Simultaneous use of in silico design and a correlated mutation network as a tool to efficiently guide enzyme engineering

Evolutionary coupling-inspired engineering of alcohol dehydrogenase reveals the influence of distant sites on its catalytic efficiency for stereospecific synthesis of chiral alcohols

Alcohol dehydrogenase (ADH) has attracted much attention due to its ability to catalyze the synthesis of important chiral alcohol pharmaceutical intermediates with high stereoselectivity. ADH protein engineering efforts have generally focused on reshaping the substrate-binding pocket. However, distant sites outside the pocket may also affect its activity, although the underlying molecular mechanism remains unclear. The current study aimed to apply evolutionary coupling-inspired engineering to the ADH CpRCR and to identify potential mutation sites. Through conservative analysis, phylogenic analysis and residues distribution analysis, the co-evolution hotspots Leu34 and Leu137 were confirmed to be highly evolved under the pressure of natural selection and to be possibly related to the catalytic function of the protein. Hence, Leu34 and Leu137, far away from the active center, were selected for mutation. The generated CpRCR-L34A and CpRCR-L137V variants showed high stereoselectivity and 1.24-7.81 fold increase in k cat /K m value compared with that of the wild type, when reacted with 8 aromatic ketones or β-ketoesters. Corresponding computational study implied that L34 and L137 may extend allosteric fluctuation in the protein structure from the distal mutational site to the active site. Moreover, the L34 and L137 mutations modified the pre-reaction state in multiple ways, in terms of position of the hydride with respect to the target carbonyl. These findings provide insights into the catalytic mechanism of the enzyme and facilitate its regulation from the perspective of the site interaction network.

Structure and evolutionary trace-assisted screening of a residue swapping the substrate ambiguity and chiral specificity in an esterase

Our understanding of enzymes with high substrate ambiguity remains limited because their large active sites allow substrate docking freedom to an extent that seems incompatible with stereospecificity. One possibility is that some of these enzymes evolved a set of evolutionarily fitted sequence positions that stringently allow switching substrate ambiguity and chiral specificity. To explore this hypothesis, we targeted for mutation a serine ester hydrolase (EH3) that exhibits an impressive 71-substrate repertoire but is not stereospecific (e.e. 50%). We used structural actions and the computational evolutionary trace method to explore specificity-swapping sequence positions and hypothesized that position I244 was critical. Driven by evolutionary action analysis, this position was substituted to leucine, which together with isoleucine appears to be the amino acid most commonly present in the closest homologous sequences (max. identity, ca. 67.1%), and to phenylalanine, which appears in distant homologues. While the I244L mutation did not have any functional consequences, the I244F mutation allowed the esterase to maintain a remarkable 53-substrate range while gaining stereospecificity properties (e.e. 99.99%). These data support the possibility that some enzymes evolve sequence positions that control the substrate scope and stereospecificity. Such residues, which can be evolutionarily screened, may serve as starting points for further designing substrate-ambiguous, yet chiral-specific, enzymes that are greatly appreciated in biotechnology and synthetic chemistry.

Tuning the Properties of Natural Promiscuous Enzymes by Engineering Their Nano-environment

Owing to their outstanding catalytic properties, enzymes represent powerful tools for carrying out a wide range of (bio)chemical transformations with high proficiency. In this context, enzymes with high biocatalytic promiscuity are somewhat neglected. Here, we demonstrate that a meticulous modification of a synthetic shell that surrounds an immobilized enzyme possessing broad substrate specificity allows the resulting nanobiocatalyst to be endowed with enantioselective properties while maintaining a high level of substrate promiscuity. Our results show that control of the enzyme nano-environment enables tuning of both substrate specificity and enantioselectivity. Further, we demonstrate that our strategy of enzyme supramolecular engineering allows the enzyme to be endowed with markedly enhanced stability in an organic solvent (i.e., acetonitrile). The versatility of the method was assessed with two additional substrate-promiscuous and structurally different enzymes, for which improvements in enantioselectivity and stability were confirmed. We expect this method to promote the use of supramolecularly engineered promiscuous enzymes in industrially relevant biocatalytic processes.

Main Structural Targets for Engineering Lipase Substrate Specificity

Microbial lipases represent one of the most important groups of biotechnological biocatalysts. However, the high-level production of lipases requires an understanding of the molecular mechanisms of gene expression, folding, and secretion processes. Stable, selective, and productive lipase is essential for modern chemical industries, as most lipases cannot work in different process conditions. However, the screening and isolation of a new lipase with desired and specific properties would be time consuming, and costly, so researchers typically modify an available lipase with a certain potential for minimizing cost. Improving enzyme properties is associated with altering the enzymatic structure by changing one or several amino acids in the protein sequence. This review detailed the main sources, classification, structural properties, and mutagenic approaches, such as rational design (site direct mutagenesis, iterative saturation mutagenesis) and direct evolution (error prone PCR, DNA shuffling), for achieving modification goals. Here, both techniques were reviewed, with different results for lipase engineering, with a particular focus on improving or changing lipase specificity. Changing the amino acid sequences of the binding pocket or lid region of the lipase led to remarkable enzyme substrate specificity and enantioselectivity improvement. Site-directed mutagenesis is one of the appropriate methods to alter the enzyme sequence, as compared to random mutagenesis, such as error-prone PCR. This contribution has summarized and evaluated several experimental studies on modifying the substrate specificity of lipases.

Dissecting the evolvability landscape of the CalB active site toward aromatic substrates

A key event in the directed evolution of enzymes is the systematic use of mutagenesis and selection, a process that can give rise to mutant libraries containing millions of protein variants. To this day, the functional analysis and identification of active variants among such high numbers of mutational possibilities is not a trivial task. Here, we describe a combinatorial semi-rational approach to partly overcome this challenge and help design smaller and smarter mutant libraries. By adapting a liquid medium transesterification assay in organic solvent conditions with a combination of virtual docking, iterative saturation mutagenesis, and residue interaction network (RIN) analysis, we engineered lipase B from P. antarctica (CalB) to improve enzyme recognition and activity against the bulky aromatic substrates and flavoring agents methyl cinnamate and methyl salicylate. Substrate-imprinted docking was used to target active-site positions involved in enzyme-substrate and enzyme-product complexes, in addition to identifying 'hot spots' most likely to yield active variants. This iterative semi-rational design strategy allowed selection of CalB variants exhibiting increased activity in just two rounds of site-saturation mutagenesis. Beneficial replacements were observed by screening only 0.308% of the theoretical library size, illustrating how semi-rational approaches with targeted diversity can quickly facilitate the discovery of improved activity variants relevant to a number of biotechnological applications.

Widely applicable background depletion step enables transaminase evolution through solid-phase screening

Directed evolution of transaminases is a widespread technique in the development of highly sought-after biocatalysts for industrial applications. This process, however, is challenged by the limited availability of effective high-throughput protocols to evaluate mutant libraries. Here we report a rapid, reliable, and widely applicable background depletion method for solid-phase screening of transaminase variants, which was successfully applied to a transaminase from Halomonas elongata (HEWT), evolved through rounds of random mutagenesis towards a series of diverse prochiral ketones. This approach enabled the identification of transaminase variants in viable cells with significantly improved activity towards para-substituted acetophenones (up to 60-fold), as well as tetrahydrothiophen-3-one and related substrates. Rationalisation of the mutants was assisted by determination of the high-resolution wild-type HEWT crystal structure presented herein.

Ultra-high throughput functional enrichment of large monoamine oxidase (MAO-N) libraries by fluorescence activated cell sorting

Directed evolution enables the improvement and optimisation of enzymes for particular applications and is a valuable tool for biotechnology and synthetic biology. However, studies are often limited in their scope by the inability to screen very large numbers of variants to identify improved enzymes. One class of enzyme for which a universal, operationally simple ultra-high throughput (>106 variants per day) assay is not available is flavin adenine dinucleotide (FAD) dependent oxidases. The current high throughput assay involves a visual, colourimetric, colony-based screen, however this is not suitable for very large libraries and does not enable quantification of the relative fitness of variants. To address this, we describe an optimised method for the sensitive detection of oxidase activity within single Escherichia coli (E. coli) cells, using the monoamine oxidase from Aspergillus niger, MAO-N, as a model system. In contrast to other methods for the screening of oxidase activity in vivo, this method does not require cell surface expression, emulsion formation or the addition of an extracellular peroxidase. Furthermore, we show that fluorescence activated cell sorting (FACS) of large libraries derived from MAO-N under the assay conditions can enrich the library in functional variants at much higher rates than via the colony-based method. We demonstrate its use for directed evolution by identifying a new mutant of MAO-N with improved activity towards a novel secondary amine substrate. This work demonstrates, for the first time, an ultra-high throughput screening methodology widely applicable for the directed evolution of FAD dependent oxidases in E. coli.

"Site and Mutation"-Specific Predictions Enable Minimal Directed Evolution Libraries

Directed evolution experiments designed to improve the activity of a biocatalyst have increased in sophistication from the early days of completely random mutagenesis. Sequence-based and structure-based methods have been developed to identify "hotspot" positions that when randomized provide a higher frequency of beneficial mutations that improve activity. These focused mutagenesis methods reduce library sizes and therefore reduce screening burden, accelerating the rate of finding improved enzymes. Looking for further acceleration in finding improved enzymes, we investigated whether two existing methods, one sequence-based (Protein GPS) and one structure-based (using Bioluminate and MOE), were sufficiently predictive to provide not just the hotspot position, but also the amino acid substitution that improved activity at that position. By limiting the libraries to variants that contained only specific amino acid substitutions, library sizes were kept to less than 100 variants. For an initial round of ATA-117 R-selective transaminase evolution, we found that the methods used produced libraries where 9% and 18% of the amino acid substitutions chosen were amino acids that improved reaction performance in lysates. The ability to create combinations of mutations as part of the initial design was confounded by the relatively large number of predicted mutations that were inactivating (30% and 45% for the sequence-based and structure-based methods, respectively). Despite this, combining several mutations identified within a given method produced variant lysates 7- and 9-fold more active than the wild-type lysate, highlighting the capability of mutations chosen this way to generate large advances in activity in addition to the reductions in screening.

Computational redesign of enzymes for regio- and enantioselective hydroamination

Introduction of innovative biocatalytic processes offers great promise for applications in green chemistry. However, owing to limited catalytic performance, the enzymes harvested from nature's biodiversity often need to be improved for their desired functions by time-consuming iterative rounds of laboratory evolution. Here we describe the use of structure-based computational enzyme design to convert Bacillus sp. YM55-1 aspartase, an enzyme with a very narrow substrate scope, to a set of complementary hydroamination biocatalysts. The redesigned enzymes catalyze asymmetric addition of ammonia to substituted acrylates, affording enantiopure aliphatic, polar and aromatic β-amino acids that are valuable building blocks for the synthesis of pharmaceuticals and bioactive compounds. Without a requirement for further optimization by laboratory evolution, the redesigned enzymes exhibit substrate tolerance up to a concentration of 300 g/L, conversion up to 99%, β-regioselectivity >99% and product enantiomeric excess >99%. The results highlight the use of computational design to rapidly adapt an enzyme to industrially viable reactions.

Stereoelectronic effects in the reaction of aromatic substrates catalysed by Halomonas elongata transaminase and its mutants

A transaminase from Halomonas elongata and four mutants generated by an in silico-based design were recombinantly produced in E. coli, purified and applied to the amination of mono-substituted aromatic carbonyl-derivatives. While benzaldehyde derivatives were excellent substrates, only NO₂-acetophenones were transformed into the (S)-amine with a high enantioselectivity. The different behaviour of wild-type and mutated transaminases was assessed by in silico substrate binding mode studies.

CorNet: Assigning function to networks of co-evolving residues by automated literature mining

CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the functions associated with these groups and the residues in them. We used CorNet to analyse six enzyme super-families and found that groups of strongly co-evolving residues tend to consist of residues involved in a same function such as activity, specificity, co-factor binding, or enantioselectivity. This finding allows to assign a function to residues for which no data is available yet in the literature. A mutant library was designed to mutate residues observed in a group of co-evolving residues predicted to be involved in enantioselectivity, but for which no literature data is available yet. The resulting set of mutations indeed showed many instances of increased enantioselectivity.

Engineering of d-fructose-6-phosphate aldolase A for improved activity towards cinnamaldehyde

d-Fructose-6-phosphate aldolase A (FSAA) from Escherichia coli was engineered for enhanced catalytic efficiency towards cinnamaldehyde.

Correlated positions in protein evolution and engineering

Statistical analysis of a protein multiple sequence alignment can reveal groups of positions that undergo interdependent mutations throughout evolution. At these so-called correlated positions, only certain combinations of amino acids appear to be viable for maintaining proper folding, stability, catalytic activity or specificity. Therefore, it is often speculated that they could be interesting guides for semi-rational protein engineering purposes. Because they are a fingerprint from protein evolution, their analysis may provide valuable insight into a protein's structure or function and furthermore, they may also be suitable target positions for mutagenesis. Unfortunately, little is currently known about the properties of these correlation networks and how they should be used in practice. This review summarises the recent findings, opportunities and pitfalls of the concept.

HotSpot Wizard 2.0: automated design of site-specific mutations and smart libraries in protein engineering

HotSpot Wizard 2.0 is a web server for automated identification of hot spots and design of smart libraries for engineering proteins' stability, catalytic activity, substrate specificity and enantioselectivity. The server integrates sequence, structural and evolutionary information obtained from 3 databases and 20 computational tools. Users are guided through the processes of selecting hot spots using four different protein engineering strategies and optimizing the resulting library's size by narrowing down a set of substitutions at individual randomized positions. The only required input is a query protein structure. The results of the calculations are mapped onto the protein's structure and visualized with a JSmol applet. HotSpot Wizard lists annotated residues suitable for mutagenesis and can automatically design appropriate codons for each implemented strategy. Overall, HotSpot Wizard provides comprehensive annotations of protein structures and assists protein engineers with the rational design of site-specific mutations and focused libraries. It is freely available at http://loschmidt.chemi.muni.cz/hotspotwizard.

How mutational epistasis impairs predictability in protein evolution and design

There has been much debate about the extent to which mutational epistasis, that is, the dependence of the outcome of a mutation on the genetic background, constrains evolutionary trajectories. The degree of unpredictability introduced by epistasis, due to the non-additivity of functional effects, strongly hinders the strategies developed in protein design and engineering. While many studies have addressed this issue through systematic characterization of evolutionary trajectories within individual enzymes, the field lacks a consensus view on this matter. In this work, we performed a comprehensive analysis of epistasis by analyzing the mutational effects from nine adaptive trajectories toward new enzymatic functions. We quantified epistasis by comparing the effect of mutations occurring between two genetic backgrounds: the starting enzyme (for example, wild type) and the intermediate variant on which the mutation occurred during the trajectory. We found that most trajectories exhibit positive epistasis, in which the mutational effect is more beneficial when it occurs later in the evolutionary trajectory. Approximately half (49%) of functional mutations were neutral or negative on the wild-type background, but became beneficial at a later stage in the trajectory, indicating that these functional mutations were not predictable from the initial starting point. While some cases of strong epistasis were associated with direct interaction between residues, many others were caused by long-range indirect interactions between mutations. Our work highlights the prevalence of epistasis in enzyme adaptive evolution, in particular positive epistasis, and suggests the necessity of incorporating mutational epistasis in protein engineering and design to create highly efficient catalysts.

Carbonyl group-dependent high-throughput screening and enzymatic characterization of diaromatic ketone reductase

We have developed a carbonyl group-dependent colorimetric method for assay of carbonyl reductases using inexpensive 2,4-dinitrophenylhydrazine (DNPH).