Toward the Computational Design of Artificial Metalloenzymes: From Protein–Ligand Docking to Multiscale Approaches

Rationalization of a Streptavidin Based Enantioselective Artificial Suzukiase: An Integrative Computational Approach

An Artificial Metalloenzyme (ArM) built employing the streptavidin-biotin technology has been used for the enantioselective synthesis of binaphthyls by means of asymmetric Suzuki-Miyaura cross-coupling reactions. Despite its success, it remains a challenge to understand how the length of the biotin cofactors or the introduction of mutations to streptavidin leads the preferential synthesis of one atropisomer over the other. In this study, we apply an integrated computational modeling approach, including DFT calculations, protein-ligand dockings and molecular dynamics to rationalize the impact of mutations and length of the biotion cofactor on the enantioselectivities of the biaryl product. The results unravel that the enantiomeric differences found experimentally can be rationalized by the disposition of the first intermediate, coming from the oxidative addition step, and the entrance of the second substrate. The work also showcases the difficulties facing to control the enantioselection when engineering ArM to catalyze enantioselective Suzuki-Miyaura couplings and how the combination of DFT calculations, molecular dockings and MD simulations can be used to rationalize artificial metalloenzymes.

Virtual screening and molecular growth guide the design of inhibitors for the influenza virus drug-resistant mutant M2-V27A/S31N

The influenza A virus matrix protein 2 (AM2) protein is a proton-gated, proton-selective ion channel essential for influenza replication that has been identified as an antiviral target. The drug-resistance of the M2-V27A/S31N strain, which has been growing more prevalent in recent years and has the potential to spread globally, prevents current amantadine inhibitors from having the desired impact. In this study, we compiled the most common influenza A virus strains from 2001-2020 from the U.S. National Center for Biotechnology Information database and hypothesized that M2-V27A/S31N would become a common strain. The lead compound ZINC299830590 was screened for M2-V27A/S31N in the ZINC15 database using a pharmacophore model and molecular descriptors. This lead compound was then optimized by molecular growth, which allowed us to identify important amino acid residues and create interactions with them to produce compound 4. Molecular dynamics simulation showed that the complex of compound 4 and M2-V27A/S31N had certain degrees of stability and flexibility. The binding free energy of compound 4 was calculated using the MM/PB(GB)SA method and totaled -106.525 kcal/mol. Finally, physicochemical and pharmacokinetic profiles were predicted using the Absorption, Distribution, Metabolism, Excretion, and Toxicity model, which indicated the good bioavailability of compound 4. These results provide the basis for further in vivo and in vitro studies to demonstrate that compound 4 is a promising drug candidate against M2-V27A/S31N.Communicated by Ramaswamy H. Sarma.

Palladium Nanoparticles Grafted onto Phytochemical Functionalized Biochar: A Sustainable Nanozyme for Colorimetric Sensing of Glucose and Glutathione

The devising and development of numerous enzyme mimics, particularly nanoparticles and nanomaterials (nanozymes), have been sparked by the inherent limitations imposed by natural enzymes. Peroxidase is one of the enzymes that is extensively utilized in commercial, medical, and biological applications because of its outstanding substrate selectivity. Herein, we present palladium nanoparticles grafted on Artocarpus heterophyllus (jackfruit) seed-derived biochar (BC-AHE@Pd) as a novel nanozyme to imitate peroxidase activity en route to the rapid and colorimetric detection of H2O2, exploiting o-phenylenediamine as a peroxidase substrate. The biogenically generated BC-AHE@Pd nanocatalyst was synthesized utilizing Artocarpus heterophyllus seed extract as the reducing agent for nanoparticle formation, while the residue became the source for biochar. Various analytical techniques like FT-IR, GC-MS, FE-SEM, EDS, TEM, SAED pattern, p-XRD, and ICP-OES, were used to characterize the BC-AHE@Pd nanocatalyst. The intrinsic peroxidase-like activity of the BC-AHE@Pd nanocatalyst was extended as a prospective nanosensor for the estimation of the biomolecules glucose and glutathione. Moreover, the BC-AHE@Pd nanocatalyst showed recyclability up to three recycles without any significant loss in activity.

The metal dependence of single-metal mediated phosphodiester bond cleavage: a QM/MM study of a multifaceted human enzyme

Nucleases catalyze the cleavage of phosphodiester bonds in nucleic acids using a range of metal cofactors. Although it is well accepted that many nucleases rely on two metal ions, the one-metal mediated pathway is debated. Furthermore, one-metal mediated nucleases maintain activity in the presence of many different metals, but the underlying reasons for this broad metal specificity are unknown. The human apurinic/apyrimidinic endonuclease (APE1), which plays a key role in DNA repair, transcription regulation, and gene expression, is a prototypical example of a one-metal dependent nuclease. Although Mg²⁺ is the native metal cofactor, APE1 remains catalytically active in the presence of several metals, with the rate decreasing as Mg²⁺ > Mn²⁺ > Ni²⁺ > Zn²⁺, while Ca²⁺ completely abolished the activity. The present work uses quantum mechanics-molecular mechanics techniques to map APE1-facilitated phosphodiester bond hydrolysis in the presence of these metals. The structural differences in stationary points along the reaction pathway shed light on the interplay between several factors that allow APE1 to remain catalytically active for various metals, with the trend in the barrier heights correlating with the experimentally reported APE1 catalytic activity. In contrast, Ca²⁺ significantly changes the metal coordination and active site geometry, and thus completely inhibits catalysis. Our work thereby provides support for the controversial single-metal mediated phosphodiester bond cleavage and clarifies uncertainties regarding the role of the metal and metal identity in this important reaction. This information is key for future medicinal and biotechnological applications including disease diagnosis and treatment, and protein engineering.

When Virtual Screening Yields Inactive Drugs: Dealing with False Theoretical Friends

The search of antivirals against SARS-CoV-2 in available libraries of compounds was initiated as soon as WHO announced that the coronavirus outbreak became a pandemic. That pivotal task has been conducted by both experimental groups in wet-labs as well as by theoretical chemists in supercomputing centers. The combination of biochemical and clinical intuitions yields first to remdesivir, a broad-spectrum antiviral that remains as the standard solution for the treatment of severe cases, while paxlovid, molnupiravir and fluvoxamine have been recently proposed as oral alternatives. Unfortunately, the intensive publication of standard virtual screening (VS) simulations might be not the best strategy to increase that short list of antivirals. This contribution joins theory and biological assays to rescore massive VS. Our goal is to critically assess pros and cons of using molecular models for drug repurposing.

Strategies for the application of metal-organic frameworks in catalytic reactions

Efficient catalysts play crucial roles in various organic reactions and polymerization. Metal–organic frameworks (MOFs) have the merits of ultrahigh porosity, large surface area, dispersed polymetallic sites and modifiable linkers, which make them promising candidates for catalyzation. This review primarily summarizes the recent research progress on diverse strategies for tailoring MOFs that are endowed with excellent catalytic behavior. These strategies include utilizing MOFs as nanosized reaction channels, metal nodes decorated as catalytic active sites and the modification of ligands or linkers. All these make them highly attractive to various applications, especially in catalyzing organic reactions or polymerizations and they have proven to be effective catalysts for a wide variety of reactions. MOFs are still an evolving field with tremendous prospects; therefore, through the research and development of more modification and regulation strategies, MOFs will realize their wider practical application in the future.

Metal–organic frameworks (MOFs) are promising candidates for catalyzation. This review primarily summarized the recent research progress in diverse strategies for tailoring MOFs which are endowed with more excellent catalytic behavior.

DEPACT and PACMatch: A Workflow of Designing De Novo Protein Pockets to Bind Small Molecules

Engineering of new functional proteins such as enzymes and biosensors involves the design of new protein pockets for the specific binding of small molecules. Here, we report a workflow composed of two new computational methods to execute this task. The DEPACT (Design Pocket as a Cluster based on Templates) method is a data-driven approach to design and evaluate small-molecule-binding pockets as isolated clusters, while the PACMatch method is a computational approach to match pocket residues in a cluster model to positions on given protein scaffolds. Using DEPACT and its scoring function, pocket clusters of natural-pocket-like chemical compositions and protein-ligand interaction strength can be designed. DEPACT can design pocket clusters containing water- or metal-ion-mediated protein-ligand interactions. While being able to efficiently treat relatively large pocket cluster models (e.g., of around 10 pocket residues), PACMatch outperforms previous methods in test cases of recovering the native positions of pocket residues in natural enzyme-substrate complexes.

Successes and challenges in multiscale modelling of artificial metalloenzymes: the case study of POP-Rh2 cyclopropanase

Molecular modelling applications in metalloenzyme design are still scarce due to a series of challenges. On top of that, the simulations of metal-mediated binding and the identification of catalytic competent geometries require both large conformational exploration and simulation of fine electronic properties. Here, we demonstrate how the incorporation of new tools in multiscale strategies, namely substrate diffusion exploration, allows taking a step further. As a showcase, the enantioselective profiles of the most outstanding variants of an artificial Rh₂-based cyclopropanase (GSH, HFF and RFY) developed by Lewis and co-workers (Nat. Commun., 2015, 6, 7789 and Nat. Chem., 2018, 10, 318-324) have been rationalized. DFT calculations on the free-cofactor-mediated process identify the carbene insertion and the cyclopropanoid formation as crucial events, the latter being the enantiodetermining step, which displays up to 8 competitive orientations easily altered by the protein environment. The key intermediates of the reaction were docked into the protein scaffold showing that some mutated residues have direct interaction with the cofactor and/or the co-substrate. These interactions take the form of a direct coordination of Rh in GSH and HFF and a strong hydrophobic patch with the carbene moiety in RFY. Posterior molecular dynamics sustain that the cofactor induces global re-arrangements of the protein. Finally, massive exploration of substrate diffusion, based on the GPathFinder approach, defines this event as the origin of the enantioselectivity in GSH and RFY. For HFF, fine molecular dockings suggest that it is likely related to local interactions upon diffusion. This work shows how modelling of long-range mutations on the catalytic profiles of metalloenzymes may be unavoidable and software simulating substrate diffusion should be applied.

Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis

Autonomous computations that rely on automated reaction network elucidation algorithms may pave the way to make computational catalysis on a par with experimental research in the field. Several advantages of this approach are key to catalysis: (i) automation allows one to consider orders of magnitude more structures in a systematic and open-ended fashion than what would be accessible by manual inspection. Eventually, full resolution in terms of structural varieties and conformations as well as with respect to the type and number of potentially important elementary reaction steps (including decomposition reactions that determine turnover numbers) may be achieved. (ii) Fast electronic structure methods with uncertainty quantification warrant high efficiency and reliability in order to not only deliver results quickly, but also to allow for predictive work. (iii) A high degree of autonomy reduces the amount of manual human work, processing errors, and human bias. Although being inherently unbiased, it is still steerable with respect to specific regions of an emerging network and with respect to the addition of new reactant species. This allows for a high fidelity of the formalization of some catalytic process and for surprising in silico discoveries. In this work, we first review the state of the art in computational catalysis to embed autonomous explorations into the general field from which it draws its ingredients. We then elaborate on the specific conceptual issues that arise in the context of autonomous computational procedures, some of which we discuss at an example catalytic system.

Rationalizing the Unprecedented Stereochemistry of an Enzymatic Nitrile Synthesis through a Combined Computational and Experimental Approach

In this contribution, the unique and unprecedented stereochemical phenomenon of an aldoxime dehydratase‐catalyzed enantioselective dehydration of racemic E‐ and Z‐aldoximes with selective formation of both enantiomeric forms of a chiral nitrile is rationalized by means of molecular modelling, comprising in silico mutations and docking studies. This theoretical investigation gave detailed insight into why with the same enzyme the use of racemic E‐ and Z‐aldoximes leads to opposite forms of the chiral nitrile. The calculated mutants with a larger or smaller cavity in the active site were then prepared and used in biotransformations, showing the theoretically predicted decrease and increase of the enantioselectivities in these nitrile syntheses. This validated model also enabled the rational design of mutants with a smaller cavity, which gave superior enantioselectivities compared to the known wild‐type enzyme, with excellent E‐values of up to E>200 when the mutant OxdRE‐Leu145Phe was utilized.

Artificial imine reductases: developments and future directions

Biocatalytic imine reduction has been a topic of intense research by the artificial metalloenzyme community in recent years. Artificial constructs, together with natural enzymes, have been engineered to produce chiral amines with high enantioselectivity. This review examines the design of the main classes of artificial imine reductases reported thus far and summarises approaches to enhancing their catalytic performance using complementary methods. Examples of utilising these biocatalysts in vivo or in multi-enzyme cascades have demonstrated the potential that artIREDs can offer, however, at this time their use in biocatalysis remains limited. This review explores the current scope of artIREDs and the strategies used for catalyst improvement, and examines the potential for artIREDs in the future.

Xanthine oxidoreductase inhibition – A review of computational aspect

Xanthine Oxidoreductase (XOR) exists in a variety of organisms from bacteria to humans and catalyzes the oxidation of hypoxanthine to xanthine and from xanthine to uric acid. Excessive uric acid could lead to gout and hyperuricemia. In this paper, we have reviewed the recent computational studies on xanthine oxidase inhibition. Computational methods, such as molecular dynamics (molecular mechanics), quantum mechanics, and quantum mechanics/molecular mechanics (QM/MM), have been employed to investigate the binding affinity of xanthine oxidase with synthesized and isolated nature inhibitors. The limitations of different computational methods for xanthine oxidase inhibition studies were also discussed. Implications of the computational approach could be used to help to understand the existing arguments on substrate/product orientation in xanthine oxidase inhibition, which allows designing new inhibitors with higher efficacy.

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.

Molecular Dynamics Simulation and Kinetic Study of Fluoride Binding to V21C/V66C Myoglobin with a Cytoglobin-like Disulfide Bond

Protein design is able to create artificial proteins with advanced functions, and computer simulation plays a key role in guiding the rational design. In the absence of structural evidence for cytoglobin (Cgb) with an intramolecular disulfide bond, we recently designed a de novo disulfide bond in myoglobin (Mb) based on structural alignment (i.e., V21C/V66C Mb double mutant). To provide deep insight into the regulation role of the Cys21-Cys66 disulfide bond, we herein perform molecular dynamics (MD) simulation of the fluoride–protein complex by using a fluoride ion as a probe, which reveals detailed interactions of the fluoride ion in the heme distal pocket, involving both the distal His64 and water molecules. Moreover, we determined the kinetic parameters of fluoride binding to the double mutant. The results agree with the MD simulation and show that the formation of the Cys21-Cys66 disulfide bond facilitates both fluoride binding to and dissociating from the heme iron. Therefore, the combination of theoretical and experimental studies provides valuable information for understanding the structure and function of heme proteins, as regulated by a disulfide bond. This study is thus able to guide the rational design of artificial proteins with tunable functions in the future.

Broadening the Scope of Biocatalysis in Sustainable Organic Synthesis

This Review is aimed at synthetic organic chemists who may be familiar with organometallic catalysis but have no experience with biocatalysis, and seeks to provide an answer to the perennial question: if it is so attractive, why wasn't it extensively used in the past? The development of biocatalysis in industrial organic synthesis is traced from the middle of the last century. Advances in molecular biology in the last two decades, in particular genome sequencing, gene synthesis and directed evolution of proteins, have enabled remarkable improvements in scope and substantially reduced biocatalyst development times and cost contributions. Additionally, improvements in biocatalyst recovery and reuse have been facilitated by developments in enzyme immobilization technologies. Biocatalysis has become eminently competitive with chemocatalysis and the biocatalytic production of important pharmaceutical intermediates, such as enantiopure alcohols and amines, has become mainstream organic synthesis. The synthetic space of biocatalysis has significantly expanded and is currently being extended even further to include new-to-nature biocatalytic reactions.

Systematic Studies on the Protocol and Criteria for Selecting a Covalent Docking Tool

With the resurgence of drugs with covalent binding mechanisms, much attention has been paid to docking methods for the discovery of targeted covalent inhibitors. The existence of many available covalent docking tools has inspired development of a systematic and objective procedure and criteria with which to evaluate these programs. In order to find a tool appropriate to studies of a covalently binding system, protocols and criteria are proposed for protein–ligand covalent docking studies. This paper consists of three sections: (1) curating a standard data set to evaluate covalent docking tools objectively; (2) establishing criteria to measure the performance of a tool applied for docking ligands into a complex system; and (3) creating a protocol to evaluate and select covalent binding tools. The protocols were applied to evaluate four covalent docking tools (MOE, GOLD, CovDock, and ICM-Pro) and parameters affecting covalent docking performance were investigated.

Advances in Sustainable Catalysis: A Computational Perspective

The enormous challenge of moving our societies to a more sustainable future offers several exciting opportunities for computational chemists. The first principles approach to "catalysis by design" will enable new and much greener chemical routes to produce vital fuels and fine chemicals. This prospective outlines a wide variety of case studies to underscore how the use of theoretical techniques, from QM/MM to unrestricted DFT and periodic boundary conditions, can be applied to biocatalysis and to both homogeneous and heterogenous catalysts of all sizes and morphologies to provide invaluable insights into the reaction mechanisms they catalyze.

The Effect of Cofactor Binding on the Conformational Plasticity of the Biological Receptors in Artificial Metalloenzymes: The Case Study of LmrR

The design of Artificial Metalloenzymes (ArMs), which result from the incorporation of organometallic cofactors into biological structures, has grown steadily in the last two decades and important new-to-Nature reactions have been reached. These type of exercises could greatly benefit from an understanding of the structural impact that the inclusion of organometallic moieties may have on the biological host. To date though, our understanding of this phenomenon is highly partial. This lack of knowledge is one of the elements that condition that first-generation ArMs generally display relatively poor catalytic profiles. In this work, we approach this matter by assessing the dynamics and stability of a series of ArMs resulting from the inclusion, via different anchoring strategies, of a variety of organometallic cofactors into the Lactococcal multidrug resistance regulator (LmrR) protein. To this aim, we coupled standard force field-based techniques such as Protein-Ligand Docking and Molecular Dynamics simulations with a variety of trajectory convergence analyses, capable of assessing both the stability and flexibility of the different systems under study upon the binding of cofactors. Together with the experimental evidence obtained in other studies, we provide an overview on how these changes can affect the catalytic outcomes obtained from the different ArMs. Fundamentally, our results show that the convergence analysis used in this work can assess how the inclusion of synthetic metallic cofactors in proteins can condition different structural modulations of their host. Those conformational modifications are key to the success of the desired catalytic activity and their proper identification can be wisely used to improve the quality and the rate of success of the ArMs.

Metallopolymers for advanced sustainable applications

Since the development of metallopolymers, there has been tremendous interest in the applications of this type of materials. The interest in these materials stems from their potential use in industry as catalysts, biomedical agents in healthcare, energy storage and production as well as climate change mitigation. The past two decades have clearly shown exponential growth in the development of many new classes of metallopolymers that address these issues. Today, metallopolymers are considered to be at the forefront for discovering new and sustainable heterogeneous catalysts, therapeutics for drug-resistant diseases, energy storage and photovoltaics, molecular barometers and thermometers, as well as carbon dioxide sequesters. The focus of this review is to highlight the advances in design of metallopolymers with specific sustainable applications.

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.

Validation and Applications of Protein-Ligand Docking Approaches Improved for Metalloligands with Multiple Vacant Sites

Decoding the interaction between coordination compounds and proteins is of fundamental importance in biology, pharmacy, and medicine. In this context, protein- ligand docking represents a particularly interesting asset to predict how small compounds could interact with biomolecules, but to date, very little information is available to adapt these methodologies to metal-containing ligands. Here, we assessed the predictive capability of a metal-compatible parameter set for the docking program GOLD for metallo ligands with multiple vacant sites and different geometries. The study first presents a benchmark of 25 well-characterized X-ray metallo ligand-protein adducts. In 100% of the cases, the docking solutions are superimposable to the X-ray determination, and in 92% the value of the root-mean-square deviation between the experimental and calculated structures is lower than 1.5 Å. After the validation step, we applied these methods to five case studies for the prediction of the binding of pharmacological active metal species to proteins: (i) the anticancer copper(II) complex [Cu^II(Br)(2-hydroxy-1-naphthaldehyde benzoyl hydrazine)(indazole)] to human serum albumin (HSA); (ii) one of the active species of antidiabetic and antitumor vanadium compounds, V^IVO²⁺ ion, to carboxypeptidase; (iii) the antiarthritic species [Au^I(PEt₃)]⁺ to HSA; (iv) the antitumor oxaliplatin to ubiquitin; (v) the antitumor ruthenium(II) compound RAPTA-PentaOH to cathepsin B. The calculations suggested that the binding modes are in good agreement with the partial information retrieved from spectroscopic and spectrometric analysis and allowed us, in certain cases, to propose additional hypotheses. This method is an important update in protein-metallo ligand docking, which could have a wide field of application, from biology and inorganic biochemistry to medicinal chemistry and pharmacology.

Strategies for designing non-natural enzymes and binders

The design of tailor-made enzymes is a major goal in biochemical research that can result in wide-range applications and will lead to a better understanding of how proteins fold and function. In this review we highlight recent advances in enzyme and small molecule binder design. A focus is placed on novel strategies for the design of scaffolds, developments in computational methods, and recent applications of these techniques on receptors, sensors, and enzymes. Further, the integration of computational and experimental methodologies is discussed. The outlined examples of designed enzymes and binders for various purposes highlight the importance of this topic and underline the need for tailor-made proteins.

The limits to biocatalysis: pushing the envelope

In the period 1985 to 1995 applications of biocatalysis, driven by the need for more sustainable manufacture of chemicals and catalytic, (enantio)selective methods for the synthesis of pharmaceutical intermediates, largely involved the available hydrolases. This was followed, in the next two decades, by revolutionary developments in protein engineering and directed evolution for the optimisation of enzyme function and performance that totally changed the biocatalysis landscape. In the same period, metabolic engineering and synthetic biology revolutionised the use of whole cell biocatalysis in the synthesis of commodity chemicals by fermentation. In particular, developments in the enzymatic enantioselective synthesis of chiral alcohols and amines are highlighted. Progress in enzyme immobilisation facilitated applications under harsh industrial conditions, such as in organic solvents. The emergence of biocatalytic or chemoenzymatic cascade processes, often with co-immobilised enzymes, has enabled telescoping of multi-step processes. Discovering and inventing new biocatalytic processes, based on (meta)genomic sequencing, evolving enzyme promiscuity, chemomimetic biocatalysis, artificial metalloenzymes, and the introduction of non-canonical amino acids into proteins, are pushing back the limits of biocatalysis function. Finally, the integral role of biocatalysis in developing a biobased carbon-neutral economy is discussed.

Prediction of the interaction of metallic moieties with proteins: An update for protein-ligand docking techniques

In this article, we present a new approach to expand the range of application of protein-ligand docking methods in the prediction of the interaction of coordination complexes (i.e., metallodrugs, natural and artificial cofactors, etc.) with proteins. To do so, we assume that, from a pure computational point of view, hydrogen bond functions could be an adequate model for the coordination bonds as both share directionality and polarity aspects. In this model, docking of metalloligands can be performed without using any geometrical constraints or energy restraints. The hard work consists in generating the convenient atom types and scoring functions. To test this approach, we applied our model to 39 high-quality X-ray structures with transition and main group metal complexes bound via a unique coordination bond to a protein. This concept was implemented in the protein-ligand docking program GOLD. The results are in very good agreement with the experimental structures: the percentage for which the RMSD of the simulated pose is smaller than the X-ray spectra resolution is 92.3% and the mean value of RMSD is < 1.0 Å. Such results also show the viability of the method to predict metal complexes-proteins interactions when the X-ray structure is not available. This work could be the first step for novel applicability of docking techniques in medicinal and bioinorganic chemistry and appears generalizable enough to be implemented in most protein-ligand docking programs nowadays available. © 2017 Wiley Periodicals, Inc.

Design of an enantioselective artificial metallo-hydratase enzyme containing an unnatural metal-binding amino acid

The design of artificial metalloenzymes is a challenging, yet ultimately highly rewarding objective because of the potential for accessing new-to-nature reactions. One of the main challenges is identifying catalytically active substrate-metal cofactor-host geometries. The advent of expanded genetic code methods for the in vivo incorporation of non-canonical metal-binding amino acids into proteins allow to address an important aspect of this challenge: the creation of a stable, well-defined metal-binding site. Here, we report a designed artificial metallohydratase, based on the transcriptional repressor lactococcal multidrug resistance regulator (LmrR), in which the non-canonical amino acid (2,2'-bipyridin-5yl)alanine is used to bind the catalytic Cu(ii) ion. Starting from a set of empirical pre-conditions, a combination of cluster model calculations (QM), protein-ligand docking and molecular dynamics simulations was used to propose metallohydratase variants, that were experimentally verified. The agreement observed between the computationally predicted and experimentally observed catalysis results demonstrates the power of the artificial metalloenzyme design approach presented here.

Artificial Metalloenzymes: Reaction Scope and Optimization Strategies

The incorporation of a synthetic, catalytically competent metallocofactor into a protein scaffold to generate an artificial metalloenzyme (ArM) has been explored since the late 1970's. Progress in the ensuing years was limited by the tools available for both organometallic synthesis and protein engineering. Advances in both of these areas, combined with increased appreciation of the potential benefits of combining attractive features of both homogeneous catalysis and enzymatic catalysis, led to a resurgence of interest in ArMs starting in the early 2000's. Perhaps the most intriguing of potential ArM properties is their ability to endow homogeneous catalysts with a genetic memory. Indeed, incorporating a homogeneous catalyst into a genetically encoded scaffold offers the opportunity to improve ArM performance by directed evolution. This capability could, in turn, lead to improvements in ArM efficiency similar to those obtained for natural enzymes, providing systems suitable for practical applications and greater insight into the role of second coordination sphere interactions in organometallic catalysis. Since its renaissance in the early 2000's, different aspects of artificial metalloenzymes have been extensively reviewed and highlighted. Our intent is to provide a comprehensive overview of all work in the field up to December 2016, organized according to reaction class. Because of the wide range of non-natural reactions catalyzed by ArMs, this was done using a functional-group transformation classification. The review begins with a summary of the proteins and the anchoring strategies used to date for the creation of ArMs, followed by a historical perspective. Then follows a summary of the reactions catalyzed by ArMs and a concluding critical outlook. This analysis allows for comparison of similar reactions catalyzed by ArMs constructed using different metallocofactor anchoring strategies, cofactors, protein scaffolds, and mutagenesis strategies. These data will be used to construct a searchable Web site on ArMs that will be updated regularly by the authors.

Selective C-H bond functionalization using repurposed or artificial metalloenzymes

Catalytic CH bond functionalization has become an important tool for organic synthesis. Metalloenzymes offer a solution to one of the foremost challenges in this field, site-selective CH functionalization, but they are only capable of catalyzing a subset of the CH functionalization reactions known to small molecule catalysts. To overcome this limitation, metalloenzymes have been repurposed by exploiting the reactivity of their native cofactors toward substrates not found in nature. Additionally, new reactivity has been accessed by incorporating synthetic metal cofactors into protein scaffolds to form artificial metalloenzymes. The selectivity and activity of these catalysts has been tuned using directed evolution. This review covers the recent progress in developing and optimizing both repurposed and artificial metalloenzymes as catalysts for selective CH bond functionalization.

Mechanistic investigation of trimethylamine-N-oxide reduction catalysed by biomimetic molybdenum enzyme models

In this paper, we report a theoretical investigation of the reduction reaction mechanism of Me3NO using molybdenum containing systems that are functional and structural analogues of trimethylamine N-oxide reductase mononuclear molybdenum enzyme. The reactivity of the monooxomolybdenum(IV) benzenedithiolato complex and its derivatives to carbamoyl (t-BuNHCO) and acylamino (t-BuCONH) substituents on the benzene rings in both cis and trans arrangements was explored. The calculated energy profiles describing the steps of two mechanisms of attack considered viable (named cis- and trans-attack) by the Me3NO substrate at cis and trans positions with respect to the oxo ligand show that the attack on cis is energetically more favourable than the attack on trans. Along the pathway for the cis-attack the first step of the reaction, that is rate-determining for all the studied compounds, is the approach of the substrate to the Mo centre in cis to the oxo ligand that causes a distortion of the initial square-pyramidal geometry of the complex. The reaction steps involved in the trans position attack were also explored. Calculations confirm that, as previously suggested, the introduction of ligands able to form intramolecular NH···S hydrogen bonds accelerates the reduction of the Me3NO substrate and contributes to the tuning of the reactivity of molybdoenzyme models.

Grand challenges for catalysis in the Science and Technology Roadmap on Catalysis for Europe: moving ahead for a sustainable future

This perspective discusses the general concepts that will guide future catalysis and related grand challenges based on the Science and Technology Roadmap on Catalysis for Europe prepared by the European Cluster on Catalysis.

Computational design of ligand-binding proteins

Custom-designed ligand-binding proteins with novel functions hold the potential for numerous applications. In recent years, the developments of computational methods together with high-throughput experimental screening techniques have led to the generation of novel, high-affinity ligand-binding proteins for given ligands. In addition, naturally occurring ligand-binding proteins have been computationally designed to recognize new ligands while keeping their original biological functions at the same time. Furthermore, metalloproteins have been successfully designed for novel functions and applications. Though much has been learned in these successful design cases, advances in our understanding of protein dynamics and functions related to ligand binding and development of novel computational strategies are necessary to further increase the success rate of computational protein-ligand binding design.