Computational redesign of a mononuclear zinc metalloenzyme for organophosphate hydrolysis

Organophosphate Hydrolysis by a Designed Metalloenzyme: Impact of Mutations Explained

The efficient design of novel enzymes has been attainable only by a combination of theoretical approaches and experimental refinement, suggesting inadequate performance of de novo design protocols. Based on the analysis of the evolutionary trajectory of a designed organophosphate hydrolase, this work aimed at developing and validating the improved theoretical models describing the catalytic activity of five enzyme variants (including wild-type as well as theoretically derived and experimentally refined enzymes) performing the hydrolysis of diethyl 7-hydroxycoumarinyl phosphate. The following aspects possibly important for enzyme design were addressed: the level of theory sufficient for a reliable description of enzyme-reactant interactions, the issue of ground state (GS) destabilization versus transition state (TS) stabilization, and the derivation of the proper side chain rotamers of amino acid residues. For enzyme variants analyzed herein, differential transition state stabilization (DTSS, i.e., preferential TS binding by an enzyme over the GS binding) calculated with a non-empirical model of the interaction energy (i.e., multipole electrostatic plus approximate dispersion terms, MED) displayed a superior performance in ranking the enzyme catalytic activity. The MED DTSS-based systematic rotamer refinement performed with an efficient scanning procedure and accounting for long-range interaction energy terms is an important step capable of unlocking the full potential impact of the given residue that could be otherwise overlooked with a conventional static approach featuring optimization to the nearby minimum. While TS stabilization is the main factor contributing to the increased catalytic activity of the de novo-designed variant studied in this work, directed evolution refinement appears to impact the catalytic activity of another enzyme variant analyzed herein via GS destabilization.

Kinetic and structural analysis of redox-reversible artificial imine reductases

Three artificial imine reductases, constructed via supramolecular anchoring utilising FeIII-azotochelin, a natural siderophore, to bind an iridium-containing catalyst to periplasmic siderophore-binding protein (PBP) scaffolds, have previously been synthesised and subjected to catalytic testing. Despite exhibiting high homology and possessing conserved siderophore anchor coordinating residues, the three artificial metalloenzymes (ArMs) displayed significant variability in turnover frequencies (TOFs). To further understand the catalytic properties of these ArMs, their kinetic behaviour was evaluated with respect to the reduction of three cyclic imines: dihydroisoquinoline, harmaline, and papaverine. Kinetic analyses revealed that all examined ArMs adhere to Michaelis-Menten kinetics, with the most pronounced saturation profile observed for the substrate harmaline. Additionally, molecular docking studies suggested varied hydrogen-bonding interactions between substrates and residues within the artificial binding pocket. Pi-stacking and pi-cation interactions were identified for harmaline and papaverine, corroborating the higher affinity of these substrates for the ArMs in comparison to dihydroisoquinoline. Furthermore, it was demonstrated that multiple cavities are capable of accommodating substrates in close proximity to the catalytic centre, thereby rationalising the moderate enantioselectivity conferred by the unmodified scaffolds.

In Vivo Synthetic Anticancer Approach by Resourcing Mouse Blood Albumin as a Biocompatible Artificial Metalloenzyme

Methods for producing drugs directly at the cancer site, particularly using bioorthogonal metal catalysts, are being explored to mitigate the side effects of therapy. Albumin-based artificial metalloenzymes (ArMs) catalyze reactions in living mice while protecting the catalyst in the hydrophobic pocket. Here, we describe the in situ preparation and application of biocompatible tumor-targeting ArMs using circulating albumin, which is abundant in the bloodstream. The ArM was formed using blood albumin through the intravenous injection of ruthenium conjugated with an albumin-binding ligand; the tumor-targeting unit was conjugated to the ArM using its catalytic activity, and the ArM was transported to the cancer site. The delivered ArM catalyzed a second tagging reaction of the proapoptotic peptide on the cancer surface, successfully suppressing cancer proliferation. This approach, which efficiently leveraged the persisting reactivity twice in vivo, holds promise for future in vivo metal-catalyzed drug synthesis utilizing endogenous albumin.

Catalytic Mechanism of Collagen Hydrolysis by Zinc(II)-Dependent Matrix Metalloproteinase-1

Human matrix metalloproteinase-1 (MMP-1) is a zinc(II)-dependent enzyme that catalyzes collagenolysis. Despite the availability of extensive experimental data, the mechanism of MMP-1-catalyzed collagenolysis remains poorly understood due to the lack of experimental structure of a catalytically productive enzyme-substrate complex of MMP-1. In this study, we apply molecular dynamics and combined quantum mechanics/molecular mechanics to reveal the reaction mechanism of MMP-1 based on a computationally modeled structure of the catalytically competent complex of MMP-1 that contains a large triple-helical peptide substrate. Our proposed mechanism involves the participation of an auxiliary (second) water molecule (wat2) in addition to the zinc(II)-coordinated water (wat1). The reaction initiates through a proton transfer to Glu219, followed by a nucleophilic attack by a zinc(II)-coordinated hydroxide anion nucleophile at the carbonyl carbon of the scissile bond, leading to the formation of a tetrahedral intermediate (IM2). The process continues with a hydrogen-bond rearrangement to facilitate proton transfer from wat2 to the amide nitrogen of the scissile bond and, finally, C-N bond cleavage. The calculations indicate that the rate-determining step is the water-mediated nucleophilic attack with an activation energy barrier of 22.3 kcal/mol. Furthermore, the calculations show that the hydrogen-bond rearrangement/proton-transfer step can proceed in a consecutive or concerted manner, depending on the conformation of the tetrahedral intermediate, with the consecutive mechanism being energetically preferable. Overall, the study reveals the crucial role of a second water molecule and the dynamics for effective MMP-1-catalyzed collagenolysis.

Design of a Flexible, Zn-Selective Protein Scaffold that Displays Anti-Irving-Williams Behavior

Selective metal binding is a key requirement not only for the functions of natural metalloproteins but also for the potential applications of artificial metalloproteins in heterogeneous environments such as cells and environmental samples. The selection of transition-metal ions through protein design can, in principle, be achieved through the appropriate choice and the precise positioning of amino acids that comprise the primary metal coordination sphere. However, this task is made difficult by the intrinsic flexibility of proteins and the fact that protein design approaches generally lack the sub-Å precision required for the steric selection of metal ions. We recently introduced a flexible/probabilistic protein design strategy (MASCoT) that allows metal ions to search for optimal coordination geometry within a flexible, yet covalently constrained dimer interface. In an earlier proof-of-principle study, we used MASCoT to generate an artificial metalloprotein dimer, (AB)₂, which selectively bound Co^II and Ni^II over Cu^II (as well as other first-row transition-metal ions) through the imposition of a rigid octahedral coordination geometry, thus countering the Irving-Williams trend. In this study, we set out to redesign (AB)₂ to examine the applicability of MASCoT to the selective binding of other metal ions. We report here the design and characterization of a new flexible protein dimer, B₂, which displays Zn^II selectivity over all other tested metal ions including Cu^II both in vitro and in cellulo. Selective, anti-Irving-Williams Zn^II binding by B₂ is achieved through the formation of a unique trinuclear Zn coordination motif in which His and Glu residues are rigidly placed in a tetrahedral geometry. These results highlight the utility of protein flexibility in the design and discovery of selective binding motifs.

Dan Tawfik's Lessons for Protein Engineers about Enzymes Adapting to New Substrates

Natural evolution has been creating new complex systems for billions of years. The process is spontaneous and requires neither intelligence nor moral purpose but is nevertheless difficult to understand. The late Dan Tawfik spent years studying enzymes as they adapted to recognize new substrates. Much of his work focused on gaining fundamental insights, so the practical utility of his experiments may not be obvious even to accomplished protein engineers. Here we focus on two questions fundamental to any directed evolution experiment. Which proteins are the best starting points for such experiments? Which trait(s) of the chosen parental protein should be evolved to achieve the desired outcome? We summarize Tawfik's contributions to our understanding of these problems, to honor his memory and encourage those unfamiliar with his ideas to read his publications.

Designing Artificial Metalloenzymes by Tuning of the Environment beyond the Primary Coordination Sphere

Metalloenzymes catalyze a variety of reactions using a limited number of natural amino acids and metallocofactors. Therefore, the environment beyond the primary coordination sphere must play an important role in both conferring and tuning their phenomenal catalytic properties, enabling active sites with otherwise similar primary coordination environments to perform a diverse array of biological functions. However, since the interactions beyond the primary coordination sphere are numerous and weak, it has been difficult to pinpoint structural features responsible for the tuning of activities of native enzymes. Designing artificial metalloenzymes (ArMs) offers an excellent basis to elucidate the roles of these interactions and to further develop practical biological catalysts. In this review, we highlight how the secondary coordination spheres of ArMs influence metal binding and catalysis, with particular focus on the use of native protein scaffolds as templates for the design of ArMs by either rational design aided by computational modeling, directed evolution, or a combination of both approaches. In describing successes in designing heme, nonheme Fe, and Cu metalloenzymes, heteronuclear metalloenzymes containing heme, and those ArMs containing other metal centers (including those with non-native metal ions and metallocofactors), we have summarized insights gained on how careful controls of the interactions in the secondary coordination sphere, including hydrophobic and hydrogen bonding interactions, allow the generation and tuning of these respective systems to approach, rival, and, in a few cases, exceed those of native enzymes. We have also provided an outlook on the remaining challenges in the field and future directions that will allow for a deeper understanding of the secondary coordination sphere a deeper understanding of the secondary coordintion sphere to be gained, and in turn to guide the design of a broader and more efficient variety of ArMs.

Introducing a New Bond-Forming Activity in an Archaeal DNA Polymerase by Structure-Guided Enzyme Redesign

DNA polymerases have evolved to feature a highly conserved activity across the tree of life: formation of, without exception, internucleotidyl O-P linkages. Can this linkage selectivity be overcome by design to produce xenonucleic acids? Here, we report that the structure-guided redesign of an archaeal DNA polymerase, 9°N, exhibits a new activity undetectable in the wild-type enzyme: catalyzing the formation of internucleotidyl N-P linkages using 3'-NH₂-ddNTPs. Replacing a metal-binding aspartate in the 9°N active site with asparagine was key to the emergence of this unnatural enzyme activity. MD simulations provided insights into how a single substitution enhances the productive positioning of a 3'-amino nucleophile in the active site. Further remodeling of the protein-nucleic acid interface in the finger subdomain yielded a quadruple-mutant variant (9°N-NRQS) displaying DNA-dependent NP-DNA polymerase activity. In addition, the engineered promiscuity of 9°N-NRQS was leveraged for one-pot synthesis of DNA─NP-DNA copolymers. This work sheds light on the molecular basis of substrate fidelity and latent promiscuity in enzymes.

Design of metalloenzyme mimics based on self-assembled peptides for organophosphorus pesticides detection

Organophosphorus pesticides (OPs) detection has attracted considerable attention because of the extensive application of OPs. In this research, non-toxic and high-performance metalloenzyme mimics of Zn²⁺-bonding peptides were developed by obtaining inspiration from phosphotriesterase (PTE) and nanofiber formation. Furthermore, based on the electrochemical activity of p-nitrophenol (PNP), the electrochemical sensor of metalloenzyme mimics was developed. By examining the effect of the active sites of peptides and fibril formation on the degradation of OPs, the optimal metalloenzyme mimic was selected. Furthermore, optimal metalloenzyme mimics were combined with NiCo₂O₄ to develop an electrochemical sensor of OPs. By monitoring square wave voltammetry (SWV) signals of PNP degraded from OPs, the amounts of OPs in actual samples could be determined in 15 min. We discovered that both the active sites of α metal and β metal were required for metalloenzyme mimics; Zn²⁺ promoted peptide fibrosis and especially acted as a cofactor for degrading OPs. Compared to traditional methods, the electrochemical sensor of metalloenzyme mimics was sensitive, reliable, and non-toxic; furthermore, the detection limit of methyl paraoxon was as low as 0.08 µM. The metalloenzyme mimics will be a promising material for detecting OPs in the food industry and environment fields.

Overcoming universal restrictions on metal selectivity by protein design

Selective metal coordination is central to the functions of metalloproteins:1,2 each metalloprotein must pair with its cognate metallocofactor to fulfil its biological role3. However, achieving metal selectivity solely through a three-dimensional protein structure is a great challenge, because there is a limited set of metal-coordinating amino acid functionalities and proteins are inherently flexible, which impedes steric selection of metals3,4. Metal-binding affinities of natural proteins are primarily dictated by the electronic properties of metal ions and follow the Irving-Williams series5 (Mn2+ < Fe2+ < Co2+ < Ni2+ < Cu2+ > Zn2+) with few exceptions6,7. Accordingly, metalloproteins overwhelmingly bind Cu2+ and Zn2+ in isolation, regardless of the nature of their active sites and their cognate metal ions1,3,8. This led organisms to evolve complex homeostatic machinery and non-equilibrium strategies to achieve correct metal speciation1,3,8-10. Here we report an artificial dimeric protein, (AB)2, that thermodynamically overcomes the Irving-Williams restrictions in vitro and in cells, favouring the binding of lower-Irving-Williams transition metals over Cu2+, the most dominant ion in the Irving-Williams series. Counter to the convention in molecular design of achieving specificity through structural preorganization, (AB)2 was deliberately designed to be flexible. This flexibility enabled (AB)2 to adopt mutually exclusive, metal-dependent conformational states, which led to the discovery of structurally coupled coordination sites that disfavour Cu2+ ions by enforcing an unfavourable coordination geometry. Aside from highlighting flexibility as a valuable element in protein design, our results illustrate design principles for constructing selective metal sequestration agents.

Computationally driven design of an artificial metalloenzyme using supramolecular anchoring strategies of iridium complexes to alcohol dehydrogenase

Artificial metalloenzymes (ArMs) confer non-biological reactivities to biomolecules, whilst taking advantage of the biomolecular architecture in terms of their selectivity and renewable origin. In particular, the design of ArMs by the supramolecular anchoring of metal catalysts to protein hosts provides flexible and easy to optimise systems. The use of cofactor dependent enzymes as hosts gives the advantage of both a (hydrophobic) binding site for the substrate and a cofactor pocket to accommodate the catalyst. Here, we present a computationally driven design approach of ArMs for the transfer hydrogenation reaction of cyclic imines, starting from the NADP⁺-dependent alcohol dehydrogenase from Thermoanaerobacter brockii (TbADH). We tested and developed a molecular docking workflow to define and optimize iridium catalysts with high affinity for the cofactor binding site of TbADH. The workflow uses high throughput docking of compound libraries to identify key structural motifs for high affinity, followed by higher accuracy docking methods on smaller, focused ligand and catalyst libraries. Iridium sulfonamide catalysts were selected and synthesised, containing either a triol, a furane, or a carboxylic acid to provide the interaction with the cofactor binding pocket. IC₅₀ values of the resulting complexes during TbADH-catalysed alcohol oxidation were determined by competition experiments and were between 4.410 mM and 0.052 mM, demonstrating the affinity of the iridium complexes for either the substrate or the cofactor binding pocket of TbADH. The catalytic activity of the free iridium complexes in solution showed a maximal turnover number (TON) of 90 for the reduction of salsolidine by the triol-functionalised iridium catalyst, whilst in the presence of TbADH, only the iridium catalyst with the triol anchoring functionality showed activity for the same reaction (TON of 36 after 24 h). The observation that the artificial metalloenzymes developed here lacked stereoselectivity demonstrates the need for the further investigation and optimisation of the ArM. Our results serve as a starting point for the design of robust artificial metalloenzymes, exploiting supramolecular anchoring to natural NAD(P)H binding pockets.

Facilitating Machine Learning-Guided Protein Engineering with Smart Library Design and Massively Parallel Assays

Protein design plays an important role in recent medical advances from antibody therapy to vaccine design. Typically, exhaustive mutational screens or directed evolution experiments are used for the identification of the best design or for improvements to the wild-type variant. Even with a high-throughput screening on pooled libraries and Next-Generation Sequencing to boost the scale of read-outs, surveying all the variants with combinatorial mutations for their empirical fitness scores is still of magnitudes beyond the capacity of existing experimental settings. To tackle this challenge, in-silico approaches using machine learning to predict the fitness of novel variants based on a subset of empirical measurements are now employed. These machine learning models turn out to be useful in many cases, with the premise that the experimentally determined fitness scores and the amino-acid descriptors of the models are informative. The machine learning models can guide the search for the highest fitness variants, resolve complex epistatic relationships, and highlight bio-physical rules for protein folding. Using machine learning-guided approaches, researchers can build more focused libraries, thus relieving themselves from labor-intensive screens and fast-tracking the optimization process. Here, we describe the current advances in massive-scale variant screens, and how machine learning and mutagenesis strategies can be integrated to accelerate protein engineering. More specifically, we examine strategies to make screens more economical, informative, and effective in discovery of useful variants.

Enhanced chemoselectivity of a plant cytochrome P450 through protein engineering of surface and catalytic residues

Cytochrome P450s (P450s) are the most versatile catalysts utilized by plants to produce structurally and functionally diverse metabolites. Given the high degree of gene redundancy and challenge to functionally characterize plant P450s, protein engineering is used as a complementary strategy to study the mechanisms of P450-mediated reactions, or to alter their functions. We previously proposed an approach of engineering plant P450s based on combining high-accuracy homology models generated by Rosetta combined with data-driven design using evolutionary information of these enzymes. With this strategy, we repurposed a multi-functional P450 (CYP87D20) into a monooxygenase after redesigning its active site. Since most plant P450s are membrane-anchored proteins that are adapted to the micro-environments of plant cells, expressing them in heterologous hosts usually results in problems of expression or activity. Here, we applied computational design to tackle these issues by simultaneous optimization of the protein surface and active site. After screening 17 variants, effective substitutions of surface residues were observed to improve both expression and activity of CYP87D20. In addition, the identified substitutions were additive and by combining them a highly efficient C11 hydroxylase of cucurbitadienol was created to participate in the mogrol biosynthesis. This study shows the importance of considering the interplay between surface and active site residues for P450 engineering. Our integrated strategy also opens an avenue to create more tailoring enzymes with desired functions for the metabolic engineering of high-valued compounds like mogrol, the precursor of natural sweetener mogrosides.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-021-00056-z.

Engineering the protein dynamics of an ancestral luciferase

Protein dynamics are often invoked in explanations of enzyme catalysis, but their design has proven elusive. Here we track the role of dynamics in evolution, starting from the evolvable and thermostable ancestral protein AncHLD-RLuc which catalyses both dehalogenase and luciferase reactions. Insertion-deletion (InDel) backbone mutagenesis of AncHLD-RLuc challenged the scaffold dynamics. Screening for both activities reveals InDel mutations localized in three distinct regions that lead to altered protein dynamics (based on crystallographic B-factors, hydrogen exchange, and molecular dynamics simulations). An anisotropic network model highlights the importance of the conformational flexibility of a loop-helix fragment of Renilla luciferases for ligand binding. Transplantation of this dynamic fragment leads to lower product inhibition and highly stable glow-type bioluminescence. The success of our approach suggests that a strategy comprising (i) constructing a stable and evolvable template, (ii) mapping functional regions by backbone mutagenesis, and (iii) transplantation of dynamic features, can lead to functionally innovative proteins.

Extension of an Atom-Atom Dispersion Function to Halogen Bonds and Its Use for Rational Design of Drugs and Biocatalysts

A dispersion function Das in the form of a damped atom-atom asymptotic expansion fitted to ab initio dispersion energies from symmetry-adapted perturbation theory was improved and extended to systems containing heavier halogen atoms. To illustrate its performance, the revised Das function was implemented in the multipole first-order electrostatic and second-order dispersion (MED) scoring model. The extension has allowed applications to a much larger set of biocomplexes than it was possible with the original Das. A reasonable correlation between MED and experimentally determined inhibitory activities was achieved in a number of test cases, including structures featuring nonphysically shortened intermonomer distances, which constitute a particular challenge for binding strength predictions. Since the MED model is also computationally efficient, it can be used for reliable and rapid assessment of the ligand affinity or multidimensional scanning of amino acid side-chain conformations in the process of rational design of novel drugs or biocatalysts.

Mathematical Modelling of Biosensing Platforms Applied for Environmental Monitoring

In recent years, mathematical modelling has known an overwhelming integration in different scientific fields. In general, modelling is used to obtain new insights and achieve more quantitative and qualitative information about systems by programming language, manipulating matrices, creating algorithms and tracing functions and data. Researchers have been inspired by these techniques to explore several methods to solve many problems with high precision. In this direction, simulation and modelling have been employed for the development of sensitive and selective detection tools in different fields including environmental control. Emerging pollutants such as pesticides, heavy metals and pharmaceuticals are contaminating water resources, thus threatening wildlife. As a consequence, various biosensors using modelling have been reported in the literature for efficient environmental monitoring. In this review paper, the recent biosensors inspired by modelling and applied for environmental monitoring will be overviewed. Moreover, the level of success and the analytical performances of each modelling-biosensor will be discussed. Finally, current challenges in this field will be highlighted.

DNA Cleavage by a De Novo Designed Protein-Titanium Complex

Titanium is one of the most abundant elements on Earth but is commonly thought to have no role in biology because of its propensity to hydrolyze. Nature stabilizes hard Lewis acidic metals from hydrolysis using a variety of mechanisms, providing inspiration for how titanium can be stabilized using biological ligands. The well-characterized Due Ferri single-chain (DFsc) de novo designed protein was developed to bind and stabilize iron and provides a binding site with hard Lewis basic residues able to bind two metal ions. We demonstrate that the DFsc scaffold stably binds 2 equiv of titanium and protects them from unwanted hydrolysis. The Ti⁴⁺-DFsc protein complex was tested for its ability to hydrolytically cleave DNA, where it was seen to linearize plasmid DNA in an overnight reaction. Ti⁴⁺-DFsc is thus the first example of a functional, soluble titanium-protein complex.

Bottom-Up Nonempirical Approach To Reducing Search Space in Enzyme Design Guided by Catalytic Fields

Currently developed protocols of theozyme design still lead to biocatalysts with much lower catalytic activity than enzymes existing in nature, and, so far, the only avenue of improvement was the in vitro laboratory-directed evolution (LDE) experiments. In this paper, we propose a different strategy based on "reversed" methodology of mutation prediction. Instead of common "top-down" approach, requiring numerous assumptions and vast computational effort, we argue for a "bottom-up" approach that is based on the catalytic fields derived directly from transition state and reactant complex wave functions. This enables direct one-step determination of the general quantitative angular characteristics of optimal catalytic site and simultaneously encompasses both the transition-state stabilization (TSS) and ground-state destabilization (GSD) effects. We further extend the static catalytic field approach by introducing a library of atomic multipoles for amino acid side-chain rotamers, which, together with the catalytic field, allow one to determine the optimal side-chain orientations of charged amino acids constituting the elusive structure of a preorganized catalytic environment. Obtained qualitative agreement with experimental LDE data for Kemp eliminase KE07 mutants validates the proposed procedure, yielding, in addition, a detailed insight into possible dynamic and epistatic effects.

Molecular Modeling for Artificial Metalloenzyme Design and Optimization

Artificial metalloenzymes (ArMs) are obtained by inserting homogeneous catalysts into biological scaffolds and are among the most promising strategies in the quest for new-to-nature biocatalysts. The quality of their design strongly depends on how three partners interact: the biological host, the "artificial cofactor," and the substrate. However, structural characterization of functional artificial metalloenzymes by X-ray or NMR is often partial, elusive, or absent. How the cofactor binds to the protein, how the receptor reorganizes upon the binding of the cofactor and the substrate, and which are the binding mode(s) of the substrate for the reaction to proceed are key questions that are frequently unresolved yet crucial for ArM design. Such questions may eventually be solved by molecular modeling but require a step change beyond the current state-of-the-art methodologies.Here, we summarize our efforts in the study of ArMs, presenting both the development of computational strategies and their application. We first focus on our integrative computational framework that incorporates a variety of methods such as protein-ligand docking, classical molecular dynamics (MD), and pure quantum mechanical (QM) methods, which, when properly combined, are able to depict questions that range from host-cofactor binding predictions to simulations of entire catalytic mechanisms. We also pay particular attention to the protein-ligand docking strategies that we have developed to accurately predict the binding of transition metal-containing molecules to proteins. While this aspect is fundamental to many bioinorganic fields beyond ArMs, it has been disregarded from the molecular modeling landscape until very recently.Next we describe how to apply this computational framework to particular ArMs including systems previously characterized experimentally as well as others where computation served to guide the design. We start with the prediction of the interactions between homogeneous catalysts and biological hosts. Protein-ligand docking is pivotal at that stage, but it needs to be combined with QM/MM or MD approaches when the binding of the cofactor implies significant conformational changes of the protein or involve changes of the electronic state of the metal.Then, we summarize molecular modeling studies aimed at identifying cofactor-substrate arrangements inside the ArM active pocket that are consistent with its reactivity. These calculations stand on "Theozyme"-like dockings, MD-refined or not, which provide molecular rationale of the catalytic profiles of the artificial systems.In the third section, we present case studies to decode the entire catalytic mechanism of two ArMs: (1) an iridium based asymmetric transfer hydrogenase obtained by insertion of Noyori's catalyst into streptavidin and (2) a metallohydrolase achieved by including a receptor. Transition states, second coordination sphere effects, as well as motions of the cofactors are identified as drivers of the enantiomeric profiles.Finally, we report computer-aided designs of ArMs to guide experiments toward chemical and mutational changes that improve their activity and/or enantioselective profiles and expand toward future directions.

Proteins as diverse, efficient, and evolvable scaffolds for artificial metalloenzymes

We have extracted and categorized the desirable properties of proteins that are adapted as the scaffolds for artificial metalloenzymes.

Unlocking the therapeutic potential of artificial metalloenzymes

In order to harness the functionality of metals, nature has evolved over billions of years to utilize metalloproteins as key components in numerous cellular processes. Despite this, transition metals such as ruthenium, palladium, iridium, and gold are largely absent from naturally occurring metalloproteins, likely due to their scarcity as precious metals. To mimic the evolutionary process of nature, the field of artificial metalloenzymes (ArMs) was born as a way to benefit from the unique chemoselectivity and orthogonality of transition metals in a biological setting. In its current state, numerous examples have successfully incorporated transition metals into a variety of protein scaffolds. Using these ArMs, many examples of new-to-nature reactions have been carried out, some of which have shown substantial biocompatibility. Given the rapid rate at which this field is growing, this review aims to highlight some important studies that have begun to take the next step within this field; namely the development of ArM-centered drug therapies or biotechnological tools.

Minimalist de novo Design of Protein Catalysts

The field of protein design has grown enormously in the past few decades. In this review we discuss the minimalist approach to design of artificial enzymes, in which protein sequences are created with the minimum number of elements for folding and function. This method relies on identifying starting points in catalytically inert scaffolds for active site installation. The progress of the field from the original helical assemblies of the 1980s to the more complex structures of the present day is discussed, highlighting the variety of catalytic reactions which have been achieved using these methods. We outline the strengths and weaknesses of the minimalist approaches, describe representative design cases and put it in the general context of the de novo design of proteins.

Artificial Metalloenzymes: Challenges and Opportunities

Artificial metalloenzymes (ArMs) result from the incorporation of an abiotic metal cofactor within a protein scaffold. From the earliest techniques of transition metals adsorbed on silk fibers, the field of ArMs has expanded dramatically over the past 60 years to encompass a range of reaction classes and inspired approaches: Assembly of the ArMs has taken multiple forms with both covalent and supramolecular anchoring strategies, while the scaffolds have been intuitively selected and evolved, repurposed, or designed in silico. Herein, we discuss some of the most prominent recent examples of ArMs to highlight the challenges and opportunities presented by the field.

Sn-Triggered Two-Dimensional Fast Protein Assembly with Emergent Functions

The discovery of a general strategy for organizing functional proteins into stable nanostructures with the desired dimension, shape, and function is an important focus in developing protein-based self-assembled materials, but the scalable synthesis of such materials and transfer to other substrates remain great challenges. We herein tackle this issue by creating a two-dimensional metal-protein hybrid nanofilm that is flexible and cost-effective with reliable self-recovery, stability, and multifunctionality. As it differs from traditional metal ions, we discover the capability of Sn²⁺ to initiate fast amyloid-like protein assembly (occurring in seconds) by effectively reducing the disulfide bonds of native globular proteins. The Sn²⁺-initiated lysozyme aggregation at the air/water interface leads to droplet flattening, a result never before reported in a protein system, which finally affords a multifunctional 2D Sn-doped hybrid lysozyme nanofilm with an ultralarge area (e.g., 0.2 m²) within a few minutes. The hybrid film is distinctive in its ease of coating on versatile material surfaces with endurable chemical and mechanical stability, optical transparency, and diverse end uses in antimicrobial and photo-/electrocatalytic scaffolds. Our approach provides not only insights into the effect of tin ions on macroscopic self-assembly of proteins but also a controllable and scalable synthesis of a potential biomimic framework for biomedical and biocatalytic applications.

Tandem catalysis driven by enzymes directed hybrid nanoflowers for on-site ultrasensitive detection of organophosphorus pesticide

Accurate analysis of organophosphate pesticides (OPs) with portable devices remain an elusive goal that have received widespread investigative attention in the areas of environmental contamination and disease prevention. Herein, using all-in-one enzyme-inorganic hybrid nanoflowers (ACC-HNFs) to fabricate high-performance artificial enzyme cascade system, we established a sensitive and affordable lab-on-paper biosensor. This biosensor incorporated disposable screen-printed carbon electrode (SPCE) and colorimetric test strips, which enabled the dual-modal readout (electrochemical and colorimetric signal) for on-site monitoring of OPs, achieving an "on-demand" tuning of the detection performance. Using paraoxon as a model analyte, the ACC-HNFs-based lab-on-paper platform could reach a limit of detection down to the femtogram/mL level (6 fg mL^-1). Meticulous design of ACC-HNFs provided a versatile approach for constructing artificial enzyme as a recognizer and amplifier to fill the gap in constructing robust artificial enzyme systems which can be used for on-site contamination monitoring and biological diagnosis.

Nanozymes: Classification, Catalytic Mechanisms, Activity Regulation, and Applications

Because of the high catalytic activities and substrate specificity, natural enzymes have been widely used in industrial, medical, and biological fields, etc. Although promising, they often suffer from intrinsic shortcomings such as high cost, low operational stability, and difficulties of recycling. To overcome these shortcomings, researchers have been devoted to the exploration of artificial enzyme mimics for a long time. Since the discovery of ferromagnetic nanoparticles with intrinsic horseradish peroxidase-like activity in 2007, a large amount of studies on nanozymes have been constantly emerging in the next decade. Nanozymes are one kind of nanomaterials with enzymatic catalytic properties. Compared with natural enzymes, nanozymes have the advantages such as low cost, high stability and durability, which have been widely used in industrial, medical, and biological fields. A thorough understanding of the possible catalytic mechanisms will contribute to the development of novel and high-efficient nanozymes, and the rational regulations of the activities of nanozymes are of great significance. In this review, we systematically introduce the classification, catalytic mechanism, activity regulation as well as recent research progress of nanozymes in the field of biosensing, environmental protection, and disease treatments, etc. in the past years. We also propose the current challenges of nanozymes as well as their future research focus. We anticipate this review may be of significance for the field to understand the properties of nanozymes and the development of novel nanomaterials with enzyme mimicking activities.

Hydrolytic zinc metallopeptides using a computational multi-state design approach

Combination of multi-state design and long-timescale conformational dynamics as a powerful strategy to obtain metalloenzymes.

Artificial β-propeller protein-based hydrolases

We investigated symmetrical β-propeller protein scaffolds as artificial hydrolases and discovered their catalytic mechanism to be centred around a threonine–histidine dyad.

Using molecular dynamics simulations to evaluate active designs of cephradine hydrolase by molecular mechanics/Poisson–Boltzmann surface area and molecular mechanics/generalized Born surface area methods

The poor predictive accuracy of current computational enzyme design methods has led to low success rates of producing highly active variants that target non-natural substrates. In this report, a quantitative assessment approach based on molecular dynamics (MD) simulations was developed to eliminate false-positive enzyme designs at the computational stage. Taking cephradine hydrolase as an example, the apparent Michaelis binding constant (K_m) and catalytic efficiency (k_cat/K_m) of designed variants were correlated with binding free energies and activation energy barriers, respectively, as calculated by molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) methods with explicit water considered based on general MD simulation protocols. The correlation results showed that both the MM/GBSA and MM/PBSA methods with a protein dielectric constant (ε_p = 4) could rank the variants well based on the predicted binding free energies between enzyme and the substrate. Furthermore, the activation energy barriers calculated by the MM/PBSA method with an ε_p = 24 correlated well with k_cat/K_m. Thus, false-positive variants obtained by the enzyme design program PRODA were eliminated prior to experimentation. Therefore, MD simulation-based quantitative assessment of designed variants greatly enhanced the predictive accuracy of computational enzyme design tools and should facilitate the construction of artificial enzymes with high catalytic activities toward non-natural substrates.

A quantitative assessment method for computational enzyme design was developed to rank the active designs of cephradine hydrolase based on molecular dynamics simulation.

Automated Design of Efficient and Functionally Diverse Enzyme Repertoires

Substantial improvements in enzyme activity demand multiple mutations at spatially proximal positions in the active site. Such mutations, however, often exhibit unpredictable epistatic (non-additive) effects on activity. Here we describe FuncLib, an automated method for designing multipoint mutations at enzyme active sites using phylogenetic analysis and Rosetta design calculations. We applied FuncLib to two unrelated enzymes, a phosphotriesterase and an acetyl-CoA synthetase. All designs were active, and most showed activity profiles that significantly differed from the wild-type and from one another. Several dozen designs with only 3-6 active-site mutations exhibited 10- to 4,000-fold higher efficiencies with a range of alternative substrates, including hydrolysis of the toxic organophosphate nerve agents soman and cyclosarin and synthesis of butyryl-CoA. FuncLib is implemented as a web server (http://FuncLib.weizmann.ac.il); it circumvents iterative, high-throughput experimental screens and opens the way to designing highly efficient and diverse catalytic repertoires.

In silico design of potentially functional artificial metallo-haloalkane dehalogenase containing catalytic zinc

Artificial metalloenzymes are unique as they combine the good features of homogeneous and enzymatic catalysts, and they can potentially improve some difficult catalytic assays. This study reports a method that can be used to create an artificial metal-binding site prior to proving it to be functional in a wet lab. Haloalkane dehalogenase was grafted into a metal-binding site to form an artificial metallo-haloalkane dehalogenase and was studied for its potential functionalities in silico. Computational protocols regarding dynamic metal docking were studied using native metalloenzymes and functional artificial metalloenzymes. Using YASARA Structure, a simulation box covering template structure was created to be filled with water molecules followed by one mutated water molecule closest to the metal-binding site to metal ion. A simple energy minimization step was subsequently run using an AMBER force field to allow the metal ion to interact with the metal-binding residues. Long molecular dynamic simulation using YASARA Structure was performed to analyze the stability of the metal-binding site and the distance between metal-binding residues. Metal ions fluctuating around 2.0 Å across a 20 ns simulation indicated a stable metal-binding site. Metal-binding energies were predicted using FoldX, with a native metalloenzyme (carbonic anhydrase) scoring 18.0 kcal/mol and the best mutant model (C1a) scoring 16.4 kcal/mol. Analysis of the metal-binding site geometry was performed using CheckMyMetal, and all scores for the metalloenzymes and mutant models were in an acceptable range. Like native metalloenzymes, the metal-binding site of C1a was supported by residues in the second coordination shell to maintain a more coordinated metal-binding site. Short-chain multihalogenated alkanes (1,2-dibromoethane and 1,2,3-trichloropropane) were able to dock in the active site of C1a. The halides of the substrate were in contact with both the metal and halide-stabilizing residues, thus indicating a better stabilization of the substrate. The simple catalytic mechanism proposed is that the metal ion interacted with halogen and polarized the carbon-halogen bond, thus making the alpha carbon susceptible to attack by nucleophilic hydroxide. The interaction between halogen in the metal ion and halide-stabilizing residues may help to improve the stabilization of the substrate-enzyme complex and reduce the activation energy. This study reports a modified dynamic metal-docking protocol and validation tests to verify the metal-binding site. These approaches can be applied to design different kinds of artificial metalloenzymes or metal-binding sites.