OptZyme: Computational Enzyme Redesign Using Transition State Analogues

OptZyme is a new computational procedure for designing improved enzymatic activity (i.e., k_cat or k_cat/K_M) with a novel substrate. The key concept is to use transition state analogue compounds, which are known for many reactions, as proxies for the typically unknown transition state structures. Mutations that minimize the interaction energy of the enzyme with its transition state analogue, rather than with its substrate, are identified that lower the transition state formation energy barrier. Using Escherichia coli β-glucuronidase as a benchmark system, we confirm that K_M correlates (R² = 0.960) with the computed interaction energy between the enzyme and the para-nitrophenyl- β, D-glucuronide substrate, k_cat/K_M correlates (R² = 0.864) with the interaction energy of the transition state analogue, 1,5-glucarolactone, and k_cat correlates (R² = 0.854) with a weighted combination of interaction energies with the substrate and transition state analogue. OptZyme is subsequently used to identify mutants with improved K_M, k_cat, and k_cat/K_M for a new substrate, para-nitrophenyl- β, D-galactoside. Differences between the three libraries reveal structural differences that underpin improving K_M, k_cat, or k_cat/K_M. Mutants predicted to enhance the activity for para-nitrophenyl- β, D-galactoside directly or indirectly create hydrogen bonds with the altered sugar ring conformation or its substituents, namely H162S, L361G, W549R, and N550S.