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

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.

Enhancing cellulosic ethanol production through coevolution of multiple enzymatic characteristics of β-glucosidase from Penicillium oxalicum 16

In previous studies, we isolated a novel β-glucosidase from Penicillium oxalicum 16 (16BGL), which is useful for producing cellulosic ethanol. However, 16BGL has a relatively low enzyme activity and product tolerance; besides, a huge gap exists between the optimum temperature of 16BGL (70 °C) and the fermentation temperature for producing cellulosic ethanol (40 °C). Here, we present a directed evolution-based study, which combines one-round error-prone PCR with three rounds of high-throughput screening, for coevolving multiple enzymatic characteristics of 16BGL. We identified an improved variant Y-1-B1 with a triple mutant (G414S/D421V/T441S). Y-1-B1 had an optimum temperature of 50 °C, much closer to the fermentation temperature. The catalytic efficiency of Y-1-B1 for hydrolyzing pNPG was 1355 mM^-1 s^-1 at 50 °C and pH 5, significantly higher than that of 16BGL (807 mM^-1 s^-1). Y-1-B1 also achieved a slightly reduced strength of product inhibition of 1.1 at a glucose concentration of 20 mM, compared with the ratio of 1.3 for 16BGL. A maximum titer of 6.9 g/L for ethanol production was achieved in the reaction with Y-1-B1, which was 22% higher than that achieved with 16BGL. Structure modeling revealed that the mutations are distant from the active-site pocket. Therefore, we performed molecular dynamics (MD) simulations to understand why these mutations can improve catalytic efficiency. MD simulation revealed that the nucleophilic residue Asp261 had a much closer contact with the glucosidic center of pNPG in the simulation with Y-1-B1 than that with 16BGL, suggesting that the mutant is more favorable for catalysis. KEY POINTS: • Multiple enzymatic properties of Penicillium oxalicum 16 BGL were coevolved. • A catalytically efficient triple mutant G414S/D421V/T441S was reported. • Molecular dynamics simulation supported the enhanced catalytic activity.

Computer-aided engineering of adipyl-CoA synthetase for enhancing adipic acid synthesis

OBJECTIVE

To enhance adipic acid production, a computer-aided approach was employed to engineer the adipyl-CoA synthetase from Thermobifida fusca by combining sequence analysis, protein structure modeling, in silico site-directed mutagenesis, and molecular dynamics simulation.

RESULTS

Two single mutants of T. fusca adipyl-CoA synthetase, E210βN and E210βQ, achieved a specific enzyme activity of 1.95 and 1.84 U/mg, respectively, which compared favorably with the 1.48 U/mg for the wild-type. The laboratory-level fermentation experiments showed that E210βN and E210βQ achieved a maximum adipic acid titer of 0.32 and 0.3 g/L. In contrast, the wild-type enzyme yielded a titer of 0.15 g/L under the same conditions. Molecular dynamics (MD) simulations revealed that the mutants (E210βN and E210βQ) could accelerate the dephosphorylation process in catalysis and enhance enzyme activity.

CONCLUSIONS

The combined computational-experimental approach provides an effective strategy for enhancing enzymatic characteristics, and the mutants may find a useful application for producing adipic acid.

Co-evolution of β-glucosidase activity and product tolerance for increasing cellulosic ethanol yield

β-Glucosidase (BGL) plays a key role in cellulose hydrolysis. However, it is still a great challenge to enhance product tolerance and enzyme activity of BGL simultaneously. Here, we utilized one round error-prone PCR to engineer the Penicillium oxalicum 16 BGL (16BGL) for improving the cellulosic ethanol yield. We identified a new variant (L-6C), a triple mutant (M280T/V484L/D589E), with enhanced catalytic efficiency ([Formula: see text]) for hydrolyzing pNPG and reduced strength of inhibition ([Formula: see text]) by glucose. To be specific, L-6C achieved a [Formula: see text] of 0.35 at a glucose concentration of 20 mM, which was 3.63 times lower than that attained by 16BGL. The catalytic efficiency for L-6C to hydrolyze pNPG was determined to be 983.68 mM^-1 s^-1, which was 22% higher than that for 16BGL. However, experiments showed that L-6C had reduced binding affinity (2.88 mM) to pNGP compared with 16BGL (1.69 mM). L-6C produced 6.15 g/L ethanol whose yield increased by about 10% than 16BGL. We performed molecular docking and molecular dynamics (MD) simulation, and binding free energy calculation using the Molecular Mechanics/Poisson Boltzmann surface area (MM/PBSA) method. MD simulation together with the MM/PBSA calculation suggested that L-6C had reduced binding free energy to pNPG, which was consistent with the experimental data.

Toward the Accuracy and Speed of Protein Side-Chain Packing: A Systematic Study on Rotamer Libraries

Protein rotamers refer to the conformational isomers taken by the side-chains of amino acids to accommodate specific structural folding environments. Since accurate modeling of atomic interactions is difficult, rotamer information collected from experimentally solved protein structures is often used to guide side-chain packing in protein folding and sequence design studies. Many rotamer libraries have been built in the literature but there is little quantitative guidance on which libraries should be chosen for different structural modeling studies. Here, we performed a comparative study of six widely used rotamer libraries and systematically examined their suitability for protein folding and sequence design in four aspects: (1) side-chain match accuracy, (2) side-chain conformation prediction, (3) de novo protein sequence design, and (4) computational time cost. We demonstrated that, compared to the backbone-dependent rotamer libraries (BBDRLs), the backbone-independent rotamer libraries (BBIRLs) generated conformations that more closely matched the native conformations due to the larger number of rotamers in the local rotamer search spaces. However, more practically, using an optimized physical energy function incorporated into a simulated annealing Monte Carlo searching scheme, we showed that utilization of the BBDRLs could result in higher accuracies in side-chain prediction and higher sequence recapitulation rates in protein design experiments. Detailed data analyses showed that the major advantage of BBDRLs lies in the energy term derived from the rotamer probabilities that are associated with the individual backbone torsion angle subspaces. This term is important for distinguishing between amino acid identities as well as the rotamer conformations of an amino acid. Meanwhile, the backbone torsion angle subspace-specific rotamer search drastically speeds up the searching time, despite the significantly larger number of total rotamers in the BBDRLs. These results should provide important guidance for the development and selection of rotamer libraries for practical protein design and structure prediction studies.

Strategy for the Biosynthesis of Short Oligopeptides: Green and Sustainable Chemistry

Short oligopeptides are some of the most promising and functionally important amide bond-containing components, with widespread applications. Biosynthesis of these oligopeptides may potentially become the ultimate strategy because it has better cost efficiency and environmental-friendliness than conventional solid phase peptide synthesis and chemo-enzymatic synthesis. To successfully apply this strategy for the biosynthesis of structurally diverse amide bond-containing components, the identification and selection of specific biocatalysts is extremely important. Given that perspective, this review focuses on the current knowledge about the typical enzymes that might be potentially used for the synthesis of short oligopeptides. Moreover, novel enzymatic methods of producing desired peptides via metabolic engineering are highlighted. It is believed that this review will be helpful for technological innovation in the production of desired peptides.

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.

In silico methods for design of biological therapeutics

It has been twenty years since the first rationally designed small molecule drug was introduced into the market. Since then, we have progressed from designing small molecules to designing biotherapeutics. This class of therapeutics includes designed proteins, peptides and nucleic acids that could more effectively combat drug resistance and even act in cases where the disease is caused because of a molecular deficiency. Computational methods are crucial in this design exercise and this review discusses the various elements of designing biotherapeutic proteins and peptides. Many of the techniques discussed here, such as the deterministic and stochastic design methods, are generally used in protein design. We have devoted special attention to the design of antibodies and vaccines. In addition to the methods for designing these molecules, we have included a comprehensive list of all biotherapeutics approved for clinical use. Also included is an overview of methods that predict the binding affinity, cell penetration ability, half-life, solubility, immunogenicity and toxicity of the designed therapeutics. Biotherapeutics are only going to grow in clinical importance and are set to herald a new generation of disease management and cure.

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.