Computational design and selections for an engineered, thermostable terpene synthase

Decoding Catalysis by Terpene Synthases

The review by Christianson, published in 2017 on the twentieth anniversary of the emergence of the field, summarizes the foundational discoveries and key advances in terpene synthase/cyclase (TS) biocatalysis (Christianson, D. W. Chem Rev2017, 117 (17), 11570-11648. DOI: 10.1021/acs.chemrev.7b00287). Here, we review the TS literature published since then, bringing the field up to date and looking forward to what could be the near future of TS rational design. Many revealing discoveries have been made in recent years, building on the knowledge and fundamental principles uncovered during those initial two decades of study. We use these to explore TS reaction chemistry and see how a combined experimental and computational approach helps to decipher the complexities of TS catalysis. Revealed are a suite of catalytic motifs which control product outcome in TSs, some obvious, some more subtle. We examine each in detail, using the most recent papers and insights to illustrate how exactly this fascinating class of enzymes takes a single acyclic substrate and turns it into the many thousands of complex terpenoids found in Nature. We then explore some of the recent strategies for TS engineering, including machine learning and other data-driven approaches. From this, rational and predictive engineering of TSs, "designer terpene synthases", will begin to emerge as a realistic goal.

Genetically Encoded Detection of Biosynthetic Protease Inhibitors

Proteases are an important class of drug targets that continue to drive inhibitor discovery. These enzymes are prone to resistance mutations, yet their promise for treating viral diseases and other disorders continues to grow. This study develops a general approach for detecting microbially synthesized protease inhibitors and uses it to screen terpenoid pathways for inhibitory compounds. The detection scheme relies on a bacterial two-hybrid (B2H) system that links protease inactivation to the transcription of a swappable reporter gene. This system, which can accomodate multiple biochemical outputs (i.e., luminescence and antibiotic resistance), permitted the facile incorporation of four disease-relevant proteases. A B2H designed to detect the inactivation of the main protease of severe acute respiratory syndrome coronavirus 2 enabled the identification of a terpenoid inhibitor of modest potency. An analysis of multiple pathways that make this terpenoid, however, suggested that its production was necessary but not sufficient to confer a survival advantage in growth-coupled assays. This finding highlights an important challenge associated with the use of genetic selection to search for inhibitors─notably, the influence of pathway toxicity─and underlines the value of including multiple pathways with overlapping product profiles in pathway screens. This study provides a detailed experimental framework for using microbes to screen libraries of biosynthetic pathways for targeted protease inhibitors.

Empirical comparison and analysis of machine learning-based predictors for predicting and analyzing of thermophilic proteins

Thermophilic proteins (TPPs) are critical for basic research and in the food industry due to their ability to maintain a thermodynamically stable fold at extremely high temperatures. Thus, the expeditious identification of novel TPPs through computational models from protein sequences is very desirable. Over the last few decades, a number of computational methods, especially machine learning (ML)-based methods, for in silico prediction of TPPs have been developed. Therefore, it is desirable to revisit these methods and summarize their advantages and disadvantages in order to further develop new computational approaches to achieve more accurate and improved prediction of TPPs. With this goal in mind, we comprehensively investigate a large collection of fourteen state-of-the-art TPP predictors in terms of their dataset size, feature encoding schemes, feature selection strategies, ML algorithms, evaluation strategies and web server/software usability. To the best of our knowledge, this article represents the first comprehensive review on the development of ML-based methods for in silico prediction of TPPs. Among these TPP predictors, they can be classified into two groups according to the interpretability of ML algorithms employed (i.e., computational black-box methods and computational white-box methods). In order to perform the comparative analysis, we conducted a comparative study on several currently available TPP predictors based on two benchmark datasets. Finally, we provide future perspectives for the design and development of new computational models for TPP prediction. We hope that this comprehensive review will facilitate researchers in selecting an appropriate TPP predictor that is the most suitable one to deal with their purposes and provide useful perspectives for the development of more effective and accurate TPP predictors.

Computational Design of Homotetrameric Peptide Bundle Variants Spanning a Wide Range of Charge States

With the ability to design their sequences and structures, peptides can be engineered to realize a wide variety of functionalities and structures. Herein, computational design was used to identify a set of 17 peptides having a wide range of putative charge states but the same tetrameric coiled-coil bundle structure. Calculations were performed to identify suitable locations for ionizable residues (D, E, K, and R) at the bundle's exterior sites, while interior hydrophobic interactions were retained. The designed bundle structures spanned putative charge states of -32 to +32 in units of electron charge. The peptides were experimentally investigated using spectroscopic and scattering techniques. Thermal stabilities of the bundles were investigated using circular dichroism. Molecular dynamics simulations assessed structural fluctuations within the bundles. The cylindrical peptide bundles, 4 nm long by 2 nm in diameter, were covalently linked to form rigid, micron-scale polymers and characterized using transmission electron microscopy. The designed suite of sequences provides a set of readily realized nanometer-scale structures of tunable charge that can also be polymerized to yield rigid-rod polyelectrolytes.

Single-molecule Taq DNA polymerase dynamics

Taq DNA polymerase functions at elevated temperatures with fast conformational dynamics-regimes previously inaccessible to mechanistic, single-molecule studies. Here, single-walled carbon nanotube transistors recorded the motions of Taq molecules processing matched or mismatched template-deoxynucleotide triphosphate pairs from 22° to 85°C. By using four enzyme orientations, the whole-enzyme closures of nucleotide incorporations were distinguished from more rapid, 20-μs closures of Taq's fingers domain testing complementarity and orientation. On average, one transient closure was observed for every nucleotide binding event; even complementary substrate pairs averaged five transient closures between each catalytic incorporation at 72°C. The rate and duration of the transient closures and the catalytic events had almost no temperature dependence, leaving all of Taq's temperature sensitivity to its rate-determining open state.

Colloid-like solution behavior of computationally designed coiled coil bundlemers

The use of isotropic potential models of simple colloids for describing complex protein-protein interactions is a topic of ongoing debate in the biophysical community. This contention stems from the unavailability of synthetic protein-like model particles that are amenable to systematic experimental characterization. In this article, we test the utility of colloidal theory to capture the solution structure, interactions and dynamics of novel globular protein-mimicking, computationally designed peptide assemblies called bundlemers that are programmable model systems at the intersection of colloids and proteins. Small-angle neutron scattering (SANS) measurements of semi-dilute bundlemer solutions in low and high ionic strength solution indicate that bundlemers interact locally via repulsive interactions that can be described by a screened repulsive potential. We also present neutron spin echo (NSE) spectroscopy results that show high-Q freely-diffusive dynamics of bundlemers. Importantly, formation of clusters due to short-range attractive, inter-bundlemer interactions is observed in SANS even at dilute bundlemer concentrations, which is indicative of the complexity of the bundlemer charged surface. The similarities and differences between bundlemers and simple colloidal as well as complex protein-protein interactions is discussed in detail.

A novel sequence-based predictor for identifying and characterizing thermophilic proteins using estimated propensity scores of dipeptides

Owing to their ability to maintain a thermodynamically stable fold at extremely high temperatures, thermophilic proteins (TTPs) play a critical role in basic research and a variety of applications in the food industry. As a result, the development of computation models for rapidly and accurately identifying novel TTPs from a large number of uncharacterized protein sequences is desirable. In spite of existing computational models that have already been developed for characterizing thermophilic proteins, their performance and interpretability remain unsatisfactory. We present a novel sequence-based thermophilic protein predictor, termed SCMTPP, for improving model predictability and interpretability. First, an up-to-date and high-quality dataset consisting of 1853 TPPs and 3233 non-TPPs was compiled from published literature. Second, the SCMTPP predictor was created by combining the scoring card method (SCM) with estimated propensity scores of g-gap dipeptides. Benchmarking experiments revealed that SCMTPP had a cross-validation accuracy of 0.883, which was comparable to that of a support vector machine-based predictor (0.906-0.910) and 2-17% higher than that of commonly used machine learning models. Furthermore, SCMTPP outperformed the state-of-the-art approach (ThermoPred) on the independent test dataset, with accuracy and MCC of 0.865 and 0.731, respectively. Finally, the SCMTPP-derived propensity scores were used to elucidate the critical physicochemical properties for protein thermostability enhancement. In terms of interpretability and generalizability, comparative results showed that SCMTPP was effective for identifying and characterizing TPPs. We had implemented the proposed predictor as a user-friendly online web server at http://pmlabstack.pythonanywhere.com/SCMTPP in order to allow easy access to the model. SCMTPP is expected to be a powerful tool for facilitating community-wide efforts to identify TPPs on a large scale and guiding experimental characterization of TPPs.

Design of a Superpositively Charged Enzyme: Human Carbonic Anhydrase II Variant with Ferritin Encapsulation and Immobilization

Supercharged proteins exhibit high solubility and other desirable properties, but no engineered superpositively charged enzymes have previously been made. Superpositively charged variants of proteins such as green fluorescent protein have been efficiently encapsulated within Archaeoglobus fulgidus thermophilic ferritin (AfFtn). Encapsulation by supramolecular ferritin can yield systems with a variety of sequestered cargo. To advance applications in enzymology and green chemistry, we sought a general method for supercharging an enzyme that retains activity and is compatible with AfFtn encapsulation. The zinc metalloenzyme human carbonic anhydrase II (hCAII) is an attractive encapsulation target based on its hydrolytic activity and physiologic conversion of carbon dioxide to bicarbonate. A computationally designed variant of hCAII contains positively charged residues substituted at 19 sites on the protein's surface, resulting in a shift of the putative net charge from -1 to +21. This designed hCAII(+21) exhibits encapsulation within AfFtn without the need for fusion partners or additional reagents. The hCAII(+21) variant retains esterase activity comparable to the wild type and spontaneously templates the assembly of AfFtn 24mers around itself. The AfFtn-hCAII(+21) host-guest complex exhibits both greater activity and thermal stability when compared to hCAII(+21). Upon immobilization on a solid support, AfFtn-hCAII(+21) retains enzymatic activity and exhibits an enhancement of activity at elevated temperatures.

Rerouting and Improving Dauc-8-en-11-ol Synthase from Streptomyces venezuelae to a High Yielding Biocatalyst

The dauc‐8‐en‐11‐ol synthase from Streptomyces venezuelae was investigated for its catalytic activity towards alternative terpene precursors, specifically designed to enable new cyclisation pathways. Exchange of aromatic amino acid residues at the enzyme surface by site‐directed mutagenesis led to a 4‐fold increase of the yield in preparative scale incubations, which likely results from an increased enzyme stability instead of improved enzyme kinetics.

Stabilizing AqdC, a Pseudomonas Quinolone Signal-Cleaving Dioxygenase from Mycobacteria, by FRESCO-Based Protein Engineering

The mycobacterial PQS dioxygenase AqdC, a cofactor-less protein with an α/β-hydrolase fold, inactivates the virulence-associated quorum-sensing signal molecule 2-heptyl-3-hydroxy-4(1H)-quinolone (PQS) produced by the opportunistic pathogen Pseudomonas aeruginosa and is therefore a potential anti-virulence tool. We have used computational library design to predict stabilizing amino acid replacements in AqdC. While 57 out of 91 tested single substitutions throughout the protein led to stabilization, as judged by increases in T app m of >2 °C, they all impaired catalytic activity. Combining substitutions, the proteins AqdC-G40K-A134L-G220D-Y238W and AqdC-G40K-G220D-Y238W showed extended half-lives and the best trade-off between stability and activity, with increases in T app m of 11.8 and 6.1 °C and relative activities of 22 and 72 %, respectively, compared to AqdC. Molecular dynamics simulations and principal component analysis suggested that stabilized proteins are less flexible than AqdC, and the loss of catalytic activity likely correlates with an inability to effectively open the entrance to the active site.

Germacrene A-A Central Intermediate in Sesquiterpene Biosynthesis

This review summarises known sesquiterpenes whose biosyntheses proceed through the intermediate germacrene A. First, the occurrence and biosynthesis of germacrene A in Nature and its peculiar chemistry will be highlighted, followed by a discussion of 6-6 and 5-7 bicyclic compounds and their more complex derivatives. For each compound the absolute configuration, if it is known, and the reasoning for its assignment is presented.

The heterologous production of terpenes by the thermophile Parageobacillus thermoglucosidasius in a consolidated bioprocess using waste bread

Parageobacillus thermoglucosidasius is a genetically tractable thermophile that grows rapidly at elevated temperatures, with a doubling time at 65 °C comparable to the shortest doubling times of Escherichia coli. It is capable of using a wide variety of substrates, including carbohydrate oligomers, and has been developed for the industrial production of ethanol. In this study, P. thermoglucosidasius NCIMB11955 has been engineered to produce the sesquiterpene τ-muurolol by introduction of a heterologous mevalonate pathway constructed using genes from several thermophilic archaea together with a recently characterised thermostable τ-muurolol synthase. P. thermoglucosidasius naturally uses the methylerythritol phosphate pathway for production of the terpene precursor, isopentenyl pyrophosphate, while archaea use a version of the mevalonate pathway. By introducing the orthogonal archaeal pathway it was possible to increase the flux through to sesquiterpene biosynthesis. Construction of such a large metabolic pathway created problems with genetic vector introduction and stability, so recombinant plasmids were introduced by conjugation, and a thermostable serine integrase system was developed for integration of large pathways onto the chromosome. Finally, by making the heterologous pathway maltose-inducible we demonstrate that the new strain is capable of using waste bread directly as an autoinduction carbon source for the production of terpenes in a consolidated bioprocess.

Protein engineering strategies for microbial production of isoprenoids

Isoprenoids comprise one of the most chemically diverse family of natural products with high commercial interest. The structural diversity of isoprenoids is mainly due to the modular activity of three distinct classes of enzymes, including prenyl diphosphate synthases, terpene synthases, and cytochrome P450s. The heterologous expression of these enzymes in microbial systems is suggested to be a promising sustainable way for the production of isoprenoids. Several limitations are associated with native enzymes, such as low stability, activity, and expression profiles. To address these challenges, protein engineering has been applied to improve the catalytic activity, selectivity, and substrate turnover of enzymes. In addition, the natural promiscuity and modular fashion of isoprenoid enzymes render them excellent targets for combinatorial studies and the production of new-to-nature metabolites. In this review, we discuss key individual and multienzyme level strategies for the successful implementation of enzyme engineering towards efficient microbial production of high-value isoprenoids. Challenges and future directions of protein engineering as a complementary strategy to metabolic engineering are likewise outlined.

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Isoprenoid enzymes are attractive biocatalysts for protein engineering.

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Isoprenoid enzymes can be engineered for broader substrate promiscuity.

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Protein engineering can lead to the production of non-natural isoprenoids.

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Protein engineering can promote co-localization of isoprenoid pathway enzymes.

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Protein engineering supplements combinatorial biosynthesis for isoprenoid synthesis.

Manipulation of the precursor supply for high-level production of longifolene by metabolically engineered Escherichia coli

Longifolene is a naturally occurring tricyclic sesquiterpene widely used in many different fields. Up to now, this valuable terpene was mainly manufactured from the high-boiling fraction of certain pine resins. Microbial production can be a promising alternative to the extraction from natural plant sources. Here, we present the metabolic engineering strategy to assemble biosynthetic pathway for longifolene production in Escherichia coli. E. coli was rendered to produce longifolene by heterologously expressing a codon optimized longifolene synthase from Picea abies. Augmentation of the metabolic flux to farnesyl pyrophosphate (FPP) by different FPP synthases conferred a 1.8-fold increase in longifolene production. An additional enhancement of longifolene production (up to 2.64 mg/L) was achieved by introducing an exogenous mevalonate pathway. Under fed-batch conditions, the best-performing strain was able to produce 382 mg/L of longifolene in a 5 L bioreactor. These results demonstrated the feasibility of producing longifolene by microbial fermentation and could serve as the basis for the construction of more robust strains in the future.

Catalysis of amorpha-4,11-diene synthase unraveled and improved by mutability landscape guided engineering

Amorpha-4,11-diene synthase (ADS) cyclizes the substrate farnesyl pyrophosphate to produce amorpha-4,11-diene as a major product. This is considered the first committed and rate-limiting step in the biosynthesis of the antimalarial artemisinin. Here, we utilize a reported 3D model of ADS to perform mutability landscape guided enzyme engineering. A mutant library of 258 variants along sixteen active site residues was created then screened for catalytic activity and product profile. This allowed for identification of the role of some of these residues in the mechanism. R262 constrains the released pyrophosphate group along with magnesium ions. The aromatic residues (W271, Y519 and F525) stabilize the intermediate carbocations while T296, G400, G439 and L515 help with the 1,6- and 1,10-ring closures. Finally, W271 is suggested to act as active site base along with T399, which ensures regioselective deprotonation. The mutability landscape also helped determine variants with improved catalytic activity. H448A showed ~4 fold increase in catalytic efficiency and the double mutation T399S/H448A improved k_cat by 5 times. This variant can be used to enhance amorphadiene production and in turn artemisinin biosynthesis. Our findings provide the basis for the first step in improving industrial production of artemisinin and they open up possibilities for further engineering and understanding of ADS.

Review: Engineering of thermostable enzymes for industrial applications

The catalytic properties of some selected enzymes have long been exploited to carry out efficient and cost-effective bioconversions in a multitude of research and industrial sectors, such as food, health, cosmetics, agriculture, chemistry, energy, and others. Nonetheless, for several applications, naturally occurring enzymes are not considered to be viable options owing to their limited stability in the required working conditions. Over the years, the quest for novel enzymes with actual potential for biotechnological applications has involved various complementary approaches such as mining enzyme variants from organisms living in extreme conditions (extremophiles), mimicking evolution in the laboratory to develop more stable enzyme variants, and more recently, using rational, computer-assisted enzyme engineering strategies. In this review, we provide an overview of the most relevant enzymes that are used for industrial applications and we discuss the strategies that are adopted to enhance enzyme stability and/or activity, along with some of the most relevant achievements. In all living species, many different enzymes catalyze fundamental chemical reactions with high substrate specificity and rate enhancements. Besides specificity, enzymes also possess many other favorable properties, such as, for instance, cost-effectiveness, good stability under mild pH and temperature conditions, generally low toxicity levels, and ease of termination of activity. As efficient natural biocatalysts, enzymes provide great opportunities to carry out important chemical reactions in several research and industrial settings, ranging from food to pharmaceutical, cosmetic, agricultural, and other crucial economic sectors.

Structural and Chemical Biology of Terpenoid Cyclases

The year 2017 marks the twentieth anniversary of terpenoid cyclase structural biology: a trio of terpenoid cyclase structures reported together in 1997 were the first to set the foundation for understanding the enzymes largely responsible for the exquisite chemodiversity of more than 80000 terpenoid natural products. Terpenoid cyclases catalyze the most complex chemical reactions in biology, in that more than half of the substrate carbon atoms undergo changes in bonding and hybridization during a single enzyme-catalyzed cyclization reaction. The past two decades have witnessed structural, functional, and computational studies illuminating the modes of substrate activation that initiate the cyclization cascade, the management and manipulation of high-energy carbocation intermediates that propagate the cyclization cascade, and the chemical strategies that terminate the cyclization cascade. The role of the terpenoid cyclase as a template for catalysis is paramount to its function, and protein engineering can be used to reprogram the cyclization cascade to generate alternative and commercially important products. Here, I review key advances in terpenoid cyclase structural and chemical biology, focusing mainly on terpenoid cyclases and related prenyltransferases for which X-ray crystal structures have informed and advanced our understanding of enzyme structure and function.

Characterization of the first naturally thermostable terpene synthases and development of strategies to improve thermostability in this family of enzymes

The terpenoid family of natural products is being targeted for heterologous microbial production as a cheaper and more reliable alternative to extraction from plants. The key enzyme responsible for diversification of terpene structure is the class-I terpene synthase (TS), and these often require engineering to improve properties such as thermostability, robustness and catalytic activity before they are suitable for industrial use. Improving thermostability typically relies on screening a large number of mutants, as there are no naturally thermostable TSs described upon which to base rational design decisions. We have characterized the first examples of natural TSs exhibiting thermostability, which catalyse the formation of the sesquiterpene τ-muurolol at temperatures up to 78 °C. We also report an enzyme with a k_cat value of 0.95 s^-1 at 65 °C, the highest k_cat recorded for a bacterial sesquiterpene synthase. In turn, these thermostable enzymes were used as a model to inform the rational engineering of another TS, with the same specificity but low sequence identity to the model. The newly engineered variant displayed increased thermostability and turnover. Given the high structural homology of the class-I TS domain, this approach could be generally applicable to improving the properties of other enzymes in this class.

DATABASE

Model data are available in the PMDB database under the accession number PM0080780.

Ten-Minute Protein Purification and Surface Tethering for Continuous-Flow Biocatalysis

Nature applies enzymatic assembly lines to synthesize bioactive compounds. Inspired by such capabilities, we have developed a facile method for spatially segregating attached enzymes in a continuous-flow, vortex fluidic device (VFD). Fused Hisn -tags at the protein termini allow rapid bioconjugation and consequent purification through complexation with immobilized metal affinity chromatography (IMAC) resin. Six proteins were purified from complex cell lysates to average homogeneities of 76 %. The most challenging to purify, tobacco epi-aristolochene synthase, was purified in only ten minutes from cell lysate to near homogeneity (>90 %). Furthermore, this "reaction-ready" system demonstrated excellent stability during five days of continuous-flow processing. Towards multi-step transformations in continuous flow, proteins were arrayed as ordered zones on the reactor surface allowing segregation of catalysts. Ordering enzymes into zones opens up new opportunities for continuous-flow biosynthesis.

Achievements and Challenges in Computational Protein Design

Computational protein design (CPD), a yet evolving field, includes computer-aided engineering for partial or full de novo designs of proteins of interest. Designs are defined by a requested structure, function, or working environment. This chapter describes the birth and maturation of the field by presenting 101 CPD examples in a chronological order emphasizing achievements and pending challenges. Integrating these aspects presents the plethora of CPD approaches with the hope of providing a "CPD 101". These reflect on the broader structural bioinformatics and computational biophysics field and include: (1) integration of knowledge-based and energy-based methods, (2) hierarchical designated approach towards local, regional, and global motifs and the integration of high- and low-resolution design schemes that fit each such region, (3) systematic differential approaches towards different protein regions, (4) identification of key hot-spot residues and the relative effect of remote regions, (5) assessment of shape-complementarity, electrostatics and solvation effects, (6) integration of thermal plasticity and functional dynamics, (7) negative design, (8) systematic integration of experimental approaches, (9) objective cross-assessment of methods, and (10) successful ranking of potential designs. Future challenges also include dissemination of CPD software to the general use of life-sciences researchers and the emphasis of success within an in vivo milieu. CPD increases our understanding of protein structure and function and the relationships between the two along with the application of such know-how for the benefit of mankind. Applied aspects range from biological drugs, via healthier and tastier food products to nanotechnology and environmentally friendly enzymes replacing toxic chemicals utilized in the industry.

Insights into the Three-Dimensional Structure of Amorpha-4,11-diene Synthase and Probing of Plasticity Residues

Amorphadiene synthase (ADS) is known for its vital role as a key enzyme in the biosynthesis of the antimalarial drug artemisinin. Despite the vast research targeting this enzyme, an X-ray crystal structure of the enzyme has not yet been reported. In spite of the remarkable difference in product profile among various sesquiterpene synthases, they all share a common α-helical fold with many highly conserved regions especially the bivalent metal ion binding motifs. Hence, to better understand the structural basis of the mechanism of ADS, a reliable 3D homology model representing the conformation of the ADS enzyme and the position of its substrate, farnesyl diphosphate, in the active site was constructed. The model was generated using the reported crystal structure of α-bisabolol synthase mutant, an enzyme with high sequence identity with ADS, as a template. Site-directed mutagenesis was used to probe the active site residues. Seven residues were probed showing their vital role in the ADS mechanism and/or their effect on product profile. The generated variants confirmed the validity of the ADS model. This model will serve as a basis for exploring structure-function relationships of all residues in the active site to obtain further insight into the ADS mechanism.

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.

Rapid Bioinformatic Identification of Thermostabilizing Mutations

Ex vivo stability is a valuable protein characteristic but is laborious to improve experimentally. In addition to biopharmaceutical and industrial applications, stable protein is important for biochemical and structural studies. Taking advantage of the large number of available genomic sequences and growth temperature data, we present two bioinformatic methods to identify a limited set of amino acids or positions that likely underlie thermostability. Because these methods allow thousands of homologs to be examined in silico, they have the advantage of providing both speed and statistical power. Using these methods, we introduced, via mutation, amino acids from thermoadapted homologs into an exemplar mesophilic membrane protein, and demonstrated significantly increased thermostability while preserving protein activity.

Biosynthetic potential of sesquiterpene synthases: product profiles of Egyptian Henbane premnaspirodiene synthase and related mutants

The plant terpene synthase (TPS) family is responsible for the biosynthesis of a variety of terpenoid natural products possessing diverse biological functions. TPSs catalyze the ionization and, most commonly, rearrangement and cyclization of prenyl diphosphate substrates, forming linear and cyclic hydrocarbons. Moreover, a single TPS often produces several minor products in addition to a dominant product. We characterized the catalytic profiles of Hyoscyamus muticus premnaspirodiene synthase (HPS) and compared it with the profile of a closely related TPS, Nicotiana tabacum 5-epi-aristolochene synthase (TEAS). The profiles of two previously studied HPS and TEAS mutants, each containing nine interconverting mutations, dubbed HPS-M9 and TEAS-M9, were also characterized. All four TPSs were compared under varying temperature and pH conditions. In addition, we solved the X-ray crystal structures of TEAS and a TEAS quadruple mutant complexed with substrate and products to gain insight into the enzymatic features modulating product formation. These informative structures, along with product profiles, provide new insight into plant TPS catalytic promiscuity.

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants

There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

Improved selectivity of an engineered multi-product terpene synthase

Mutation of the sesquiterpene synthase Cop2 was conducted with a high-throughput screen for the cyclization activity using a non-natural substrate. A mutant of Cop2 was identified that contained three amino acid substitutions. This mutant, 17H2, converted the natural substrate FPP into germacrene D-4-ol with 77% selectivity. This selectivity is in contrast to that of the parent enzyme in which germacrene D-4-ol is produced as 29% and α-cadinol is produced as 46% of the product mixture. The mutations were shown to each contribute to this selectivity, and a homology model suggested that the mutations lie near to the active site though would be unlikely to be targeted for mutation by rational methods. Kinetic comparisons show that 17H2 maintains a kcat/KM of 0.62 mM(-1) s(-1), which is nearly identical to that of the parent Cop2, which had a kcat/KM of 0.58 mM(-1) s(-1).

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

Thermostable artificial enzyme isolated by in vitro selection

Artificial enzymes hold the potential to catalyze valuable reactions not observed in nature. One approach to build artificial enzymes introduces mutations into an existing protein scaffold to enable a new catalytic activity. This process commonly results in a simultaneous reduction of protein stability as an undesired side effect. While protein stability can be increased through techniques like directed evolution, care needs to be taken that added stability, conversely, does not sacrifice the desired activity of the enzyme. Ideally, enzymatic activity and protein stability are engineered simultaneously to ensure that stable enzymes with the desired catalytic properties are isolated. Here, we present the use of the in vitro selection technique mRNA display to isolate enzymes with improved stability and activity in a single step. Starting with a library of artificial RNA ligase enzymes that were previously isolated at ambient temperature and were therefore mostly mesophilic, we selected for thermostable active enzyme variants by performing the selection step at 65°C. The most efficient enzyme, ligase 10C, was not only active at 65°C, but was also an order of magnitude more active at room temperature compared to related enzymes previously isolated at ambient temperature. Concurrently, the melting temperature of ligase 10C increased by 35 degrees compared to these related enzymes. While low stability and solubility of the previously selected enzymes prevented a structural characterization, the improved properties of the heat-stable ligase 10C finally allowed us to solve the three-dimensional structure by NMR. This artificial enzyme adopted an entirely novel fold that has not been seen in nature, which was published elsewhere. These results highlight the versatility of the in vitro selection technique mRNA display as a powerful method for the isolation of thermostable novel enzymes.

Rapid Computational Prediction of Thermostabilizing Mutations for G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are highly dynamic and often denature when extracted in detergents. Deriving thermostable mutants has been a successful strategy to stabilize GPCRs in detergents, but this process is experimentally tedious. We have developed a computational method to predict the position of the thermostabilizing mutations for a given GPCR sequence. We have validated the method against experimentally measured thermostability data for single mutants of the β₁-adrenergic receptor (β₁AR), adenosine A_2A receptor (A_2AR) and neurotensin receptor 1 (NTSR1). To make these predictions we started from homology models of these receptors of varying accuracies and generated an ensemble of conformations by sampling the rigid body degrees of freedom of transmembrane helices. Then, an all-atom force field function was used to calculate the enthalpy gain, known as the “stability score” upon mutation of every residue, in these receptor structures, to alanine. For all three receptors, β₁AR, A_2AR, and NTSR1, we observed that mutations of hydrophobic residues in the transmembrane domain to alanine that have high stability scores correlate with high experimental thermostability. The prediction using the stability score improves when using an ensemble of receptor conformations compared to a single structure, showing that receptor flexibility is important. We also find that our previously developed LITiCon method for generating conformation ensembles is similar in performance to predictions using ensembles obtained from microseconds of molecular dynamics simulations (which is computationally hundred times slower than LITiCon). We improved the thermostability prediction by including other properties such as residue-based stress and the extent of allosteric communication by each residue in the stability score. Our method is the first step toward a computational method for rapid prediction of thermostable mutants of GPCRs.

Computational library design for increasing haloalkane dehalogenase stability

We explored the use of a computational design framework for the stabilization of the haloalkane dehalogenase LinB. Energy calculations, disulfide bond design, molecular dynamics simulations, and rational inspection of mutant structures predicted many stabilizing mutations. Screening of these in small mutant libraries led to the discovery of seventeen point mutations and one disulfide bond that enhanced thermostability. Mutations located in or contacting flexible regions of the protein had a larger stabilizing effect than mutations outside such regions. The combined introduction of twelve stabilizing mutations resulted in a LinB mutant with a 23 °C increase in apparent melting temperature (Tm,app , 72.5 °C) and an over 200-fold longer half-life at 60 °C. The most stable LinB variants also displayed increased compatibility with co-solvents, thus allowing substrate conversion and kinetic resolution at much higher concentrations than with the wild-type enzyme.

A high-throughput colorimetric screening assay for terpene synthase activity based on substrate consumption

Terpene synthases catalyze the formation of a variety of terpene chemical structures. Systematic mutagenesis studies have been effective in providing insights into the characteristic and complex mechanisms of C-C bond formations and in exploring the enzymatic potential for inventing new chemical structures. In addition, there is growing demand to increase terpene synthase activity in heterologous hosts, given the maturation of metabolic engineering and host breeding for terpenoid synthesis. We have developed a simple screening method for the cellular activities of terpene synthases by scoring their substrate consumption based on the color loss of the cell harboring carotenoid pathways. We demonstrate that this method can be used to detect activities of various terpene synthase or prenyltransferase genes in a high-throughput manner, irrespective of the product type, enabling the mutation analysis and directed evolution of terpene synthases. We also report the possibility for substrate-specific screening system of terpene synthases by taking advantage of the substrate-size specificity of C₃₀ and C₄₀ carotenoid pathways.

Computationally designed libraries for rapid enzyme stabilization

The ability to engineer enzymes and other proteins to any desired stability would have wide-ranging applications. Here, we demonstrate that computational design of a library with chemically diverse stabilizing mutations allows the engineering of drastically stabilized and fully functional variants of the mesostable enzyme limonene epoxide hydrolase. First, point mutations were selected if they significantly improved the predicted free energy of protein folding. Disulfide bonds were designed using sampling of backbone conformational space, which tripled the number of experimentally stabilizing disulfide bridges. Next, orthogonal in silico screening steps were used to remove chemically unreasonable mutations and mutations that are predicted to increase protein flexibility. The resulting library of 64 variants was experimentally screened, which revealed 21 (pairs of) stabilizing mutations located both in relatively rigid and in flexible areas of the enzyme. Finally, combining 10-12 of these confirmed mutations resulted in multi-site mutants with an increase in apparent melting temperature from 50 to 85°C, enhanced catalytic activity, preserved regioselectivity and a >250-fold longer half-life. The developed Framework for Rapid Enzyme Stabilization by Computational libraries (FRESCO) requires far less screening than conventional directed evolution.

GroEL/ES buffering and compensatory mutations promote protein evolution by stabilizing folding intermediates

Maintaining stability is a major constraint in protein evolution because most mutations are destabilizing. Buffering and/or compensatory mechanisms that counteract this progressive destabilization during functional adaptation are pivotal for protein evolution as well as protein engineering. However, the interplay of these two mechanisms during a full evolutionary trajectory has never been explored. Here, we unravel such dynamics during the laboratory evolution of a phosphotriesterase into an arylesterase. A controllable GroEL/ES chaperone co-expression system enabled us to vary the selection environment between buffering and compensatory, which smoothened the trajectory along the fitness landscape to achieve a >10(4) increase in arylesterase activity. Biophysical characterization revealed that, in contrast to prevalent models of protein stability and evolution, the variants' soluble cellular expression did not correlate with in vitro stability, and compensatory mutations were linked to a stabilization of folding intermediates. Thus, folding kinetics in the cell are a key feature of protein evolvability.

Modulating protein stability - directed evolution strategies for improved protein function

Protein engineering is widely used to generate proteins with novel or enhanced function. However, manipulating protein function in the laboratory can prove laborious, protracted and challenging. Recent developments in the understanding of protein evolutionary dynamics have unveiled the full extent by which the evolution of function is limited by protein stability - a revelation that may be applied to protein engineering on a whole. Thus, strategies that modulate protein stability and reduce its constraining effects may facilitate the engineering of protein function. A combinatorial approach involving the introduction of compensatory mutations and manipulation of the stability threshold by chaperone buffering during directed evolution can improve the functional adaptation of a protein, thereby fostering our ability to attain ever-more ambitious protein functions in the laboratory.

Structure- and sequence-analysis inspired engineering of proteins for enhanced thermostability

Protein engineering strategies for increasing stability can be improved by replacing random mutagenesis and high-throughput screening by approaches that include bioinformatics and computational design. Mutations can be focused on regions in the structure that are most flexible and involved in the early steps of thermal unfolding. Sequence analysis can often predict the position and nature of stabilizing mutations, and may allow the reconstruction of thermostable ancestral sequences. Various computational tools make it possible to design stabilizing features, such as hydrophobic clusters and surface charges. Different methods for designing chimeric enzymes can also support the engineering of more stable proteins without the need of high-throughput screening.

Integrating the protein and metabolic engineering toolkits for next-generation chemical biosynthesis

Through microbial engineering, biosynthesis has the potential to produce thousands of chemicals used in everyday life. Metabolic engineering and synthetic biology are fields driven by the manipulation of genes, genetic regulatory systems, and enzymatic pathways for developing highly productive microbial strains. Fundamentally, it is the biochemical characteristics of the enzymes themselves that dictate flux through a biosynthetic pathway toward the product of interest. As metabolic engineers target sophisticated secondary metabolites, there has been little recognition of the reduced catalytic activity and increased substrate/product promiscuity of the corresponding enzymes compared to those of central metabolism. Thus, fine-tuning these enzymatic characteristics through protein engineering is paramount for developing high-productivity microbial strains for secondary metabolites. Here, we describe the importance of protein engineering for advancing metabolic engineering of secondary metabolism pathways. This pathway integrated enzyme optimization can enhance the collective toolkit of microbial engineering to shape the future of chemical manufacturing.

Improving thermostability of phosphatidylinositol-synthesizing Streptomyces phospholipase D

Aimed to produce thermostable phosphatidylinositol (PI)-synthesizing phospholipase D (PLD), we initiated site-directed combinatorial mutagenesis followed by high-throughput screening. Previous site-directed combinatorial mutagenesis of wild-type Streptomyces PLD produced a mutant, DYR (W187D/Y191Y/Y385R) with PI-synthesizing ability. Deriving PI as a product of transphosphatidylation between phosphatidylcholine and myo-inositol, with myo-inositol in excess at high-temperature reaction conditions can increase yield due to enhanced solubility of this substrate. Thus, we improved DYR's thermostability by introduction of random mutations into selected amino acid positions having high B-factor. Screening of the libraries under restricted conditions yielded single-point mutants, specifically D40H, T291Y and R329G. Combinations of these point mutations yielded double (D40H/T291Y, D40H/R329G and T291Y/R329G) and triple (D40H/T291Y/R329G) mutants. PI synthesis at elevated temperatures pointed at D40H/T291Y as the most efficient enzyme. Circular dichroism analysis revealed D40H/T291Y to have increased melting temperature and postponed onset of thermal unfolding compared with DYR. Thermal tolerance study at 65°C confirmed D40H/T291Y's thermostability as its half-inactivation time was 8.7 min longer compared with DYR. This mutant had significantly less root-mean-square deviation change compared with DYR and showed no change in root-mean-square fluctuation when temperature shifts from 40 to 60°C, as determined by molecular dynamics analysis. Acquired different degrees of thermostability were also observed for several other DYR mutants.