Adaptive landscape flattening allows the design of both enzyme:substrate binding and catalytic power

Abstract

Designed enzymes are of fundamental and technological interest. Experimental directed evolution still has significant limitations, and computational approaches are complementary. A designed enzyme should satisfy multiple criteria: stability, substrate binding, transition state binding. Such multi-objective design is computationally challenging. Two recent studies used adaptive importance sampling Monte Carlo to redesign proteins for ligand binding. By first flattening the energy landscape of the apo protein, they obtained positive design for the bound state and negative design for the unbound. We extend the method to the design of an enzyme for specific transition state binding, i.e., for catalytic power. We consider methionyl-tRNA synthetase (MetRS), which attaches methionine (Met) to its cognate tRNA, helping establishing codon identity. MetRS and other synthetases have been extensively redesigned by experimental directed evolution to accept noncanonical amino acids as substrates, leading to genetic code expansion. We redesigned MetRS computationally to bind several ligands: the Met analog azidonorleucine, methionyl-adenylate (MetAMP), and the activated ligands that form the transition state for MetAMP production. Enzyme mutants known to have azidonorleucine activity were recovered, and mutants predicted to bind MetAMP were characterized experimentally and found to be active. Mutants predicted to have low activation free energies for MetAMP production were found to be active and the predicted reaction rates agreed well with the experimental values. We expect the present method will become the paradigm for computational enzyme design.

Proteus software for physics-based protein design

“…Now, thanks to the new adaptive MC procedure, 41 we can use more relevant quantities. We can directly target the substrate affinity, the catalytic rate, or the catalytic efficiency, which is the ratio of the rate and the Michaelis constant, and closely approximates the second order rate constant.…”

“…which can be interpreted as the free energy to bind and activate the substrate S. 41,54 Specificities are characterized by the free energy difference ∆G eff (S) − ∆G eff (S ), where S and S are the target and reference ligands, respectively. The upper section of Table 5 lists the top sequences obtained with specificity for L-Tyr as the design criterion.…”

“…56 Adaptive Wang-Landau MC is even more versatile, and was used to obtain conformational free energies, 38 acid/base constants, 57 relative binding constants, catalytic rates, and catalytic efficiencies. 41 Many capabilities were illustrated by the TyrRS design, above.…”

“…The first application was reported very recently. 41 Another is given in Results, where the tyrosyl-tRNA synthetase enzyme is redesigned to maximize activity towards the D-tyrosine substrate, instead of the usual L-tyrosine.…”

“…The bias potential contains terms associated with each mutating position and possibly pairs of positions. 41 The individual terms are updated at regular intervals of length T . At each update, whichever sequence variant…”