Biomacromolecule-Assisted Screening for Reaction Discovery and Catalyst Optimization

Reaction discovery and catalyst screening lie at the heart of synthetic organic chemistry. While there are efforts at de novo catalyst design using computation/artificial intelligence, at its core, synthetic chemistry is an experimental science. This review overviews biomacromolecule-assisted screening methods and the follow-on elaboration of chemistry so discovered. All three types of biomacromolecules discussed─enzymes, antibodies, and nucleic acids─have been used as "sensors" to provide a readout on product chirality exploiting their native chirality. Enzymatic sensing methods yield both UV-spectrophotometric and visible, colorimetric readouts. Antibody sensors provide direct fluorescent readout upon analyte binding in some cases or provide for cat-ELISA (Enzyme-Linked ImmunoSorbent Assay)-type readouts. DNA biomacromolecule-assisted screening allows for templation to facilitate reaction discovery, driving bimolecular reactions into a pseudo-unimolecular format. In addition, the ability to use DNA-encoded libraries permits the barcoding of reactants. All three types of biomacromolecule-based screens afford high sensitivity and selectivity. Among the chemical transformations discovered by enzymatic screening methods are the first Ni(0)-mediated asymmetric allylic amination and a new thiocyanopalladation/carbocyclization transformation in which both C-SCN and C-C bonds are fashioned sequentially. Cat-ELISA screening has identified new classes of sydnone-alkyne cycloadditions, and DNA-encoded screening has been exploited to uncover interesting oxidative Pd-mediated amido-alkyne/alkene coupling reactions.

Processing of D1 Protein: A Mysterious Process Carried Out in Thylakoid Lumen

In oxygenic photosynthetic organisms, D1 protein, a core subunit of photosystem II (PSII), displays a rapid turnover in the light, in which D1 proteins are distinctively damaged and immediately removed from the PSII. In parallel, as a repair process, D1 proteins are synthesized and simultaneously assembled into the PSII. On this flow, the D1 protein is synthesized as a precursor with a carboxyl-terminal extension, and the D1 processing is defined as a step for proteolytic removal of the extension by a specific protease, CtpA. The D1 processing plays a crucial role in appearance of water-oxidizing capacity of PSII, because the main chain carboxyl group at carboxyl-terminus of the D1 protein, exposed by the D1 processing, ligates a manganese and a calcium atom in the Mn4CaO5-cluster, a special equipment for water-oxidizing chemistry of PSII. This review focuses on the D1 processing and discusses it from four angles: (i) Discovery of the D1 processing and recognition of its importance: (ii) Enzyme involved in the D1 processing: (iii) Efforts for understanding significance of the D1 processing: (iv) Remaining mysteries in the D1 processing. Through the review, I summarize the current status of our knowledge on and around the D1 processing.

Structural Comparison of a Promiscuous and a Highly Specific Sucrose 6F-Phosphate Phosphorylase

In family GH13 of the carbohydrate-active enzyme database, subfamily 18 contains glycoside phosphorylases that act on α-sugars and glucosides. Because their phosphorolysis reactions are effectively reversible, these enzymes are of interest for the biocatalytic synthesis of various glycosidic compounds. Sucrose 6^F-phosphate phosphorylases (SPPs) constitute one of the known substrate specificities. Here, we report the characterization of an SPP from Ilumatobacter coccineus with a far stricter specificity than the previously described promiscuous SPP from Thermoanaerobacterium thermosaccharolyticum. Crystal structures of both SPPs were determined to provide insight into their similarities and differences. The residues responsible for binding the fructose 6-phosphate group in subsite +1 were found to differ considerably between the two enzymes. Furthermore, several variants that introduce a higher degree of substrate promiscuity in the strict SPP from I. coccineus were designed. These results contribute to an expanded structural knowledge of enzymes in subfamily GH13_18 and facilitate their rational engineering.

Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins

Molecular evolution based on mutagenesis is widely used in protein engineering. However, optimal proteins are often difficult to obtain due to a large sequence space. Here, we propose a novel approach that combines molecular evolution with machine learning. In this approach, we conduct two rounds of mutagenesis where an initial library of protein variants is used to train a machine-learning model to guide mutagenesis for the second-round library. This enables us to prepare a small library suited for screening experiments with high enrichment of functional proteins. We demonstrated a proof-of-concept of our approach by altering the reference green fluorescent protein (GFP) so that its fluorescence is changed into yellow. We successfully obtained a number of proteins showing yellow fluorescence, 12 of which had longer wavelengths than the reference yellow fluorescent protein (YFP). These results show the potential of our approach as a powerful method for directed evolution of fluorescent proteins.

Engineering the Enantioselectivity and Thermostability of a (+)-γ-Lactamase from Microbacterium hydrocarbonoxydans for Kinetic Resolution of Vince Lactam (2-Azabicyclo[2.2.1]hept-5-en-3-one)

To produce promising biocatalysts, natural enzymes often need to be engineered to increase their catalytic performance. In this study, the enantioselectivity and thermostability of a (+)-γ-lactamase from Microbacterium hydrocarbonoxydans as the catalyst in the kinetic resolution of Vince lactam (2-azabicyclo[2.2.1]hept-5-en-3-one) were improved. Enantiomerically pure (-)-Vince lactam is the key synthon in the synthesis of antiviral drugs, such as carbovir and abacavir, which are used to fight against HIV and hepatitis B virus. The work was initialized by using the combinatorial active-site saturation test strategy to engineer the enantioselectivity of the enzyme. The approach resulted in two mutants, Val54Ser and Val54Leu, which catalyzed the hydrolysis of Vince lactam to give (-)-Vince lactam, with 99.2% (enantiomeric ratio [E] > 200) enantiomeric excess (ee) and 99.5% ee (E > 200), respectively. To improve the thermostability of the enzyme, 11 residues with high temperature factors (B-factors) calculated by B-FITTER or high root mean square fluctuation (RMSF) values from the molecular dynamics simulation were selected. Six mutants with increased thermostability were obtained. Finally, the mutants generated with improved enantioselectivity and mutants evolved for enhanced thermostability were combined. Several variants showing (+)-selectivity (E value > 200) and improved thermostability were observed. These engineered enzymes are good candidates to serve as enantioselective catalysts for the preparation of enantiomerically pure Vince lactam.IMPORTANCE Enzymatic kinetic resolution of the racemic Vince lactam using (+)-γ-lactamase is the most often utilized means of resolving the enantiomers for the preparation of carbocyclic nucleoside compounds. The efficiency of the native enzymes could be improved by using protein engineering methods, such as directed evolution and rational design. In our study, two properties (enantioselectivity and thermostability) of a γ-lactamase identified from Microbacterium hydrocarbonoxydans were tackled using a semirational design. The protein engineering was initialized by combinatorial active-site saturation test to improve the enantioselectivity. At the same time, two strategies were applied to identify mutation candidates to enhance the thermostability based on calculations from both a static (B-FITTER based on the crystal structure) and a dynamic (root mean square fluctuation [RMSF] values based on molecular dynamics simulations) way. After combining the mutants, we successfully obtained the final mutants showing better properties in both properties. The engineered (+)-lactamase could be a candidate for the preparation of (-)-Vince lactam.

The Generation and Exploitation of Protein Mutability Landscapes for Enzyme Engineering

The increasing number of enzyme applications in chemical synthesis calls for new engineering methods to develop the biocatalysts of the future. An interesting concept in enzyme engineering is the generation of large-scale mutational data in order to chart protein mutability landscapes. These landscapes allow the important discrimination between beneficial mutations and those that are neutral or detrimental, thus providing detailed insight into sequence-function relationships. As such, mutability landscapes are a powerful tool with which to identify functional hotspots at any place in the amino acid sequence of an enzyme. These hotspots can be used as targets for combinatorial mutagenesis to yield superior enzymes with improved catalytic properties, stability, or even new enzymatic activities. The generation of mutability landscapes for multiple properties of one enzyme provides the exciting opportunity to select mutations that are beneficial either for one or for several of these properties. This review presents an overview of the recent advances in the construction of mutability landscapes and discusses their importance for enzyme engineering.

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.

Improvement of biocatalysts for industrial and environmental purposes by saturation mutagenesis

Laboratory evolution techniques are becoming increasingly widespread among protein engineers for the development of novel and designed biocatalysts. The palette of different approaches ranges from complete randomized strategies to rational and structure-guided mutagenesis, with a wide variety of costs, impacts, drawbacks and relevance to biotechnology. A technique that convincingly compromises the extremes of fully randomized vs. rational mutagenesis, with a high benefit/cost ratio, is saturation mutagenesis. Here we will present and discuss this approach in its many facets, also tackling the issue of randomization, statistical evaluation of library completeness and throughput efficiency of screening methods. Successful recent applications covering different classes of enzymes will be presented referring to the literature and to research lines pursued in our group. The focus is put on saturation mutagenesis as a tool for designing novel biocatalysts specifically relevant to production of fine chemicals for improving bulk enzymes for industry and engineering technical enzymes involved in treatment of waste, detoxification and production of clean energy from renewable sources.

Reducing codon redundancy and screening effort of combinatorial protein libraries created by saturation mutagenesis

Saturation mutagenesis probes define sections of the vast protein sequence space. However, even if randomization is limited this way, the combinatorial numbers problem is severe. Because diversity is created at the codon level, codon redundancy is a crucial factor determining the necessary effort for library screening. Additionally, due to the probabilistic nature of the sampling process, oversampling is required to ensure library completeness as well as a high probability to encounter all unique variants. Our trick employs a special mixture of three primers, creating a degeneracy of 22 unique codons coding for the 20 canonical amino acids. Therefore, codon redundancy and subsequent screening effort is significantly reduced, and a balanced distribution of codon per amino acid is achieved, as demonstrated exemplarily for a library of cyclohexanone monooxygenase. We show that this strategy is suitable for any saturation mutagenesis methodology to generate less-redundant libraries.

Enhancing the efficiency of directed evolution in focused enzyme libraries by the adaptive substituent reordering algorithm

Directed evolution is a broadly successful strategy for protein engineering in the quest to enhance the stereoselectivity, activity, and thermostability of enzymes. To increase the efficiency of directed evolution based on iterative saturation mutagenesis, the adaptive substituent reordering algorithm (ASRA) is introduced here as an alternative to traditional quantitative structure-activity relationship (QSAR) methods for identifying potential protein mutants with desired properties from minimal sampling of focused libraries. The operation of ASRA depends on identifying the underlying regularity of the protein property landscape, allowing it to make predictions without explicit knowledge of the structure-property relationships. In a proof-of-principle study, ASRA identified all or most of the best enantioselective mutants among the synthesized epoxide hydrolase from Aspergillus niger, in the absence of peptide seeds with high E-values. ASRA even revealed a laboratory error from irregularities of the reordered E-value landscape alone.

Focused directed evolution of pentaerythritol tetranitrate reductase by using automated anaerobic kinetic screening of site-saturated libraries

This work describes the development of an automated robotic platform for the rapid screening of enzyme variants generated from directed evolution studies of pentraerythritol tetranitrate (PETN) reductase, a target for industrial biocatalysis. By using a 96-well format, near pure enzyme was recovered and was suitable for high throughput kinetic assays; this enabled rapid screening for improved and new activities from libraries of enzyme variants. Initial characterisation of several single site-saturation libraries targeted at active site residues of PETN reductase, are described. Two mutants (T26S and W102F) were shown to have switched in substrate enantiopreference against substrates (E)-2-aryl-1-nitropropene and α-methyl-trans-cinnamaldehyde, respectively, with an increase in ee (62 % (R) for W102F). In addition, the detection of mutants with weak activity against α,β-unsaturated carboxylic acid substrates showed progress in the expansion of the substrate range of PETN reductase. These methods can readily be adapted for rapid evolution of enzyme variants with other oxidoreductase enzymes.

Why is chemical synthesis and property optimization easier than expected?

Identifying optimal conditions for chemical and material synthesis as well as optimizing the properties of the products is often much easier than simple reasoning would predict. The potential search space is infinite in principle and enormous in practice, yet optimal molecules, materials, and synthesis conditions for many objectives can often be found by performing a reasonable number of distinct experiments. Considering the goal of chemical synthesis or property identification as optimal control problems provides insight into this good fortune. Both of these goals may be described by a fitness function J that depends on a suitable set of variables (e.g., reactant concentrations, components of a material, processing conditions, etc.). The relationship between J and the variables specifies the fitness landscape for the target objective. Upon making simple physical assumptions, this work demonstrates that the fitness landscape for chemical optimization contains no local sub-optimal maxima that may hinder attainment of the absolute best value of J. This feature provides a basis to explain the many reported efficient optimizations of synthesis conditions and molecular or material properties. We refer to this development as OptiChem theory. The predicted characteristics of chemical fitness landscapes are assessed through a broad examination of the recent literature, which shows ample evidence of trap-free landscapes for many objectives. The fundamental and practical implications of OptiChem theory for chemistry are discussed.

Site-saturation mutagenesis: a powerful tool for structure-based design of combinatorial mutation libraries

This unit describes a method for site-saturation mutagenesis (SSM) using PCR amplification with degenerate synthetic oligonucleotides as primers. SSM allows the substitution of predetermined protein sites against all twenty possible amino acids at once. Therefore, SSM is a powerful approach in protein engineering to characterize structure-function relationships, as well as to create improved protein variants. The procedure accepts double-stranded plasmid isolated from the dam(+) E. coli strain. The procedure is simple, fast, efficient, and eliminates time-consuming subcloning and ligation steps.

Engineering of Candida antarctica lipase B for hydrolysis of bulky carboxylic acid esters

Candida antarctica lipase B (CALB) is a widely used biocatalyst with high activity and specificity for a wide range of primary and secondary alcohols. However, the range of converted carboxylic acids is more narrow and mainly limited to unbranched fatty acids. To further broaden the biotechnological applications of CALB it is of interest to expand the range of converted carboxylic acid and extend it to carboxylic acids that are branched or substituted in close proximity of the carboxyl group. An in silico library of 2400 CALB variants was built and screened in silico by substrate-imprinted docking, a four step docking procedure. First, reaction intermediates of putative substrates are covalently docked into enzyme active sites. Second, the geometry of the resulting enzyme-substrate complex is optimized. Third, the substrate is removed from the complex and then docked again into the optimized structure. Fourth, the resulting substrate poses are rated by geometric filter criteria as productive or non-productive poses. Eleven enzyme variants resulting from the in silico screening were expressed in Escherichia coli BL21 and measured in the hydrolysis of two branched fatty acid esters, isononanoic acid ethyl ester and 2-ethyl hexanoic acid ethyl esters. Five variants showed an initial increase in activity. The variant with the highest wet mass activity (T138S) was purified and further characterized. It showed a 5-fold increase in hydrolysis of isononanoic acid ethyl ester, but not toward sterically more demanding 2-ethyl hexanoic acid ethyl ester.

New efficient recombinant expression system to engineer Candida antarctica lipase B

Here, we report the use of Yarrowia lipolytica as a versatile expression host for developing protein engineering approaches to modify the properties of Candida antarctica lipase B. A reliable screening protocol was defined and validated using a saturation mutagenesis library, yielding mutants displaying higher catalytic efficiencies than the wild-type enzyme.