Click, Compute, Create: A Review of Web-based Tools for Enzyme Engineering.

Enzyme engineering, though pivotal across various biotechnological domains, is often plagued by its time-consuming and labor-intensive nature. This review aims to offer an overview of supportive in silico methodologies for this demanding endeavor. Starting from methods to predict protein structures, to classification of their activity and even the discovery of new enzymes we continue with describing tools used to increase thermostability and production yields of selected targets. Subsequently, we discuss computational methods to modulate both, the activity as well as selectivity of enzymes. Last, we present recent approaches based on cutting-edge machine learning methods to redesign enzymes. With exception of the last chapter, there is a strong focus on methods easily accessible via web-interfaces or simple Python-scripts, therefore readily useable for a diverse and broad community.

Flattening the curve-How to get better results with small deep-mutational-scanning datasets.

Proteins are used in various biotechnological applications, often requiring the optimization of protein properties by introducing specific amino-acid exchanges. Deep mutational scanning (DMS) is an effective high-throughput method for evaluating the effects of these exchanges on protein function. DMS data can then inform the training of a neural network to predict the impact of mutations. Most approaches use some representation of the protein sequence for training and prediction. As proteins are characterized by complex structures and intricate residue interaction networks, directly providing structural information as input reduces the need to learn these features from the data. We introduce a method for encoding protein structures as stacked 2D contact maps, which capture residue interactions, their evolutionary conservation, and mutation-induced interaction changes. Furthermore, we explored techniques to augment neural network training performance on smaller DMS datasets. To validate our approach, we trained three neural network architectures originally used for image analysis on three DMS datasets, and we compared their performances with networks trained solely on protein sequences. The results confirm the effectiveness of the protein structure encoding in machine learning efforts on DMS data. Using structural representations as direct input to the networks, along with data augmentation and pretraining, significantly reduced demands on training data size and improved prediction performance, especially on smaller datasets, while performance on large datasets was on par with state-of-the-art sequence convolutional neural networks. The methods presented here have the potential to provide the same workflow as DMS without the experimental and financial burden of testing thousands of mutants. Additionally, we present an open-source, user-friendly software tool to make these data analysis techniques accessible, particularly to biotechnology and protein engineering researchers who wish to apply them to their mutagenesis data.

Sterol interactions influence the function of Wsc sensors.

The Wsc1, Wsc2, and Wsc3 proteins are essential cell surface sensors that respond to cell wall perturbation by activating the cell wall integrity pathway (CWIP). We show here that in situ production of cholesterol (in place of ergosterol) induces hyper-phosphorylation of Slt2, the MAPK of the CWIP, and upregulates cell wall biosynthesis. Deletion of all three Wsc genes in K. phaffii reverts these phenotypes. In the cholesterol-producing strain, both Wsc1 and Wsc3 accumulate in the plasma membrane. Close inspection of the transmembrane domains of all three Wsc proteins predicted by AlphaFold2 revealed the presence of CRAC sterol-binding motifs. Experiments using a photoreactive cholesterol derivative indicate intimate interaction of this sterol with the Wsc transmembrane domain, and this apparent sterol binding was abrogated in Wsc mutants with substitutions in the CRAC motif. We also observed cholesterol interaction with CRAC-like motifs in the transmembrane domains of mammalian integrins, analogs of Wsc proteins. Our results suggest that proper signaling of the Wsc sensors requires highly specific binding of the native endogenous terminal sterol, ergosterol.

Essential Functional Interplay of the Catalytic Groups in Acid Phosphatase.

The cooperative interplay between the functional devices of a preorganized active site is fundamental to enzyme catalysis. An in-depth understanding of this phenomenon is central to elucidating the remarkable efficiency of natural enzymes and provides an essential benchmark for enzyme design and engineering. Here, we study the functional interconnectedness of the catalytic nucleophile (His18) in an acid phosphatase by analyzing the consequences of its replacement with aspartate. We present crystallographic, biochemical, and computational evidence for a conserved mechanistic pathway via a phospho-enzyme intermediate on Asp18. Linear free-energy relationships for phosphoryl transfer from phosphomonoester substrates to His18/Asp18 provide evidence for the cooperative interplay between the nucleophilic and general-acid catalytic groups in the wild-type enzyme, and its substantial loss in the H18D variant. As an isolated factor of phosphatase efficiency, the advantage of a histidine compared to an aspartate nucleophile is ∼104-fold. Cooperativity with the catalytic acid adds ≥102-fold to that advantage. Empirical valence bond simulations of phosphoryl transfer from glucose 1-phosphate to His and Asp in the enzyme explain the loss of activity of the Asp18 enzyme through a combination of impaired substrate positioning in the Michaelis complex, as well as a shift from early to late protonation of the leaving group in the H18D variant. The evidence presented furthermore suggests that the cooperative nature of catalysis distinguishes the enzymatic reaction from the corresponding reaction in solution and is enabled by the electrostatic preorganization of the active site. Our results reveal sophisticated discrimination in multifunctional catalysis of a highly proficient phosphatase active site.

Derivatives of Natural Organocatalytic Cofactors and Artificial Organocatalytic Cofactors as Catalysts in Enzymes.

Catalytically active non-metal cofactors in enzymes carry out a variety of different reactions. The efforts to develop derivatives of naturally occurring cofactors such as flavins or pyridoxal phosphate and the advances to design new, non-natural cofactors are reviewed here. We report the status quo for enzymes harboring organocatalysts as derivatives of natural cofactors or as artificial ones and their application in the asymmetric synthesis of various compounds.

Structure of the Reductase Domain of a Fungal Carboxylic Acid Reductase and Its Substrate Scope in Thioester and Aldehyde Reduction.

The synthesis of aldehydes from carboxylic acids has long been a challenge in chemistry. In contrast to the harsh chemically driven reduction, enzymes such as carboxylic acid reductases (CARs) are considered appealing biocatalysts for aldehyde production. Although structures of single- and didomains of microbial CARs have been reported, to date no full-length protein structure has been elucidated. In this study, we aimed to obtain structural and functional information regarding the reductase (R) domain of a CAR from the fungus Neurospora crassa (Nc). The NcCAR R-domain revealed activity for N-acetylcysteamine thioester (S-(2-acetamidoethyl) benzothioate), which mimics the phosphopantetheinylacyl-intermediate and can be anticipated as the minimal substrate for thioester reduction by CARs. The determined crystal structure of the NcCAR R-domain reveals a tunnel that putatively harbors the phosphopantetheinylacyl-intermediate, which is in good agreement with docking experiments performed with the minimal substrate. In vitro studies were performed with this highly purified R-domain and NADPH, demonstrating carbonyl reduction activity. The R-domain was able to accept not only a simple aromatic ketone but also benzaldehyde and octanal, which are typically considered to be the final product of carboxylic acid reduction by CAR. Also, the full-length NcCAR reduced aldehydes to primary alcohols. In conclusion, aldehyde overreduction can no longer be attributed exclusively to the host background.

A Novel High-Throughput Nanopore-Sequencing-Based Strategy for Rapid and Automated S-Protein Typing of SARS-CoV-2 Variants.

Rapid molecular surveillance of SARS-CoV-2 S-protein variants leading to immune escape and/or increased infectivity is of utmost importance. Among global bottlenecks for variant monitoring in diagnostic settings are sequencing and bioinformatics capacities. In this study, we aimed to establish a rapid and user-friendly protocol for high-throughput S-gene sequencing and subsequent automated identification of variants. We designed two new primer pairs to amplify only the immunodominant part of the S-gene for nanopore sequencing. Furthermore, we developed an automated "S-Protein-Typer" tool that analyzes and reports S-protein mutations on the amino acid level including a variant of concern indicator. Validation of our primer panel using SARS-CoV-2-positive respiratory specimens covering a broad Ct range showed successful amplification for 29/30 samples. Restriction to the region of interest freed sequencing capacity by a factor of 12-13, compared with whole-genome sequencing. Using either the MinION or Flongle flow cell, our sequencing strategy reduced the time required to identify SARS-CoV-2 variants accordingly. The S-Protein-Typer tool identified all mutations correctly when challenged with our sequenced samples and 50 deposited sequences covering all VOCs (December 2021). Our proposed S-protein variant screening offers a simple, more rapid, and low-cost entry into NGS-based SARS-CoV-2 analysis, compared with current whole-genome approaches.

A local platform for user-friendly FAIR data management and reproducible analytics.

Collaborative research is common practice in modern life sciences. For most projects several researchers from multiple universities collaborate on a specific topic. Frequently, these research projects produce a wealth of data that requires central and secure storage, which should also allow for easy sharing among project participants. Only under best circumstances, this comes with minimal technical overhead for the researchers. Moreover, the need for data to be analyzed in a reproducible way often poses a challenge for researchers without a data science background and thus represents an overly time-consuming process. Here, we report on the integration of CyVerse Austria (CAT), a new cyberinfrastructure for a local community of life science researchers, and provide two examples how it can be used to facilitate FAIR data management and reproducible analytics for teaching and research. In particular, we describe in detail how CAT can be used (i) as a teaching platform with a defined software environment and data management/sharing possibilities, and (ii) to build a data analysis pipeline using the Docker technology tailored to the needs and interests of the researcher.

Computational backbone design enables soluble engineering of transferrin receptor apical domain.

Supply of iron into human cells is achieved by iron carrier protein transferrin and its receptor that upon complex formation get internalized by endocytosis. Similarly, the iron needs to be delivered into the brain, and necessitates the transport across the blood-brain barrier. While there are still unanswered questions about these mechanisms, extensive efforts have been made to use the system for delivery of therapeutics into biological compartments. The dimeric form of the receptor, where each subunit consists of three domains, further complicates the detailed investigation of molecular determinants responsible for guiding the receptor interactions with other proteins. Especially the apical domain's biological function has been elusive. To further the study of transferrin receptor, we have computationally decoupled the apical domain for soluble expression, and validated the design strategy by structure determination. Besides presenting a methodology for solubilizing domains, the results will allow for study of apical domain's function.

De novo design of a homo-trimeric amantadine-binding protein.

The computational design of a symmetric protein homo-oligomer that binds a symmetry-matched small molecule larger than a metal ion has not yet been achieved. We used de novo protein design to create a homo-trimeric protein that binds the C3 symmetric small molecule drug amantadine with each protein monomer making identical interactions with each face of the small molecule. Solution NMR data show that the protein has regular three-fold symmetry and undergoes localized structural changes upon ligand binding. A high-resolution X-ray structure reveals a close overall match to the design model with the exception of water molecules in the amantadine binding site not included in the Rosetta design calculations, and a neutron structure provides experimental validation of the computationally designed hydrogen-bond networks. Exploration of approaches to generate a small molecule inducible homo-trimerization system based on the design highlight challenges that must be overcome to computationally design such systems.

De novo design of self-assembling helical protein filaments.

We describe a general computational approach to designing self-assembling helical filaments from monomeric proteins and use this approach to design proteins that assemble into micrometer-scale filaments with a wide range of geometries in vivo and in vitro. Cryo-electron microscopy structures of six designs are close to the computational design models. The filament building blocks are idealized repeat proteins, and thus the diameter of the filaments can be systematically tuned by varying the number of repeat units. The assembly and disassembly of the filaments can be controlled by engineered anchor and capping units built from monomers lacking one of the interaction surfaces. The ability to generate dynamic, highly ordered structures that span micrometers from protein monomers opens up possibilities for the fabrication of new multiscale metamaterials.

De novo design of a non-local ß-sheet protein with high stability and accuracy.

ß-sheet proteins carry out critical functions in biology, and hence are attractive scaffolds for computational protein design. Despite this potential, de novo design of all-ß-sheet proteins from first principles lags far behind the design of all-α or mixed-αß domains owing to their non-local nature and the tendency of exposed ß-strand edges to aggregate. Through study of loops connecting unpaired ß-strands (ß-arches), we have identified a series of structural relationships between loop geometry, side chain directionality and ß-strand length that arise from hydrogen bonding and packing constraints on regular ß-sheet structures. We use these rules to de novo design jellyroll structures with double-stranded ß-helices formed by eight antiparallel ß-strands. The nuclear magnetic resonance structure of a hyperthermostable design closely matched the computational model, demonstrating accurate control over the ß-sheet structure and loop geometry. Our results open the door to the design of a broad range of non-local ß-sheet protein structures.

Principles for designing proteins with cavities formed by curved ß sheets.

Active sites and ligand-binding cavities in native proteins are often formed by curved ß sheets, and the ability to control ß-sheet curvature would allow design of binding proteins with cavities customized to specific ligands. Toward this end, we investigated the mechanisms controlling ß-sheet curvature by studying the geometry of ß sheets in naturally occurring protein structures and folding simulations. The principles emerging from this analysis were used to design, de novo, a series of proteins with curved ß sheets topped with α helices. Nuclear magnetic resonance and crystal structures of the designs closely match the computational models, showing that ß-sheet curvature can be controlled with atomic-level accuracy. Our approach enables the design of proteins with cavities and provides a route to custom design ligand-binding and catalytic sites.

Computational design of a homotrimeric metalloprotein with a trisbipyridyl core.

Metal-chelating heteroaryl small molecules have found widespread use as building blocks for coordination-driven, self-assembling nanostructures. The metal-chelating noncanonical amino acid (2,2'-bipyridin-5yl)alanine (Bpy-ala) could, in principle, be used to nucleate specific metalloprotein assemblies if introduced into proteins such that one assembly had much lower free energy than all alternatives. Here we describe the use of the Rosetta computational methodology to design a self-assembling homotrimeric protein with [Fe(Bpy-ala)3]2+ complexes at the interface between monomers. X-ray crystallographic analysis of the homotrimer showed that the design process had near-atomic-level accuracy: The all-atom rmsd between the design model and crystal structure for the residues at the protein interface is ∼1.4 Å. These results demonstrate that computational protein design together with genetically encoded noncanonical amino acids can be used to drive formation of precisely specified metal-mediated protein assemblies that could find use in a wide range of photophysical applications.

Structure of a Berberine Bridge Enzyme-Like Enzyme with an Active Site Specific to the Plant Family Brassicaceae.

Berberine bridge enzyme-like (BBE-like) proteins form a multigene family (pfam 08031), which is present in plants, fungi and bacteria. They adopt the vanillyl alcohol-oxidase fold and predominantly show bi-covalent tethering of the FAD cofactor to a cysteine and histidine residue, respectively. The Arabidopsis thaliana genome was recently shown to contain genes coding for 28 BBE-like proteins, while featuring four distinct active site compositions. We determined the structure of a member of the AtBBE-like protein family (termed AtBBE-like 28), which has an active site composition that has not been structurally and biochemically characterized thus far. The most salient and distinguishing features of the active site found in AtBBE-like 28 are a mono-covalent linkage of a histidine to the 8α-position of the flavin-isoalloxazine ring and the lack of a second covalent linkage to the 6-position, owing to the replacement of a cysteine with a histidine. In addition, the structure reveals the interaction of a glutamic acid (Glu426) with an aspartic acid (Asp369) at the active site, which appear to share a proton. This arrangement leads to the delocalization of a negative charge at the active site that may be exploited for catalysis. The structure also indicates a shift of the position of the isoalloxazine ring in comparison to other members of the BBE-like family. The dioxygen surrogate chloride was found near the C(4a) position of the isoalloxazine ring in the oxygen pocket, pointing to a rapid reoxidation of reduced enzyme by dioxygen. A T-DNA insertional mutant line for AtBBE-like 28 results in a phenotype, that is characterized by reduced biomass and lower salt stress tolerance. Multiple sequence analysis showed that the active site composition found in AtBBE-like 28 is only present in the Brassicaceae, suggesting that it plays a specific role in the metabolism of this plant family.

De novo design of protein homo-oligomers with modular hydrogen-bond network-mediated specificity.

In nature, structural specificity in DNA and proteins is encoded differently: In DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here, we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen-bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen-bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen-bond networks with atomic accuracy enables the programming of protein interaction specificity for a broad range of synthetic biology applications; more generally, our results demonstrate that, even with the tremendous diversity observed in nature, there are fundamentally new modes of interaction to be discovered in proteins.

The crystal structure of D-threonine aldolase from Alcaligenes xylosoxidans provides insight into a metal ion assisted PLP-dependent mechanism.

Threonine aldolases catalyze the pyridoxal phosphate (PLP) dependent cleavage of threonine into glycine and acetaldehyde and play a major role in the degradation of this amino acid. In nature, L- as well as D-specific enzymes have been identified, but the exact physiological function of D-threonine aldolases (DTAs) is still largely unknown. Both types of enantio-complementary enzymes have a considerable potential in biocatalysis for the stereospecific synthesis of various ß-hydroxy amino acids, which are valuable building blocks for the production of pharmaceuticals. While several structures of L-threonine aldolases (LTAs) have already been determined, no structure of a DTA is available to date. Here, we report on the determination of the crystal structure of the DTA from Alcaligenes xylosoxidans (AxDTA) at 1.5 Å resolution. Our results underline the close relationship of DTAs and alanine racemases and allow the identification of a metal binding site close to the PLP-cofactor in the active site of the enzyme which is consistent with the previous observation that divalent cations are essential for DTA activity. Modeling of AxDTA substrate complexes provides a rationale for this metal dependence and indicates that binding of the ß-hydroxy group of the substrate to the metal ion very likely activates this group and facilitates its deprotonation by His193. An equivalent involvement of a metal ion has been implicated in the mechanism of a serine dehydratase, which harbors a metal ion binding site in the vicinity of the PLP cofactor at the same position as in DTA. The structure of AxDTA is completely different to available structures of LTAs. The enantio-complementarity of DTAs and LTAs can be explained by an approximate mirror symmetry of crucial active site residues relative to the PLP-cofactor.

High thermodynamic stability of parametrically designed helical bundles.

We describe a procedure for designing proteins with backbones produced by varying the parameters in the Crick coiled coil-generating equations. Combinatorial design calculations identify low-energy sequences for alternative helix supercoil arrangements, and the helices in the lowest-energy arrangements are connected by loop building. We design an antiparallel monomeric untwisted three-helix bundle with 80-residue helices, an antiparallel monomeric right-handed four-helix bundle, and a pentameric parallel left-handed five-helix bundle. The designed proteins are extremely stable (extrapolated ΔGfold > 60 kilocalories per mole), and their crystal structures are close to those of the design models with nearly identical core packing between the helices. The approach enables the custom design of hyperstable proteins with fine-tuned geometries for a wide range of applications.

Engineering V-type nerve agents detoxifying enzymes using computationally focused libraries.

VX and its Russian (RVX) and Chinese (CVX) analogues rapidly inactivate acetylcholinesterase and are the most toxic stockpile nerve agents. These organophosphates have a thiol leaving group with a choline-like moiety and are hydrolyzed very slowly by natural enzymes. We used an integrated computational and experimental approach to increase Brevundimonas diminuta phosphotriesterase's (PTE) detoxification rate of V-agents by 5000-fold. Computational models were built of the complex between PTE and V-agents. On the basis of these models, the active site was redesigned to be complementary in shape to VX and RVX and to include favorable electrostatic interactions with their choline-like leaving group. Small libraries based on designed sequences were constructed. The libraries were screened by a direct assay for V-agent detoxification, as our initial studies showed that colorimetric surrogates fail to report the detoxification rates of the actual agents. The experimental results were fed back to improve the computational models. Overall, five rounds of iterating between experiment and model refinement led to variants that hydrolyze the toxic SP isomers of all three V-agents with kcat/KM values of up to 5 × 10(6) M(-1) min(-1) and also efficiently detoxify G-agents. These new catalysts provide the basis for broad spectrum nerve agent detoxification.

Fusion of binding domains to Thermobifida cellulosilytica cutinase to tune sorption characteristics and enhancing PET hydrolysis.

A cutinase from Thermomyces cellullosylitica (Thc_Cut1), hydrolyzing the synthetic polymer polyethylene terephthalate (PET), was fused with two different binding modules to improve sorption and thereby hydrolysis. The binding modules were from cellobiohydrolase I from Hypocrea jecorina (CBM) and from a polyhydroxyalkanoate depolymerase from Alcaligenes faecalis (PBM). Although both binding modules have a hydrophobic nature, it was possible to express the proteins in E. coli . Both fusion enzymes and the native one had comparable kcat values in the range of 311 to 342 s(-1) on pNP-butyrate, while the catalytic efficiencies kcat/Km decreased from 0.41 s(-1)/ µM (native enzyme) to 0.21 and 0.33 s(-1)/µM for Thc_Cut1+PBM and Thc_Cut1+CBM, respectively. The fusion enzymes were active both on the insoluble PET model substrate bis(benzoyloxyethyl) terephthalate (3PET) and on PET although the hydrolysis pattern was differed when compared to Thc_Cut1. Enhanced adsorption of the fusion enzymes was visible by chemiluminescence after incubation with a 6xHisTag specific horseradish peroxidase (HRP) labeled probe. Increased adsorption to PET by the fusion enzymes was confirmed with Quarz Crystal Microbalance (QCM-D) analysis and indeed resulted in enhanced hydrolysis activity (3.8× for Thc_Cut1+CBM) on PET, as quantified, based on released mono/oligomers.