Combinatorial reshaping of the Candida antarctica lipase A substrate pocket for enantioselectivity using an extremely condensed library

Abstract

A highly combinatorial structure-based protein engineering method for obtaining enantioselectivity is reported that results in a thorough modification of the substrate binding pocket of Candida antarctica lipase A (CALA). Nine amino acid residues surrounding the entire pocket were simultaneously mutated, contributing to a reshaping of the substrate pocket to give increased enantioselectivity and activity for a sterically demanding substrate. This approach seems to be powerful for developing enantioselectivity when a complete reshaping of the active site is required. Screening toward ibuprofen ester 1, a substrate for which previously used methods had failed, gave variants with a significantly increased enantioselectivity and activity. Wild-type CALA has a moderate activity with an E value of only 3.4 toward this substrate. The best variant had an E value of 100 and it also displayed a high activity. The variation at each mutated position was highly reduced, comprising only the wild type and an alternative residue, preferably a smaller one with similar properties. These minimal binary variations allow for an extremely condensed protein library. With this highly combinatorial method synergistic effects are accounted for and the protein fitness landscape is explored efficiently.

Fig. 1.

α-Methylcarboxylate esters of interest for the project with different steric bulk. CALA-YNG has high enantioselectivity and activity toward 2, 3, and 4, but poor enantioselectivity and activity toward 1.

Fig. 2.

Flowchart of combinatorial substrate pocket reshaping.

Fig. 3.

The active site of CALA with the tetrahedral intermediate (S)-1 docked in the active site. The nucleophilic Ser184 is covalently bound to the carbonyl of the ester. Surrounding the substrate are the nine sites that were selected for mutagenesis. The residues forming the combinatorial mutagenesis set are displayed with the wild-type residues underlined.

Fig. 4.

Comparison of activity toward different α-methylcarboxylate esters for a small subset (89 transformants) of the combinatorial library. The transformants are ordered after increasing activity toward substrate 2. The highest activity for each substrate in this subset was normalized to 100. P. pastoris X33 supernatants were used as blank. The highest activity toward 1 found in this subset is an SV₁CAV₂ variant. For comparison, in this subset the initial rates for the best variants toward 1, 2, and 4 are 1.1, 22, and 32 mOD₄₁₀ min^-1, respectively.

Fig. 5.

Models of CALA variants with the tetrahedral intermediate (S)-1 seen in the active site. The variants shown are (A) WT, and (B) SV₁CAV₂. SV₁CAV₂ provides more space than WT to accommodate the substrate.

Fig. 6.

A greatly simplified illustration of a protein fitness landscape that is mostly neutral but with a distant peak. Point A represents a starting point with neutral surroundings. B represents a point in a distant patch with increased fitness compared to point A. To be able to directly jump from A to B the fitness landscape has to be probed radically.