A matching algorithm for catalytic residue site selection in computational enzyme design

Computational design of carboxylase for the synthesis of 4-hydroxyisophthalic acid from p-hydroxybenzoic acid by fixing CO2

Carbon dioxide (CO2) emissions constitute the primary contribution to global climate change. Synthetic CO2 fixation represents an exceptionally appealing and sustainable method for carbon neutralization. Unlike the limitations of chemical catalysis, biological CO2 fixation displays high selectivity and the ability to operate under mild conditions. The superfamily of amidohydrolases has demonstrated the ability to synthesize a range of aromatic monocarboxylic acids. However, there is a scarcity of reported carboxylases capable of synthesizing aromatic dicarboxylic acids. Among these, 4-hydroxyisophthalic acid holds significant potential for applications across various fields, yet no enzyme has been reported for its synthesis. In this study, we developed for the first time that exhibits starting activity in fixing CO2 to synthesize 4-hydroxyisophthalic acid. Furthermore, we have devised a computational strategy that effectively enhances the catalytic activity of this enzyme. A focused library comprising only 13 variants was generated. Experimental validation confirmed a threefold improvement in the carboxylation activity of the optimal variant (L47M). The computational enzyme design strategy proposed in this paper demonstrates broad applicability in developing carboxylases for synthesizing other aromatic dicarboxylic acids. This lays the groundwork for leveraging biocatalysis in industrial synthesis for CO2 fixation.

Computational design of highly efficient thermostable MHET hydrolases and dual enzyme system for PET recycling

Recently developed enzymes for the depolymerization of polyethylene terephthalate (PET) such as FAST-PETase and LCC-ICCG are inhibited by the intermediate PET product mono(2-hydroxyethyl) terephthalate (MHET). Consequently, the conversion of PET enzymatically into its constituent monomers terephthalic acid (TPA) and ethylene glycol (EG) is inefficient. In this study, a protein scaffold (1TQH) corresponding to a thermophilic carboxylesterase (Est30) was selected from the structural database and redesigned in silico. Among designs, a double variant KL-MHETase (I171K/G130L) with a similar protein melting temperature (67.58 °C) to that of the PET hydrolase FAST-PETase (67.80 °C) exhibited a 67-fold higher activity for MHET hydrolysis than FAST-PETase. A fused dual enzyme system comprising KL-MHETase and FAST-PETase exhibited a 2.6-fold faster PET depolymerization rate than FAST-PETase alone. Synergy increased the yield of TPA by 1.64 fold, and its purity in the released aromatic products reached 99.5%. In large reaction systems with 100 g/L substrate concentrations, the dual enzyme system KL36F achieved over 90% PET depolymerization into monomers, demonstrating its potential applicability in the industrial recycling of PET plastics. Therefore, a dual enzyme system can greatly reduce the reaction and separation cost for sustainable enzymatic PET recycling.

Using High-Throughput Molecular Dynamics Simulation to Enhance the Computational Design of Kemp Elimination Enzymes

Computational enzyme design has been successfully applied to identify new alternatives to natural enzymes for the biosynthesis of important compounds. However, the moderate catalytic activities of de novo designed enzymes indicate that the modeling accuracy of current computational enzyme design methods should be improved. Here, high-throughput molecular dynamics simulations were used to enhance computational enzyme design, thus allowing the identification of variants with higher activities in silico. Different time schemes of high-throughput molecular dynamics simulations were tested to identify the catalytic features of evolved Kemp eliminases. The 20 × 1 ns molecular dynamics simulation scheme was sufficiently accurate and computationally viable to screen the computationally designed massive variants of Kemp elimination enzymes. The developed hybrid computational strategy was used to redesign the most active Kemp eliminase, HG3.17, and five variants were generated and experimentally confirmed to afford higher catalytic efficiencies than that of HG3.17, with one double variant (D52Q/A53S) exhibiting a 55% increase. The hybrid computational enzyme design strategy is general and computationally economical, with which we anticipate the efficient creation of practical enzymes for industrial biocatalysis.

Artificial Enzymes for Diels-Alder Reactions

The Diels-Alder (DA) reaction is a cycloaddition of a conjugated diene and an alkene (dienophile) leading to the formation of a cyclohexene derivative through a concerted mechanism. As DA reactions generally proceed with a high degree of regio- and stereoselectivity, they are widely used in synthetic organic chemistry. Considering eco-conscious public and governmental movements, efforts are now directed towards the development of synthetic processes that meet environmental concerns. Artificial enzymes, which can be developed to catalyze abiotic reactions, appear to be important synthetic tools in the synthetic biology field. This review describes the different strategies used to develop protein-based artificial enzymes for DA reactions, including for in cellulo approaches.

Computational design of new enzymes for hydrolysis and synthesis of third-generation cephalosporin antibiotics

Engineering active sites in inert scaffolds to catalyze chemical transformations with unnatural substrates is still a great challenge for enzyme catalysis. In this research, a p-nitrobenzyl esterase from Bacillus subtilis was identified from the structural database, and a double mutant E115A/E188A was designed to afford catalytic activities toward the hydrolysis of ceftizoxime. A quadruple mutant E115A/E188A/L362S/I270A with enhanced catalytic efficiency was created to catalyze the condensation reaction of ethyl-2-methoxy-amino-2-(2-aminothiazole-4-yl) acetate with 7-amino-3-nor-cephalosporanic acid to produce ceftizoxime in a fully aqueous medium. The catalytic efficiencies of the computationally designed mutants E115A/E188A/L362S/I270A and E115A/Y118 K/E188 V/I270A/L362S can be taken as starting points to further improve their properties towards the practical application in designing more ecology-friendly production of third-generation cephalosporins.

A computational method for design of connected catalytic networks in proteins

Computational design of new active sites has generally proceeded by geometrically defining interactions between the reaction transition state(s) and surrounding side‐chain functional groups which maximize transition‐state stabilization, and then searching for sites in protein scaffolds where the specified side‐chain–transition‐state interactions can be realized. A limitation of this approach is that the interactions between the side chains themselves are not constrained. An extensive connected hydrogen bond network involving the catalytic residues was observed in a designed retroaldolase following directed evolution. Such connected networks could increase catalytic activity by preorganizing active site residues in catalytically competent orientations, and enabling concerted interactions between side chains during catalysis, for example, proton shuffling. We developed a method for designing active sites in which the catalytic side chains, in addition to making interactions with the transition state, are also involved in extensive hydrogen bond networks. Because of the added constraint of hydrogen‐bond connectivity between the catalytic side chains, to find solutions, a wider range of interactions between these side chains and the transition state must be considered. Our new method starts from a ChemDraw‐like two‐dimensional representation of the transition state with hydrogen‐bond donors, acceptors, and covalent interaction sites indicated, and all placements of side‐chain functional groups that make the indicated interactions with the transition state, and are fully connected in a single hydrogen‐bond network are systematically enumerated. The RosettaMatch method can then be used to identify realizations of these fully‐connected active sites in protein scaffolds. The method generates many fully‐connected active site solutions for a set of model reactions that are promising starting points for the design of fully‐preorganized enzyme catalysts.

Computational design of enhanced detoxification activity of a zearalenone lactonase from Clonostachys rosea in acidic medium

Computational design of pH-activity profiles for enzymes is of great importance in industrial applications. In this research, a computational strategy was developed to engineer the pH-activity profile of a zearalenone lactonase (ZHD101) from Clonostachys rosea to promote its activity in acidic medium. The active site pK _a values of ZHD101 were computationally designed by introducing positively charged lysine mutations on the enzyme surface, and the experimental results showed that two variants, M2(D157K) and M9(E171K), increased the catalytic efficiencies of ZHD101 modestly under acidic conditions. Moreover, two variants, M8(D133K) and M9(E171K), were shown to increase the turnover numbers by 2.73 and 2.06-fold with respect to wild type, respectively, though their apparent Michaelis constants were concomitantly increased. These results imply that the active site pK _a value change might affect the pH-activity profile of the enzyme. Our computational strategy for pH-activity profile engineering considers protein stability; therefore, limited experimental validation is needed to discover beneficial mutations under shifted pH conditions.

Using molecular dynamics simulations to evaluate active designs of cephradine hydrolase by molecular mechanics/Poisson–Boltzmann surface area and molecular mechanics/generalized Born surface area methods

The poor predictive accuracy of current computational enzyme design methods has led to low success rates of producing highly active variants that target non-natural substrates. In this report, a quantitative assessment approach based on molecular dynamics (MD) simulations was developed to eliminate false-positive enzyme designs at the computational stage. Taking cephradine hydrolase as an example, the apparent Michaelis binding constant (K_m) and catalytic efficiency (k_cat/K_m) of designed variants were correlated with binding free energies and activation energy barriers, respectively, as calculated by molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) methods with explicit water considered based on general MD simulation protocols. The correlation results showed that both the MM/GBSA and MM/PBSA methods with a protein dielectric constant (ε_p = 4) could rank the variants well based on the predicted binding free energies between enzyme and the substrate. Furthermore, the activation energy barriers calculated by the MM/PBSA method with an ε_p = 24 correlated well with k_cat/K_m. Thus, false-positive variants obtained by the enzyme design program PRODA were eliminated prior to experimentation. Therefore, MD simulation-based quantitative assessment of designed variants greatly enhanced the predictive accuracy of computational enzyme design tools and should facilitate the construction of artificial enzymes with high catalytic activities toward non-natural substrates.

A quantitative assessment method for computational enzyme design was developed to rank the active designs of cephradine hydrolase based on molecular dynamics simulation.

Computational design of cephradine synthase in a new scaffold identified from structural databases

Computational enzyme design exhibits excellent performance for identifying potential scaffolds from structural databases and creating new enzymatic catalysts from naught. Using the active site-matching algorithm ProdaMatch, we identified a new scaffold cocaine esterase from Rhodococcus sp. that showed modest activity (k_cat/K_m = 0.018 M^-1 s^-1) towards the hydrolysis of β-lactam antibiotic cephradine. The identified cocaine esterase scaffold afforded low sequence identity (<30%) with the known β-lactam synthases, such as penicillin G acylase or α-amino acid ester hydrolase, and was able to catalyze the condensation reaction between d-dihydrophenylglycine methyl ester and 7-aminodesacetoxycephalosporanic acid to produce cephradine via a kinetically controlled synthesis. By virtue of the computational enzyme design protocol, hundreds of sequences were predicted in the cocaine esterase scaffold to promote the catalytic activity towards the hydrolytic reaction of cephradine. Moreover, a single mutant (F261T) was experimentally confirmed to have improved the catalytic efficiency by ten times (k_cat/K_m = 0.193 M^-1 s^-1), indicating that the novel scaffold cocaine esterase may be potentially redesigned to become an industrially useful cephradine synthase.

Computational design to improve catalytic activity of cephalosporin C acylase from Pseudomonas strain N176

Engineering enzymes with high catalytic activities using enzyme designin silicoand a limited number of experimental evaluations is the new trend for the discovery of highly efficient biocatalysts.

Computational design of variants for cephalosporin C acylase from Pseudomonas strain N176 with improved stability and activity

In this report, redesigning cephalosporin C acylase from the Pseudomonas strain N176 revealed that the loss of stability owing to the introduced mutations at the active site can be recovered by repacking the nearby hydrophobic core regions. Starting from a quadruple mutant M31βF/H57βS/V68βA/H70βS, whose decrease in stability is largely owing to the mutation V68βA at the active site, we employed a computational enzyme design strategy that integrated design both at hydrophobic core regions for stability enhancement and at the active site for activity improvement. Single-point mutations L154βF, Y167βF, L180βF and their combinations L154βF/L180βF and L154βF/Y167βF/L180βF were found to display improved stability and activity. The two-point mutant L154βF/L180βF increased the protein melting temperature (T _m) by 11.7 °C and the catalytic efficiency V _max/K _m by 57 % compared with the values of the starting quadruple mutant. The catalytic efficiency of the resulting sixfold mutant M31βF/H57βS/V68βA/H70βS/L154βF/L180βF is recovered to become comparable to that of the triple mutant M31βF/H57βS/H70βS, but with a higher T _m. Further experiments showed that single-point mutations L154βF, L180βF, and their combination contribute no stability enhancement to the triple mutant M31βF/H57βS/H70βS. These results verify that the lost stability because of mutation V68βA at the active site was recovered by introducing mutations L154βF and L180βF at hydrophobic core regions. Importantly, mutation V68βA in the six-residue mutant provides more space to accommodate the bulky side chain of cephalosporin C, which could help in designing cephalosporin C acylase mutants with higher activities and the practical one-step enzymatic route to prepare 7-aminocephalosporanic acid at industrial-scale levels.

Use of an Improved Matching Algorithm to Select Scaffolds for Enzyme Design Based on a Complex Active Site Model

Active site preorganization helps native enzymes electrostatically stabilize the transition state better than the ground state for their primary substrates and achieve significant rate enhancement. In this report, we hypothesize that a complex active site model for active site preorganization modeling should help to create preorganized active site design and afford higher starting activities towards target reactions. Our matching algorithm ProdaMatch was improved by invoking effective pruning strategies and the native active sites for ten scaffolds in a benchmark test set were reproduced. The root-mean squared deviations between the matched transition states and those in the crystal structures were < 1.0 Å for the ten scaffolds, and the repacking calculation results showed that 91% of the hydrogen bonds within the active sites are recovered, indicating that the active sites can be preorganized based on the predicted positions of transition states. The application of the complex active site model for de novo enzyme design was evaluated by scaffold selection using a classic catalytic triad motif for the hydrolysis of p-nitrophenyl acetate. Eighty scaffolds were identified from a scaffold library with 1,491 proteins and four scaffolds were native esterase. Furthermore, enzyme design for complicated substrates was investigated for the hydrolysis of cephalexin using scaffold selection based on two different catalytic motifs. Only three scaffolds were identified from the scaffold library by virtue of the classic catalytic triad-based motif. In contrast, 40 scaffolds were identified using a more flexible, but still preorganized catalytic motif, where one scaffold corresponded to the α-amino acid ester hydrolase that catalyzes the hydrolysis and synthesis of cephalexin. Thus, the complex active site modeling approach for de novo enzyme design with the aid of the improved ProdaMatch program is a promising approach for the creation of active sites with high catalytic efficiencies towards target reactions.

Computational strategies for the design of new enzymatic functions

In this contribution, recent developments in the design of biocatalysts are reviewed with particular emphasis in the de novo strategy. Studies based on three different reactions, Kemp elimination, Diels-Alder and Retro-Aldolase, are used to illustrate different success achieved during the last years. Finally, a section is devoted to the particular case of designed metalloenzymes. As a general conclusion, the interplay between new and more sophisticated engineering protocols and computational methods, based on molecular dynamics simulations with Quantum Mechanics/Molecular Mechanics potentials and fully flexible models, seems to constitute the bed rock for present and future successful design strategies.

Computational design of enzyme-ligand binding using a combined energy function and deterministic sequence optimization algorithm

Enzyme amino-acid sequences at ligand-binding interfaces are evolutionarily optimized for reactions, and the natural conformation of an enzyme-ligand complex must have a low free energy relative to alternative conformations in native-like or non-native sequences. Based on this assumption, a combined energy function was developed for enzyme design and then evaluated by recapitulating native enzyme sequences at ligand-binding interfaces for 10 enzyme-ligand complexes. In this energy function, the electrostatic interaction between polar or charged atoms at buried interfaces is described by an explicitly orientation-dependent hydrogen-bonding potential and a pairwise-decomposable generalized Born model based on the general side chain in the protein design framework. The energy function is augmented with a pairwise surface-area based hydrophobic contribution for nonpolar atom burial. Using this function, on average, 78% of the amino acids at ligand-binding sites were predicted correctly in the minimum-energy sequences, whereas 84% were predicted correctly in the most-similar sequences, which were selected from the top 20 sequences for each enzyme-ligand complex. Hydrogen bonds at the enzyme-ligand binding interfaces in the 10 complexes were usually recovered with the correct geometries. The binding energies calculated using the combined energy function helped to discriminate the active sequences from a pool of alternative sequences that were generated by repeatedly solving a series of mixed-integer linear programming problems for sequence selection with increasing integer cuts.

Computational study of a model system of enzyme-mediated [4+2] cycloaddition reaction

A possible mechanistic pathway related to an enzyme-catalyzed [4+2] cycloaddition reac-tion was studied by theoretical calculations at density functional (B3LYP, O3LYP, M062X) and semiempirical levels (PM6-DH2, PM6) performed on a model system. The calculations were carried out for the key [4+2] cycloaddition step considering enzyme-catalyzed biosynthesis of Spinosyn A in a model reaction, where a reliable example of a biological Diels-Alder reaction was reported experimentally. In the present study it was demonstrated that the [4+2] cycloaddition reaction may benefit from moving along the energetically balanced reaction coordinate, which enabled the catalytic rate enhancement of the [4+2] cycloaddition pathway involving a single transition state. Modeling of such a system with coordination of three amino acids indicated a reliable decrease of activation energy by ~18.0 kcal/mol as compared to a non-catalytic transformation.

Evaluation of active designs of cephalosporin C acylase by molecular dynamics simulation and molecular docking

Optimization to identify the global minimum energy conformation sequence in in silico enzyme design is computationally non-deterministic polynomial-time (NP)-hard, with the search time growing exponentially as the number of design sites increases. This drawback forces the modeling of protein-ligand systems to adopt discrete amino acid rotamers and ligand conformers, as well as continuum solvent treatment of the environment; however, such compromises produce large numbers of false positives in sequence selection. In this report, cephalosporin acylase, which catalyzes the hydrolytic reaction of cephalosporin C to 7-aminocephalosporanic acid, was used to investigate the dynamic features of active-site-transition-state complex structures using molecular dynamics (MD) simulations to potentially eliminate false positives. The molecular docking between cephalosporin C and wild type acylase N176 and its eight mutants showed that the rate-limiting step in the hydrolytic reaction of cephalosporin C is the acylation process. MD simulations of the active-site-transition-state complex structures of the acylation processes for N176 and its eight mutants showed that the geometrical constraints between catalytic residues and small molecule transition states are always well maintained during the 20 ns simulation for mutants with higher activities, and more hydrogen bonds between binding residues and functional groups of the ligand side chain in the active pocket are formed for mutants with higher activities. The conformations of the ligand transition states were changed greatly after the simulation. This indicates that the hydrogen bond network between the ligand and protein could be improved to enhance the activity of cephalosporin C acylase in subsequent design.

Identification of protein scaffolds for enzyme design using scaffold selection

The identification of suitable protein structures that can serve as scaffolds for the introduction of catalytic residues is crucial for the design of new enzymes. Here we describe how the automated and rapid scaffold search program ScaffoldSelection can be used to find the best starting points, namely protein structures that are most likely to tolerate the introduction and promote the proper formation of a specific catalytic motif.

Systematic optimization model and algorithm for binding sequence selection in computational enzyme design

A systematic optimization model for binding sequence selection in computational enzyme design was developed based on the transition state theory of enzyme catalysis and graph-theoretical modeling. The saddle point on the free energy surface of the reaction system was represented by catalytic geometrical constraints, and the binding energy between the active site and transition state was minimized to reduce the activation energy barrier. The resulting hyperscale combinatorial optimization problem was tackled using a novel heuristic global optimization algorithm, which was inspired and tested by the protein core sequence selection problem. The sequence recapitulation tests on native active sites for two enzyme catalyzed hydrolytic reactions were applied to evaluate the predictive power of the design methodology. The results of the calculation show that most of the native binding sites can be successfully identified if the catalytic geometrical constraints and the structural motifs of the substrate are taken into account. Reliably predicting active site sequences may have significant implications for the creation of novel enzymes that are capable of catalyzing targeted chemical reactions.

A solvated ligand rotamer approach and its application in computational protein design

The structure-based design of protein-ligand interfaces with respect to different small molecules is of great significance in the discovery of functional proteins. By statistical analysis of a set of protein-ligand complex structures, it was determined that water-mediated hydrogen bonding at the protein-ligand interface plays a crucial role in governing the binding between the protein and the ligand. Based on the novel statistic results, a solvated ligand rotamer approach was developed to explicitly describe the key water molecules at the protein-ligand interface and a water-mediated hydrogen bonding model was applied in the computational protein design context to complement the continuum solvent model. The solvated ligand rotamer approach produces only one additional solvated rotamer for each rotamer in the ligand rotamer library and does not change the number of side-chain rotamers at each protein design site. This has greatly reduced the total combinatorial number in sequence selection for protein design, and the accuracy of the model was confirmed by two tests. For the water placement test, 61% of the crystal water molecules were predicted correctly in five protein-ligand complex structures. For the sequence recapitulation test, 44.7% of the amino acid identities were recovered using the solvated ligand rotamer approach and the water-mediated hydrogen bonding model, while only 30.4% were recovered when the explicitly bound waters were removed. These results indicated that the developed solvated ligand rotamer approach is promising for functional protein design targeting novel protein-ligand interactions.