on the mid-point of the bound ribose (E. coli structure). In the primary complementary surface (first shell, 9 Å), the two sequences are identical; at the furthest distance from the ligand-binding site (eighth shell, 31 Å) they are only 30% identical.

Figure 4

Initial DHAP-dependent rates of GAP formation. (a) the uncatalyzed reaction. The solid line represents the best-fit to the experimental data giving a rate constant of 3.4×10⁻⁷ s⁻¹ (b) Comparison of ecNovoTIM1.2 (■) and tteNovoTIM1.2 (◆) designs. The solid line represents the best-fit of the Michaelis-Menten equation to the experimental data giving a k_cat of 0.15 and 0.25 s⁻¹, and K_M of 7.1 and 6.5 mM for ecNovoTIM1.2 and tteNovoTIM1.2, respectively.

Figure 5

Steady-state inhibition of novoTIM activity by phosphoglycolohydroxamate (a). Lineweaver-Burke transformations of DHAP-dependent reaction rates were determined from 0 μM (lower line) to 250 μM (upper line) inhibitor for ecNovoTIM1.2 (b) and tteNovoTIM1.2 (c). Both ecNovoTIM1.2 and tteNovoTIM1.2 are competitively inhibited by phosphoglycolohydroxamate with 84 μM and 92 μM inhibition constants of respectively.

Figure 6

pH dependence of the reaction profile for ecNovoTIM1.2 (▲) and tteNovoTIM1.2 (◆). The solid line represents the best-fit to the experimental ecNovoTIM1.2 data (pK_a of 6.6); a fit to the tteNovoTIM1.2 data is precluded because the low-pH values are underdetermined.