Catalysis by a De Novo Zinc-Mediated Protein Interface: Implications for Natural Enzyme Evolution and Rational Enzyme Engineering

Here we show that a recent computationally designed zinc-mediated protein interface is serendipitously capable of catalyzing carboxyester and phosphoester hydrolysis. Although the original motivation was to design a de novo zinc-mediated protein–protein interaction (called MID1-zinc), we observed in the homodimer crystal structure a small cleft and open zinc coordination site. We investigated if the cleft and zinc site at the designed interface were sufficient for formation of a primitive active site that can perform hydrolysis. MID1-zinc hydrolyzes 4-nitrophenyl acetate with a rate acceleration of 10⁵ and a <i>k</i>_cat/<i>K</i>_M of 630 M^–1 s^–1 and 4-nitrophenyl phosphate with a rate acceleration of 10⁴ and a <i>k</i>_cat/<i>K</i>_M of 14 M^–1 s^–1. These rate accelerations by an unoptimized active site highlight the catalytic power of zinc and suggest that the clefts formed by protein–protein interactions are well-suited for creating enzyme active sites. This discovery has implications for protein evolution and engineering: from an evolutionary perspective, three-coordinated zinc at a homodimer interface cleft represents a simple evolutionary path to nascent enzymatic activity; from a protein engineering perspective, future efforts in de novo design of enzyme active sites may benefit from exploring clefts at protein interfaces for active site placement

The structure of calpain and calpastatin.

<p>(A)The calpain-1 DI-DVI (green) with calpain-4 DVI (cyan) with a calpastatin subdomains A,B, and C (magenta). Dashed lines are where there was no density in the crystal structure for calpastatin. (B) Enlarged view of the interaction between subdomain C of calpastatin and DVI of calpain-4 indicated in A by black square.</p

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein–protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics

Weights on the stock Rosetta energy function and on the modified energy function.

<p>Weights on the stock Rosetta energy function and on the modified energy function.</p

Rosetta predictions for experimentally tested calpain/calpastatin interface redesigns.

<p>Calpain is shown in cyan and calpastatin is shown in magenta, with the calpastatin position shown in yellow. Rosetta predictions for calpastatin position 607, wild type serine (A), amino-butyeiric acid (B), norvaline (C). Rosetta predictions for calpastatin position 609, wild type aspartic acid (D), 1-methyl-histidine (E), and homoserine (F). Rosetta predictions for calpastatin position 610, wild type phenylalanine (G), and 4-methyl-phenyl-alanine (H). Comparison of the PD150560 (yellow) inhibitor and predicted conformation of the 4-methyl-phenyl-alanine mutation at position 610 (I). The structure of 4-methyl-phenylalanine closely resembles that of the inhibitor and the orientation of PD150560 is identical to the predicted binding mode of the 4-methyl-phenylalanine.</p

The structures of the example NCCA side chains.

<p>The structure of α-methyl-tryptophan is shown in a dipeptide context with φ = −150 and ψ = 150 (A). Plots of backbone the energy landscape of α-methyl-tryptophan and tryptophan (left) and canonical tryptophan (right) as calculated by Rosetta (B). Calculations were done in a didpeptide context where the backbone φ and ψ were fixed, the side chain was repacked and minimized for each φ and ψ bin in 5 degree intervals. Colors represent energy of the didpeptide in kcals/mol with red being the lowest energy and most preferred backbone conformation. The structure of homoserine in a didpeptide context with φ = −150 and ψ = 150 (C). The structure of 2-indynal-glycine is shown in a dipeptide context with φ = −150 and ψ = 150 (D). The different pucker state of the five member ring of 2-indynal glycine are modeled as separate amino acid type by Rosetta because of the difficulty in using rotamer libraries to capture coordinated movements that involved simultaneous rotation about multiple dihedral angles. There is a 1.45 kcal/mol energy difference between the “exo” conformer (left) and the “endo” conformer (right) with the “endo” conformer lower in energy.</p

Comparison of the top 95% of CAA rotamers predicted by the MakeRotLib protocol to the rotamers given by the Dunbrack rotamer library.

<p>Low, high, and average values (see methods) are calculated over all φ/ψ bins where the Dunbrack rotamer library reports more than 10 observations. A high percent overlap (see methods) indicates that the rotamers predicted by the MakeRotLib protocol are in agreement with the rotamers predicted by the Dunbrack rotamer library. A low average RMS distance indicates that the dihedral angles for rotamer bins that overlap are in good agreement.</p

Summary of the Rosetta energy predictions for the redesign of the calpain/calpastatin interface and experimentally determined disassociation constants.

<p>Summary of the Rosetta energy predictions for the redesign of the calpain/calpastatin interface and experimentally determined disassociation constants.</p

Percent overlap and RMS distance for the top 95% of rotamers between the Dunbrack rotamer library and the rotamer predicted by the MakeRotLib protocol for leucine.

<p>(A,B), asparagine (C,D), and phenylalanine (E,F). For each φ/ψ bin with more than 10 observations in the Dunbrack rotamer library, the percent overlap between the rotamer bins that comprise the top 95% of rotamer bins is calculated. For each pair of rotamer bins that overlap the root mean square distance in degrees is calculated. See methods for additional details on creation and results for details on analysis. A full description of how overlap and RMSD are calculated, given two rotamer sets for a given residue, are provided in the methods section.</p

The rotamers of 2-indanyl-glycine predicted by the MakeRotLib protocol with the rotamer for valine from the Dunbrack rotamer library for β-strand and α-helical φ and ψ.

<p>The rotamers of 2-indanyl-glycine predicted by the MakeRotLib protocol with the rotamer for valine from the Dunbrack rotamer library for β-strand and α-helical φ and ψ.</p