Better library design: data-driven protein engineering

Hotspot Wizard-informed engineering of a hyperthermophilic β-glucosidase for enhanced enzyme activity at low temperatures

Hyperthermophilic enzymes serve as an important source of industrial enzymes due to their high thermostability. Unfortunately, most hyperthermophilic enzymes suffer from reduced activity at low temperatures (e.g., ambient temperature), limiting their applicability. In addition, evolving hyperthermophilic enzymes to increase low temperature activity without compromising other desired properties is generally difficult. In the current study, a variant of β-glucosidase from Pyrococcus furiosus (PfBGL) was engineered to enhance enzyme activity at low temperatures through the construction of a saturation mutagenesis library guided by the HotSpot Wizard analysis, followed by its screening for activity and thermostability. From this library construction and screening, one PfBGL mutant, PfBGL-A4 containing Q214S/A264S/F344I mutations, showed an over twofold increase in β-glucosidase activity at 25 and 50°C compared to the wild type, without compromising high-temperature activity, thermostability and substrate specificity. Our experimental and computational characterizations suggest that the findings with PfBGL-A4 may be due to the elevation of local conformational flexibility around the active site, while slightly compacting the global protein structure. This study showcases the potential of HotSpot Wizard-informed engineering of hyperthermophilic enzymes and underscores the interplays among temperature, enzyme activity, and conformational flexibility in these enzymes.

LibGENiE - A bioinformatic pipeline for the design of information-enriched enzyme libraries

Enzymes are potent catalysts with high specificity and selectivity. To leverage nature's synthetic potential for industrial applications, various protein engineering techniques have emerged which allow to tailor the catalytic, biophysical, and molecular recognition properties of enzymes. However, the many possible ways a protein can be altered forces researchers to carefully balance between the exhaustiveness of an enzyme screening campaign and the required resources. Consequently, the optimal engineering strategy is often defined on a case-by-case basis. Strikingly, while predicting mutations that lead to an improved target function is challenging, here we show that the prediction and exclusion of deleterious mutations is a much more straightforward task as analyzed for an engineered carbonic acid anhydrase, a transaminase, a squalene-hopene cyclase and a Kemp eliminase. Combining such a pre-selection of allowed residues with advanced gene synthesis methods opens a path toward an efficient and generalizable library construction approach for protein engineering. To give researchers easy access to this methodology, we provide the website LibGENiE containing the bioinformatic tools for the library design workflow.

Combined Theoretical, Bioinformatic, and Biochemical Analyses of RNA Editing by Adenine Base Editors

Adenine base editors (ABEs) have been subjected to multiple rounds of mutagenesis with the goal of optimizing their function as efficient and precise genome editing agents. Despite an ever-expanding data set of ABE mutants and their corresponding DNA or RNA-editing activity, the molecular mechanisms defining these changes remain to be elucidated. In this study, we provide a systematic interpretation of the nature of these mutations using an entropy-based classification model that relies on evolutionary data from extant protein sequences. Using this model in conjunction with experimental analyses, we identify two previously reported mutations that form an epistatic pair in the RNA-editing functional landscape of ABEs. Molecular dynamics simulations reveal the atomistic details of how these two mutations affect substrate-binding and catalytic activity, via both individual and cooperative effects, hence providing insights into the mechanisms through which these two mutations are epistatically coupled.

Critical assessment of structure-based approaches to improve protein resistance in aqueous ionic liquids by enzyme-wide saturation mutagenesis

Ionic liquids (IL) and aqueous ionic liquids (aIL) are attractive (co-)solvents for green industrial processes involving biocatalysts, but often reduce enzyme activity. Experimental and computational methods are applied to predict favorable substitution sites and, most often, subsequent site-directed surface charge modifications are introduced to enhance enzyme resistance towards aIL. However, almost no studies evaluate the prediction precision with random mutagenesis or the application of simple data-driven filtering processes. Here, we systematically and rigorously evaluated the performance of 22 previously described structure-based approaches to increase enzyme resistance to aIL based on an experimental complete site-saturation mutagenesis library of Bacillus subtilis Lipase A (BsLipA) screened against four aIL. We show that, surprisingly, most of the approaches yield low gain-in-precision (GiP) values, particularly for predicting relevant positions: 14 approaches perform worse than random mutagenesis. Encouragingly, exploiting experimental information on the thermostability of BsLipA or structural weak spots of BsLipA predicted by rigidity theory yields GiP = 3.03 and 2.39 for relevant variants and GiP = 1.61 and 1.41 for relevant positions. Combining five simple-to-compute physicochemical and evolutionary properties substantially increases the precision of predicting relevant variants and positions, yielding GiP = 3.35 and 1.29. Finally, combining these properties with predictions of structural weak spots identified by rigidity theory additionally improves GiP for relevant variants up to 4-fold to ∼10 and sustains or increases GiP for relevant positions, resulting in a prediction precision of ∼90% compared to ∼9% in random mutagenesis. This combination should be applicable to other enzyme systems for guiding protein engineering approaches towards improved aIL resistance.

Phage-Assisted Continuous Evolution and Selection of Enzymes for Chemical Synthesis

Ligand-dependent biosensors are valuable tools for coupling the intracellular concentrations of small molecules to easily detectable readouts such as absorbance, fluorescence, or cell growth. While ligand-dependent biosensors are widely used for monitoring the production of small molecules in engineered cells and for controlling or optimizing biosynthetic pathways, their application to directed evolution for biocatalysts remains underexplored. As a consequence, emerging continuous evolution technologies are rarely applied to biocatalyst evolution. Here, we develop a panel of ligand-dependent biosensors that can detect a range of small molecules. We demonstrate that these biosensors can link enzymatic activity to the production of an essential phage protein to enable biocatalyst-dependent phage-assisted continuous evolution (PACE) and phage-assisted continuous selection (PACS). By combining these phage-based evolution and library selection technologies, we demonstrate that we can evolve enzyme variants with improved and expanded catalytic properties. Finally, we show that the genetic diversity resulting from a highly mutated PACS library is enriched for active enzyme variants with altered substrate scope. These results lay the foundation for using phage-based continuous evolution and selection technologies to engineer biocatalysts with novel substrate scope and reactivity.

Recent advances in user-friendly computational tools to engineer protein function

Progress in technology and algorithms throughout the past decade has transformed the field of protein design and engineering. Computational approaches have become well-engrained in the processes of tailoring proteins for various biotechnological applications. Many tools and methods are developed and upgraded each year to satisfy the increasing demands and challenges of protein engineering. To help protein engineers and bioinformaticians navigate this emerging wave of dedicated software, we have critically evaluated recent additions to the toolbox regarding their application for semi-rational and rational protein engineering. These newly developed tools identify and prioritize hotspots and analyze the effects of mutations for a variety of properties, comprising ligand binding, protein-protein and protein-nucleic acid interactions, and electrostatic potential. We also discuss notable progress to target elusive protein dynamics and associated properties like ligand-transport processes and allosteric communication. Finally, we discuss several challenges these tools face and provide our perspectives on the further development of readily applicable methods to guide protein engineering efforts.

Synthesis of libraries and multi-site mutagenesis using a PCR-derived, dU-containing template

Directed DNA libraries are useful because they focus genetic diversity in the most important regions within a sequence. Ideally, all sequences in such libraries should appear with the same frequency and there should be no significant background from the starting sequence. These properties maximize the number of different sequences that can be screened. Described herein is a method termed SLUPT (Synthesis of Libraries via a dU-containing PCR-derived Template) for generating highly targeted DNA libraries and/or multi-site mutations wherein the altered bases may be widely distributed within a target sequence. This method is highly efficient and modular. Moreover, multiple distinct sites, each with one or more base changes, can be altered in a single reaction. There is very low background from the starting sequence, and SLUPT libraries have similar representation of each base at the positions selected for variation. The SLUPT method utilizes a single-stranded dU-containing DNA template that is made by polymerase chain reaction (PCR). Synthesis of the template in this way is significantly easier than has been described earlier. A series of oligonucleotide primers that are homologous to the template and encode the desired genetic diversity are extended and ligated in a single reaction to form the mutated product sequence or library. After selective inactivation of the template, only the product library is amplified. There are no restrictions on the spacing of the mutagenic primers except that they cannot overlap.

Computational Design of Enantiocomplementary Epoxide Hydrolases for Asymmetric Synthesis of Aliphatic and Aromatic Diols

The use of enzymes in preparative biocatalysis often requires tailoring enzyme selectivity by protein engineering. Herein we explore the use of computational library design and molecular dynamics simulations to create variants of limonene epoxide hydrolase that produce enantiomeric diols from meso‐epoxides. Three substrates of different sizes were targeted: cis‐2,3‐butene oxide, cyclopentene oxide, and cis‐stilbene oxide. Most of the 28 designs tested were active and showed the predicted enantioselectivity. Excellent enantioselectivities were obtained for the bulky substrate cis‐stilbene oxide, and enantiocomplementary mutants produced (S,S)‐ and (R,R)‐stilbene diol with >97 % enantiomeric excess. An (R,R)‐selective mutant was used to prepare (R,R)‐stilbene diol with high enantiopurity (98 % conversion into diol, >99 % ee). Some variants displayed higher catalytic rates (k_cat) than the original enzyme, but in most cases K_M values increased as well. The results demonstrate the feasibility of computational design and screening to engineer enantioselective epoxide hydrolase variants with very limited laboratory screening.

Engineering repeat proteins of the immune system

Limitations associated with immunoglobulins have motivated the search for novel binding scaffolds. Repeat proteins have emerged as one promising class of scaffolds, but often are limited to binding protein and peptide targets. An exception is the repeat proteins of the immune system, which have in recent years served as an inspiration for binding scaffolds which can bind glycans and other classes of biomolecule. Like other repeat proteins, these proteins can be very stable and have a monomeric mode of binding, with elongated and highly variable binding surfaces. The ability to target glycans and glycoproteins fill an important gap in current tools for research and biomedical applications.

Systematically Scrutinizing the Impact of Substitution Sites on Thermostability and Detergent Tolerance for Bacillus subtilis Lipase A

Improving an enzyme's (thermo-)stability or tolerance against solvents and detergents is highly relevant in protein engineering and biotechnology. Recent developments have tended toward data-driven approaches, where available knowledge about the protein is used to identify substitution sites with high potential to yield protein variants with improved stability, and subsequently, substitutions are engineered by site-directed or site-saturation (SSM) mutagenesis. However, the development and validation of algorithms for data-driven approaches have been hampered by the lack of availability of large-scale data measured in a uniform way and being unbiased with respect to substitution types and locations. Here, we extend our knowledge on guidelines for protein engineering following a data-driven approach by scrutinizing the impact of substitution sites on thermostability or/and detergent tolerance for Bacillus subtilis lipase A (BsLipA) at very large scale. We systematically analyze a complete experimental SSM library of BsLipA containing all 3439 possible single variants, which was evaluated as to thermostability and tolerances against four detergents under respectively uniform conditions. Our results provide systematic and unbiased reference data at unprecedented scale for a biotechnologically important protein, identify consistently defined hot spot types for evaluating the performance of data-driven protein-engineering approaches, and show that the rigidity theory and ensemble-based approach Constraint Network Analysis yields hot spot predictions with an up to ninefold gain in precision over random classification.

"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.

RosettaAntibodyDesign (RAbD): A general framework for computational antibody design

A structural-bioinformatics-based computational methodology and framework have been developed for the design of antibodies to targets of interest. RosettaAntibodyDesign (RAbD) samples the diverse sequence, structure, and binding space of an antibody to an antigen in highly customizable protocols for the design of antibodies in a broad range of applications. The program samples antibody sequences and structures by grafting structures from a widely accepted set of the canonical clusters of CDRs (North et al., J. Mol. Biol., 406:228-256, 2011). It then performs sequence design according to amino acid sequence profiles of each cluster, and samples CDR backbones using a flexible-backbone design protocol incorporating cluster-based CDR constraints. Starting from an existing experimental or computationally modeled antigen-antibody structure, RAbD can be used to redesign a single CDR or multiple CDRs with loops of different length, conformation, and sequence. We rigorously benchmarked RAbD on a set of 60 diverse antibody-antigen complexes, using two design strategies-optimizing total Rosetta energy and optimizing interface energy alone. We utilized two novel metrics for measuring success in computational protein design. The design risk ratio (DRR) is equal to the frequency of recovery of native CDR lengths and clusters divided by the frequency of sampling of those features during the Monte Carlo design procedure. Ratios greater than 1.0 indicate that the design process is picking out the native more frequently than expected from their sampled rate. We achieved DRRs for the non-H3 CDRs of between 2.4 and 4.0. The antigen risk ratio (ARR) is the ratio of frequencies of the native amino acid types, CDR lengths, and clusters in the output decoys for simulations performed in the presence and absence of the antigen. For CDRs, we achieved cluster ARRs as high as 2.5 for L1 and 1.5 for H2. For sequence design simulations without CDR grafting, the overall recovery for the native amino acid types for residues that contact the antigen in the native structures was 72% in simulations performed in the presence of the antigen and 48% in simulations performed without the antigen, for an ARR of 1.5. For the non-contacting residues, the ARR was 1.08. This shows that the sequence profiles are able to maintain the amino acid types of these conserved, buried sites, while recovery of the exposed, contacting residues requires the presence of the antigen-antibody interface. We tested RAbD experimentally on both a lambda and kappa antibody-antigen complex, successfully improving their affinities 10 to 50 fold by replacing individual CDRs of the native antibody with new CDR lengths and clusters.

ProtDataTherm: A database for thermostability analysis and engineering of proteins

Protein thermostability engineering is a powerful tool to improve resistance of proteins against high temperatures and thereafter broaden their applications. For efficient protein thermostability engineering, different thermostability-classified data sources including sequences and 3D structures are needed for different protein families. However, no data source is available providing such data easily. It is the first release of ProtDataTherm database for analysis and engineering of protein thermostability which contains more than 14 million protein sequences categorized based on their thermal stability and protein family. This database contains data needed for better understanding protein thermostability and stability engineering. Providing categorized protein sequences and structures as psychrophilic, mesophilic and thermophilic makes this database useful for the development of new tools in protein stability prediction. This database is available at http://profiles.bs.ipm.ir/softwares/protdatatherm. As a proof of concept, the thermostability that improves mutations were suggested for one sample protein belonging to one of protein families with more than 20 mesophilic and thermophilic sequences and with known experimentally measured ΔT of mutations available within ProTherm database.

In vitro evolution of an l-amino acid deaminase active on l-1-naphthylalanine

l-Amino acid deaminase from Proteus myxofaciens (PmaLAAD) is a promising biocatalyst for enantioselective biocatalysis that can be exploited to produce optically pure d-amino acids or α-keto acids.

Data-Driven Antibody Engineering Using Genedata Biologics™

Genedata Biologics is a novel informatics platform specifically designed for biologics R&D. Here, we discuss the main principles employed in designing such a platform, focusing on antibody engineering. To illustrate, we present a case study of how the platform effectively supports an antibody optimization workflow and ensures the successful integration and analysis of all relevant sequence, expression, assay, and analytics data.

Protein Stability: Enhancement and Measurement

This article defines protein stability, emphasizes its importance and surveys the field of protein stabilization, with summary reference to a selection of 2009-2015 publications. One can enhance stability by, in particular, protein engineering strategies and by chemical modification (including conjugation) in solution. General protocols are set out on how to measure a given protein's (1) kinetic thermal stability, and (2) oxidative stability, and (3) how to undertake chemical modification of a protein in solution.

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.

Using mutability landscapes of a promiscuous tautomerase to guide the engineering of enantioselective Michaelases

The Michael-type addition reaction is widely used in organic synthesis for carbon–carbon bond formation. However, biocatalytic methodologies for this type of reaction are scarce, which is related to the fact that enzymes naturally catalysing carbon–carbon bond-forming Michael-type additions are rare. A promising template to develop new biocatalysts for carbon–carbon bond formation is the enzyme 4-oxalocrotonate tautomerase, which exhibits promiscuous Michael-type addition activity. Here we present mutability landscapes for the expression, tautomerase and Michael-type addition activities, and enantioselectivity of 4-oxalocrotonate tautomerase. These maps of neutral, beneficial and detrimental amino acids for each residue position and enzyme property provide detailed insight into sequence–function relationships. This offers exciting opportunities for enzyme engineering, which is illustrated by the redesign of 4-oxalocrotonate tautomerase into two enantiocomplementary ‘Michaelases'. These ‘Michaelases' catalyse the asymmetric addition of acetaldehyde to various nitroolefins, providing access to both enantiomers of γ-nitroaldehydes, which are important precursors for pharmaceutically active γ-aminobutyric acid derivatives.

The Michael-type addition reaction is used for carbon-carbon bond formation; however biocatalytic methods for this reaction are rare. Here, the authors generate and exploit mutability landscapes of 4-oxalocrotonate tautomerase to direct the redesign of this promiscuous enzyme into enantio-complementary Michaelases.

Protein thermostability engineering

Using structure and sequence based analysis we can engineer proteins to increase their thermal stability.

Genetically modified proteins: functional improvement and chimeragenesis

This review focuses on the emerging role of site-specific mutagenesis and chimeragenesis for the functional improvement of proteins in areas where traditional protein engineering methods have been extensively used and practically exhausted. The novel path for the creation of the novel proteins has been created on the farther development of the new structure and sequence optimization algorithms for generating and designing the accurate structure models in result of x-ray crystallography studies of a lot of proteins and their mutant forms. Artificial genetic modifications aim to expand nature's repertoire of biomolecules. One of the most exciting potential results of mutagenesis or chimeragenesis finding could be design of effective diagnostics, bio-therapeutics and biocatalysts. A sampling of recent examples is listed below for the in vivo and in vitro genetically improvement of various binding protein and enzyme functions, with references for more in-depth study provided for the reader's benefit.

MDC-Analyzer-facilitated combinatorial strategy for improving the activity and stability of halohydrin dehalogenase from Agrobacterium radiobacter AD1

Halohydrin dehalogenase from Agrobacterium radiobacter AD1 (HheC) displays a broad substrate range with high regio- and enantioselectivity of both ring-closure and ring-opening reactions, making the enzyme a useful catalyst for the production of optically pure epoxides and β-substituted alcohols. In this study, we report a novel method using an MDC-Analyzer-facilitated combinatorial strategy to improve the activity and stability of HheC by simultaneously randomizing multiple contiguous residues. Six contiguous active-site residues, which are the hotspots for improving the activity of HheC, were simultaneously selected and randomized using the MDC-Analyzer-facilitated combinatorial strategy, resulting in a high-quality mutagenesis library. After screening a total of 1152 clones, three positive mutants were obtained, which exhibited approximately 3.5-5.9-fold higher kcat values than the wild-type HheC toward 1,3-dichloro-2-propanol (1,3-DCP). However, the inactivation half-life of the best mutant (DG9) at 55 °C decreased 9-fold compared with that of the wild-type HheC. To improve the stability of mutant DG9, seven contiguous potential surface amino acids were revealed by using the B-FITTER tool. Two charged amino acids, Glu and Lys, which are more abundant in thermophilic proteins than in their mesophilic counterparts, were selected to substitute those seven amino acids and were combined together via an MDC-Analyzer-facilitated combinatorial strategy. Two mutants displaying 1.6- and 2.3-fold higher half-life τ1/2 (55 °C) values than their DG9 template were obtained after screening only 384 clones. The results indicated that an MDC-Analyzer-facilitated combinatorial strategy represents an efficient tool for the directed evolution of functional enzymes with multiple contiguous targeting sites.

Assembly of Designed Oligonucleotides: a useful tool in synthetic biology for creating high-quality combinatorial DNA libraries

The method dubbed Assembly of Designed Oligonucleotides (ADO) is a powerful tool in synthetic biology to create combinatorial DNA libraries for gene, protein, metabolic, and genome engineering. In directed evolution of proteins, ADO benefits from using reduced amino acid alphabets for saturation mutagenesis and/or DNA shuffling, but all 20 canonical amino acids can be also used as building blocks. ADO is performed in a two-step reaction. The first involves a primer-free, polymerase cycling assembly or overlap extension PCR step using carefully designed overlapping oligonucleotides. The second step is a PCR amplification using the outer primers, resulting in a high-quality and bias-free double-stranded DNA library that can be assembled with other gene fragments and/or cloned into a suitable plasmid subsequently. The protocol can be performed in a few hours. In theory, neither the length of the DNA library nor the number of DNA changes has any limits. Furthermore, with the costs of synthetic DNA dropping every year, after an initial investment is made in the oligonucleotides, these can be exchanged for alternative ones with different sequences at any point in the process, fully exploiting the potential of creating highly diverse combinatorial libraries. In the example chosen here, we show the construction of a high-quality combinatorial ADO library targeting sixteen different codons simultaneously with nonredundant degenerate codons encoding various reduced alphabets of four amino acids along the heme region of the monooxygenase P450-BM3.

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.

MDC-Analyzer: a novel degenerate primer design tool for the construction of intelligent mutagenesis libraries with contiguous sites

Recent computational and bioinformatics advances have enabled the efficient creation of novel biocatalysts by reducing amino acid variability at hot spot regions. To further expand the utility of this strategy, we present here a tool called Multi-site Degenerate Codon Analyzer (MDC-Analyzer) for the automated design of intelligent mutagenesis libraries that can completely cover user-defined randomized sequences, especially when multiple contiguous and/or adjacent sites are targeted. By initially defining an objective function, the possible optimal degenerate PCR primer profiles could be automatically explored using the heuristic approach of Greedy Best-First-Search. Compared to the previously developed DC-Analyzer, MDC-Analyzer allows for the existence of a small amount of undesired sequences as a tradeoff between the number of degenerate primers and the encoded library size while still providing all the benefits of DC-Analyzer with the ability to randomize multiple contiguous sites. MDC-Analyzer was validated using a series of randomly generated mutation schemes and experimental case studies on the evolution of halohydrin dehalogenase, which proved that the MDC methodology is more efficient than other methods and is particularly well-suited to exploring the sequence space of proteins using data-driven protein engineering strategies.

Quality matters: extension of clusters of residues with good hydrophobic contacts stabilize (hyper)thermophilic proteins

Identifying determinant(s) of protein thermostability is key for rational and data-driven protein engineering. By analyzing more than 130 pairs of mesophilic/(hyper)thermophilic proteins, we identified the quality (residue-wise energy) of hydrophobic interactions as a key factor for protein thermostability. This distinguishes our study from previous ones that investigated predominantly structural determinants. Considering this key factor, we successfully discriminated between pairs of mesophilic/(hyper)thermophilic proteins (discrimination accuracy: ∼80%) and searched for structural weak spots in E. coli dihydrofolate reductase (classification accuracy: 70%).

Computational tools for designing smart libraries

Traditional directed evolution experiments are often time-, labor- and cost-intensive because they involve repeated rounds of random mutagenesis and the selection or screening of large mutant libraries. The efficiency of directed evolution experiments can be significantly improved by targeting mutagenesis to a limited number of hot-spot positions and/or selecting a limited set of substitutions. The design of such "smart" libraries can be greatly facilitated by in silico analyses and predictions. Here we provide an overview of computational tools applicable for (a) the identification of hot-spots for engineering enzyme properties, and (b) the evaluation of predicted hot-spots and selection of suitable amino acids for substitutions. The selected tools do not require any specific expertise and can easily be implemented by the wider scientific community.

Iterative saturation mutagenesis: a powerful approach to engineer proteins by systematically simulating Darwinian evolution

Iterative saturation mutagenesis (ISM) is a widely applicable and powerful strategy for the efficient directed evolution of enzymes. First, one or more amino acid positions from the chosen enzyme are assigned to multi-residue sites (i.e., groups of amino acids or "multisites"). Then, the residues in each multisite are mutated with a user-defined randomization scheme to all canonical amino acids or a reduced amino acid alphabet. Subsequently, the genes of chosen variants (usually the best but not necessarily) are used as templates for saturation mutagenesis at other multisites, and the process is repeated until the desired degree of biocatalyst improvement has been achieved. Addressing multisites iteratively results in a so-called ISM scheme or tree with various upward branches or pathways. The systematic character of ISM simulates in vitro the natural process of Darwinian evolution: variation (library creation), selection (library screening), and amplification (template chosen for the next round of randomization). However, the main feature of ISM that distinguishes it from other directed evolution methods is the systematic probing of a defined segment of the protein sequence space, as it has been shown that ISM is much more efficient in terms of biocatalyst optimization than random methods such as error-prone PCR. In addition, ISM trees have also shed light on the emergence of epistasis, thereby rationally improving the strategies for evolving better enzymes. ISM was developed to improve catalytic properties such as rate, substrate scope, stereo- and regioselectivity using the Combinatorial Active-site Saturation Test (CAST), as well as chemical and thermal stability employing the B-Factor Iterative Test (B-FIT). However, ISM can also be invoked to manipulate such protein properties as binding affinity among other possibilities, including protein-protein interactions. Herein, we provide general guidelines for ISM, using CAST as the case study in the quest to enhance the activity and regioselectivity of the monooxygenase P450BM3 toward testosterone.

Double site saturation mutagenesis of the human cytochrome P450 2D6 results in regioselective steroid hydroxylation

The human cytochrome P450 2D6 (CYP2D6) is one of the major human drug metabolizing enzymes and acts preferably on substrates containing a basic nitrogen atom. Testosterone - just as other steroids - is an atypical substrate and only poorly metabolized by CYP2D6. The present study intended to investigate the influence of the two active site residues 216 and 483 on the capability of CYP2D6 to hydroxylate steroids such as for example testosterone. All 400 possible combinatorial mutations at these two positions have been generated and expressed individually in Pichia pastoris. Employing whole-cell biotransformations coupled with HPLC-MS analysis the testosterone hydroxylase activity and regioselectivity of every single CYP2D6 variant was determined. Covering the whole sequence space, CYP2D6 variants with improved activity and so far unknown regio-preference in testosterone hydroxylation were identified. Most intriguingly and in contrast to previous literature reports about mutein F483I, the mutation F483G led to preferred hydroxylation at the 2β-position, while the slow formation of 6β-hydroxytestosterone, the main product of wild-type CYP2D6, was further reduced. Two point mutations have already been sufficient to convert CYP2D6 into a steroid hydroxylase with the highest ever reported testosterone hydroxylation rate for this enzyme, which is of the same order of magnitude as for the conversion of the standard substrate bufuralol by wild-type CYP2D6. Furthermore, this study is also an example for efficient human CYP engineering in P. pastoris for biocatalytic applications and to study so far unknown pharmacokinetic effects of individual and combined mutations in these key enzymes of the human drug metabolism.

Computational tools for rational protein engineering of aldolases

In this mini-review we describe the different strategies for rational protein engineering and summarize the computational tools available. Computational tools can either be used to design focused libraries, to predict sequence-function relationships or for structure-based molecular modelling. This also includes de novo design of enzymes. Examples for protein engineering of aldolases and transaldolases are given in the second part of the mini-review.

Computational enzyme design approaches with significant biological outcomes: progress and challenges

Enzymes are powerful biocatalysts, however, so far there is still a large gap between the number of enzyme-based practical applications and that of naturally occurring enzymes. Multiple experimental approaches have been applied to generate nearly all possible mutations of target enzymes, allowing the identification of desirable variants with improved properties to meet the practical needs. Meanwhile, an increasing number of computational methods have been developed to assist in the modification of enzymes during the past few decades. With the development of bioinformatic algorithms, computational approaches are now able to provide more precise guidance for enzyme engineering and make it more efficient and less laborious. In this review, we summarize the recent advances of method development with significant biological outcomes to provide important insights into successful computational protein designs. We also discuss the limitations and challenges of existing methods and the future directions that should improve them.

Thermostabilizing mutations preferentially occur at structural weak spots with a high mutation ratio

We apply Constraint Network Analysis (CNA) to investigate the relationship between structural rigidity and thermostability of five citrate synthase (CS) structures over a temperature range from 37 °C to 100 °C. For the first time, we introduce an ensemble-based variant of CNA and model the temperature-dependence of hydrophobic interactions in the constraint network. A very good correlation between the predicted thermostabilities of CS and optimal growth temperatures of their source organisms (R²=0.88, p=0.017) is obtained, which validates that CNA is able to quantitatively discriminate between less and more thermostable proteins even within a series of orthologs. Structural weak spots on a less thermostable CS, predicted by CNA to be in the top 5% with respect to the frequency of occurrence over an ensemble, have a higher mutation ratio in a more thermostable CS than other sequence positions. Furthermore, highly ranked weak spots that are also highly conserved with respect to the amino acid type found at that sequence position are nevertheless found to be mutated in the more stable CS. As for mechanisms at an atomic level that lead to a reinforcement of weak spots in more stable CS, we observe that the thermophilic CS achieve a higher thermostability by better hydrogen bonding networks whereas hyperthermophilic CS incorporate more hydrophobic contacts to reach the same goal. Overall, these findings suggest that CNA can be applied as a pre-filter in data-driven protein engineering to focus on residues that are highly likely to improve thermostability upon mutation.

Relationship between stability and flexibility in the most flexible region of Photinus pyralis luciferase

Firefly luciferase is a protein with a large N-terminal and a small C-terminal domain. B-factor analysis shows that its C-terminal is much more flexible than its N-terminal. Studies on hyperthermophile proteins have been shown that the increased thermal stability of hyperthermophile proteins is due to their enhanced conformational rigidity and the relationship between flexibility, stability and function in most of proteins is on debate. Two mutations (D474K and D476N) in the most flexible region of firefly luciferase were designed. Thermostability analysis shows that D476N mutation doesn't have any significant effect but D474K mutation destabilized protein. On the other hand, flexibility analysis using dynamic quenching and limited proteolysis demonstrates that D474K mutation became much more flexible than wild type although D476N doesn't have any significant difference. Intrinsic and ANS fluorescence studies demonstrate that D476N mutation is brought about by structural changes without significant effect on thermostability and flexibility. Molecular modeling reveals that disruption of a salt bridge between D(474) and K(445) accompanying with some H-bond deletion may be involved in destabilization of D474K mutant.

The contribution of coevolving residues to the stability of KDO8P synthase

Background

The evolutionary tree of 3-deoxy-D-manno-octulosonate 8-phosphate (KDO8P) synthase (KDO8PS), a bacterial enzyme that catalyzes a key step in the biosynthesis of bacterial endotoxin, is evenly divided between metal and non-metal forms, both having similar structures, but diverging in various degrees in amino acid sequence. Mutagenesis, crystallographic and computational studies have established that only a few residues determine whether or not KDO8PS requires a metal for function. The remaining divergence in the amino acid sequence of KDO8PSs is apparently unrelated to the underlying catalytic mechanism.

Methodology/Principal Findings

The multiple alignment of all known KDO8PS sequences reveals that several residue pairs coevolved, an indication of their possible linkage to a structural constraint. In this study we investigated by computational means the contribution of coevolving residues to the stability of KDO8PS. We found that about 1/4 of all strongly coevolving pairs probably originated from cycles of mutation (decreasing stability) and suppression (restoring it), while the remaining pairs are best explained by a succession of neutral or nearly neutral covarions.

Conclusions/Significance

Both sequence conservation and coevolution are involved in the preservation of the core structure of KDO8PS, but the contribution of coevolving residues is, in proportion, smaller. This is because small stability gains or losses associated with selection of certain residues in some regions of the stability landscape of KDO8PS are easily offset by a large number of possible changes in other regions. While this effect increases the tolerance of KDO8PS to deleterious mutations, it also decreases the probability that specific pairs of residues could have a strong contribution to the thermodynamic stability of the protein.

Engineering protein stability

This article defines protein stability, emphasizes its importance and surveys some notable recent publications (2004-2008) in the field of protein stability/stabilization. Knowledge of the factors stabilizing proteins has emerged from denaturation studies and from study of thermophilic (and other extremophilic) proteins. One can enhance stability by protein engineering strategies, the judicious use of solutes and additives, immobilization, and chemical modification in solution. General protocols are set out on how to measure the kinetic thermal stability of a given protein and how to undertake chemical modification of a protein in solution.