We review the standard model for de novo computational design of enzymes, which primarily focuses on the development of an active-site geometry, composed of protein functional groups in orientations optimized to stabilize the transition state, for a novel chemical reaction not found in nature. Its emphasis is placed on the structure and energetics of the active site embedded in an accommodating protein that serves as a physical support that shields the reaction chemistry from solvent, which is typically improved upon by laboratory-directed evolution. We also provide a review of design strategies that move beyond the standard model, by placing more emphasis on the designed enzyme as a whole catalytic construct. Starting with complete de novo enzyme design examples, we consider additional design factors such as entropy of individual residues, correlated motion between side chains (mutual information), dynamical correlations of the enzyme motions that could aid the reaction, reorganization energy, and electric fields as ways to exploit the entire protein scaffold to improve upon the catalytic rate, thereby providing directed evolution with better starting sequences for increasing biocatalytic performance.

Tetrahedral assemblies of stoichiometry M₄L₆ have been proven to catalyze a range of chemical reactions including the carbon-carbon reductive elimination reaction from transition metals such as gold. Here, we perform quantum chemical calculations of Gold(III) transition metal complexes in vacuum, and encapsulated in Ga₄L₆^12- or Si₄L₆^8- assemblies within both a reaction field continuum solvent and in an aqueous molecular environment with counterions, to rationalize the rate enhancements observed experimentally for the reductive elimination reaction. We find that the Ga₄L₆^12- assembly lowers the energy barrier of the reaction compared to Si₄L₆^8-, which is consistent with kinetic trends observed experimentally. We have determined that the primary factor for catalytic rate acceleration stems from the electrostatic environment emanating from the Ga₄L₆^12- capsule as opposed to the water or counterions.

Supramolecular assemblies have gained tremendous attention due to their ability to catalyze reactions with the efficiencies of natural enzymes. Using ab initio molecular dynamics, we identify the origin of the catalysis by the supramolecular capsule Ga₄L₆^12- on the reductive elimination reaction from gold complexes and assess their similarity to natural enzymes. By comparing the free energies of the reactants and transition states for the catalyzed and uncatalyzed reactions, we determine that an encapsulated water molecule generates electric fields that contributes the most to the reduction in the activation free energy. Although this is unlike the biomimetic scenario of catalysis through direct host-guest interactions, the electric fields from the nanocage also supports the transition state to complete the reductive elimination reaction with greater catalytic efficiency. However it is also shown that the nanocage poorly organizes the interfacial water, which in turn creates electric fields that misalign with the breaking bonds of the substrate, thus identifying new opportunities for catalytic design improvements in nanocage assemblies.

Although the ubiquitous role that long-ranged electric fields play in catalysis has been recognized, it is seldom used as a primary design parameter in the discovery of new catalytic materials. Here we illustrate how electric fields have been used to computationally optimize biocatalytic performance of a synthetic enzyme, and how they could be used as a unifying descriptor for catalytic design across a range of homogeneous and heterogeneous catalysts. Although focusing on electrostatic environmental effects may open new routes toward the rational optimization of efficient catalysts, much more predictive capacity is required of theoretical methods to have a transformative impact in their computational design — and thus experimental relevance — when using electric field alignments in the reactive centres of complex catalytic systems.

This work considers the evaluation of density functional theory (DFT) when comparing against experimental observations of CO binding trends on the strong binding Pt(111) and intermediate binding Cu(111) and for weak binding Ag(111) and Au(111) surfaces important in electrocatalysis. By introducing thermal fluctuations using appropriate statistical mechanical NVT and NPT ensembles, we find that the RPBE and B97M-rV DFT functionals yield qualitatively better metal surface strain trends and CO enthalpies of binding for Cu(111) and Pt(111) than found at 0 K, thereby correcting the overbinding by 0.2 to 0.3 eV to yield better agreement with the enthalpies determined from experiment. The importance of dispersion effects are manifest for the weak CO binding Ag(111) and Au(111) surfaces at finite temperatures in which the RPBE functional does not bind CO at all, while the B97M-rV functional shows that the CO-metal interactions are a mixture of chemisorbed and physisorbed species with binding enthalpies that are within ∼0.05 eV of experiment. Across all M(111) surfaces, we show that the B97M-rV functional consistently predicts the correct atop site preference for all metals due to thermally induced surface distortions that preferentially favor the undercoordinated site. This study demonstrates the need to fully account for finite temperature fluctuations to make contact with the binding enthalpies from surface science experiments and electrocatalysis applications.

Density Functional Theory (DFT) is currently the most tractable choice of theoretical model used to understand the mechanistic pathways for electrocatalytic processes such as CO₂ or CO reduction. Here, we assess the performance of two DFT functionals designed specifically to describe surface interactions, RTPSS and RPBE, as well as two popular meta-GGA functionals, SCAN and B97M-rV, that have not been a priori optimized for better interfacial properties. We assess all four functionals against available experimental data for prediction of bulk and bare surface properties on four electrocatalytically relevant metals, Au, Ag, Cu, and Pt, and for binding CO to surfaces of these metals. To partially mitigate issues such as thermal and anharmonic corrections associated with comparing computations with experiments, molecular benchmarks against high level quantum chemistry are reported for CO complexes with Au, Ag, Cu and Pt atoms, as well as the CO-water complex and the water dimer. Overall, we find that the surface modified RPBE functional performs reliably for many of the benchmarks examined here, and the meta-GGA functionals also show promising results. Specifically B97M-rV predicts the correct site preference for CO binding on Ag and Au (the only functional tested here to do so), while RTPSS performs well for surface relaxations and binding of CO on Pt and Cu.