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

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.

Computational redesign of cytochrome P450 CYP102A1 for highly stereoselective omeprazole hydroxylation by UniDesign

Cytochrome P450 CYP102A1 is a prototypic biocatalyst that has great potential in chemical synthesis, drug discovery, and biotechnology. CYP102A1 variants engineered by directed evolution and/or rational design are capable of catalyzing the oxidation of a wide range of organic compounds. However, it is difficult to foresee the outcome of engineering CYP102A1 for a compound of interest. Here, we introduce UniDesign as a computational framework for enzyme design and engineering. We tested UniDesign by redesigning CYP102A1 for stereoselective metabolism of omeprazole (OMP), a proton pump inhibitor, starting from an active but nonstereoselective triple mutant (TM: A82F/F87V/L188Q). To shift stereoselectivity toward (R)-OMP, we computationally scanned three active site positions (75, 264, and 328) for mutations that would stabilize the binding of the transition state of (R)-OMP while destabilizing that of (S)-OMP and picked three variants, namely UD1 (TM/L75I), UD2 (TM/A264G), and UD3 (TM/A328V), for experimentation, based on computed energy scores and models. UD1, UD2, and UD3 exhibit high turnover rates of 55 ± 4.7, 84 ± 4.8, and 79 ± 5.7 min-1, respectively, for (R)-OMP hydroxylation, whereas the corresponding rates for (S)-OMP are only 2.2 ± 0.19, 6.0 ± 0.68, and 14 ± 2.8 min-1, yielding an enantiomeric excess value of 92, 87, and 70%, respectively. These results suggest the critical roles of L75I, A264G, and A328V in steering OMP in the optimal orientation for stereoselective oxidation and demonstrate the utility of UniDesign for engineering CYP102A1 to produce drug metabolites of interest. The results are discussed in the context of protein structures.

Decoding CRISPR-Cas PAM recognition with UniDesign

The critical first step in Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated (CRISPR-Cas) protein-mediated gene editing is recognizing a preferred protospacer adjacent motif (PAM) on target DNAs by the protein's PAM-interacting amino acids (PIAAs). Thus, accurate computational modeling of PAM recognition is useful in assisting CRISPR-Cas engineering to relax or tighten PAM requirements for subsequent applications. Here, we describe a universal computational protein design framework (UniDesign) for designing protein-nucleic acid interactions. As a proof of concept, we applied UniDesign to decode the PAM-PIAA interactions for eight Cas9 and two Cas12a proteins. We show that, given native PIAAs, the UniDesign-predicted PAMs are largely identical to the natural PAMs of all Cas proteins. In turn, given natural PAMs, the computationally redesigned PIAA residues largely recapitulated the native PIAAs (74% and 86% in terms of identity and similarity, respectively). These results demonstrate that UniDesign faithfully captures the mutual preference between natural PAMs and native PIAAs, suggesting it is a useful tool for engineering CRISPR-Cas and other nucleic acid-interacting proteins. UniDesign is open-sourced at https://github.com/tommyhuangthu/UniDesign.

Optimization of Cephalosporin C Acylase Expression in Escherichia coli by High-Throughput Screening a Constitutive Promoter Mutant library

Cephalosporin C acylase (CCA) is capable of catalyzing cephalosporin C (CPC) to produce 7-aminocephalosporanic acid (7-ACA), an intermediate of semi-synthetic cephalosporins. Inducible expression is usually used for CCA. To improve the efficiency of CCA expression without gene induction, three recombinant strains regulated by constitutive promoters BBa_J23105, PLtetO1, and tac were constructed, respectively. Among them, BBa_J23105 was the best promoter and its mutant libraries were established using saturation mutagenesis. In order to obtain the mutants with enhanced activity, a high-throughput screening method based on flow cytometric sorting techniques was developed by using green fluorescent protein (GFP) as the reporter gene. A series of mutants were screened at 28 °C, 200 rpm, and 24-h culture condition. The study of mutants showed that the enzyme activity, fluorescence intensity, and promoter transcriptional strength were positively correlated. The enzyme activity of the optimal mutant obtained by screening reached 12772 U/L, 3.47 times that of the original strain.

FASPR: an open-source tool for fast and accurate protein side-chain packing

MOTIVATION

Protein structure and function are essentially determined by how the side-chain atoms interact with each other. Thus, accurate protein side-chain packing (PSCP) is a critical step toward protein structure prediction and protein design. Despite the importance of the problem, however, the accuracy and speed of current PSCP programs are still not satisfactory.

RESULTS

We present FASPR for fast and accurate PSCP by using an optimized scoring function in combination with a deterministic searching algorithm. The performance of FASPR was compared with four state-of-the-art PSCP methods (CISRR, RASP, SCATD and SCWRL4) on both native and non-native protein backbones. For the assessment on native backbones, FASPR achieved a good performance by correctly predicting 69.1% of all the side-chain dihedral angles using a stringent tolerance criterion of 20°, compared favorably with SCWRL4, CISRR, RASP and SCATD which successfully predicted 68.8%, 68.6%, 67.8% and 61.7%, respectively. Additionally, FASPR achieved the highest speed for packing the 379 test protein structures in only 34.3 s, which was significantly faster than the control methods. For the assessment on non-native backbones, FASPR showed an equivalent or better performance on I-TASSER predicted backbones and the backbones perturbed from experimental structures. Detailed analyses showed that the major advantage of FASPR lies in the optimal combination of the dead-end elimination and tree decomposition with a well optimized scoring function, which makes FASPR of practical use for both protein structure modeling and protein design studies.

AVAILABILITY AND IMPLEMENTATION

The web server, source code and datasets are freely available at https://zhanglab.ccmb.med.umich.edu/FASPR and https://github.com/tommyhuangthu/FASPR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Marine-polysaccharide degrading enzymes: Status and prospects

Marine-polysaccharide degrading enzymes have recently been studied extensively. They are particularly interesting as they catalyze the cleavage of glycosidic bonds in polysaccharide macromolecules and produce oligosaccharides with low degrees of polymerization. Numerous findings have demonstrated that marine polysaccharides and their biotransformed products possess beneficial properties including antitumor, antiviral, anticoagulant, and anti-inflammatory activities, and they have great value in healthcare, cosmetics, the food industry, and agriculture. Exploitation of enzymes that can degrade marine polysaccharides is in the ascendant, and is important for high-value use of marine biomass resources. In this review, we describe research and prospects regarding the classification, biochemical properties, and catalytic mechanisms of the main types of marine-polysaccharide degrading enzymes, focusing on chitinase, chitosanase, alginate lyase, agarase, and carrageenase, and their product oligosaccharides. The state-of-the-art discussion of marine-polysaccharide degrading enzymes and their properties offers information that might enable more efficient production of marine oligosaccharides. We also highlight current problems in the field of marine-polysaccharide degrading enzymes and trends in their development. Understanding the properties, catalytic mechanisms, and modification of known enzymes will aid the identification of novel enzymes to degrade marine polysaccharides and facilitation of their use in various biotechnological processes.

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.

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.

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.

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.