Machine Learning-Enhanced Quantum Chemistry-Assisted Refinement of the Active Site Structure of Metalloproteins.

Understanding the fine structural details of inhibitor binding at the active site of metalloenzymes can have a profound impact on the rational drug design targeted to this broad class of biomolecules. Structural techniques such as NMR, cryo-EM, and X-ray crystallography can provide bond lengths and angles, but the uncertainties in these measurements can be as large as the range of values that have been observed for these quantities in all the published structures. This uncertainty is far too large to allow for reliable calculations at the quantum chemical (QC) levels for developing precise structure-activity relationships or for improving the energetic considerations in protein-inhibitor studies. Therefore, the need arises to rely upon computational methods to refine the active site structures well beyond the resolution obtained with routine application of structural methods. In a recent paper, we have shown that it is possible to refine the active site of cobalt(II)-substituted MMP12, a metalloprotein that is a relevant drug target, by matching to the experimental pseudocontact shifts (PCS) those calculated using multireference ab initio QC methods. The computational cost of this methodology becomes a significant bottleneck when the starting structure is not sufficiently close to the final one, which is often the case with biomolecular structures. To tackle this problem, we have developed an approach based on a neural network (NN) and a support vector regression (SVR) and applied it to the refinement of the active site structure of oxalate-inhibited human carbonic anhydrase 2 (hCAII), another prototypical metalloprotein target. The refined structure gives a remarkably good agreement between the QC-calculated and the experimental PCS. This study not only contributes to the knowledge of CAII but also demonstrates the utility of combining machine learning (ML) algorithms with QC calculations, offering a promising avenue for investigating other drug targets and complex biological systems in general.

Functional metalloenzymes based on myoglobin and neuroglobin that exploit covalent interactions.

Globins, such as myoglobin (Mb) and neuroglobin (Ngb), are ideal protein scaffolds for the design of functional metalloenzymes. To date, numerous approaches have been developed for enzyme design. This review presents a summary of the progress made in the design of functional metalloenzymes based on Mb and Ngb, with a focus on the exploitation of covalent interactions, including coordination bonds and covalent modifications. These include the construction of a metal-binding site, the incorporation of a non-native metal cofactor, the formation of Cys/Tyr-heme covalent links, and the design of disulfide bonds, as well as other Cys-covalent modifications. As exemplified by recent studies from our group and others, the designed metalloenzymes have potential applications in biocatalysis and bioconversions. Furthermore, we discuss the current trends in the design of functional metalloenzymes and highlight the importance of covalent interactions in the design of functional metalloenzymes.

Computational modelling of supramolecular metallopeptide assemblies.

Among the important questions in supramolecular peptide self-assemblies are their interactions with metallic compounds and ions. In the last decade, intensive efforts have been devoted to understanding the structural properties of these interactions including their dynamical and catalytic impact in natural and de novo systems. Since structural insights from experimental approaches could be particularly challenging, computational chemistry methods are interesting complementary tools. Here, we present the general multiscale strategies we developed and applied for the study of metallopeptide assemblies. These strategies include prediction of metal binding site, docking of metallic moieties, classical and accelerated molecular dynamics and finally QM/MM calculations. The systems of choice for this chapter are, on one side, peptides involved in neurodegenerative diseases and, on the other, de novo fibrillar systems with catalytic properties. Both successes and remaining challenges are highlighted so that the protocol could be apply to other system of this kind.

Redox-reversible siderophore-based catalyst anchoring within cross-linked artificial metalloenzyme aggregates enables enantioselectivity switching.

The immobilisation of artificial metalloenzymes (ArMs) holds promise for the implementation of new biocatalytic reactions. We present the synthesis of cross-linked artificial metalloenzyme aggregates (CLArMAs) with excellent recyclability, as an alternative to carrier-based immobilisation strategies. Furthermore, iron-siderophore supramolecular anchoring facilitates redox-triggered cofactor release, enabling CLArMAs to be recharged with alternative cofactors for diverse selectivity.

A database overview of metal-coordination distances in metalloproteins.

Metalloproteins are ubiquitous in all living organisms and take part in a very wide range of biological processes. For this reason, their experimental characterization is crucial to obtain improved knowledge of their structure and biological functions. The three-dimensional structure represents highly relevant information since it provides insight into the interaction between the metal ion(s) and the protein fold. Such interactions determine the chemical reactivity of the bound metal. The available PDB structures can contain errors due to experimental factors such as poor resolution and radiation damage. A lack of use of distance restraints during the refinement and validation process also impacts the structure quality. Here, the aim was to obtain a thorough overview of the distribution of the distances between metal ions and their donor atoms through the statistical analysis of a data set based on more than 115 000 metal-binding sites in proteins. This analysis not only produced reference data that can be used by experimentalists to support the structure-determination process, for example as refinement restraints, but also resulted in an improved insight into how protein coordination occurs for different metals and the nature of their binding interactions. In particular, the features of carboxylate coordination were inspected, which is the only type of interaction that is commonly present for nearly all metals.

Flexibility of Binding Site is Essential to the Ca2+ Selectivity in EF-Hand Calcium-Binding Proteins.

High binding affinity and selectivity of metal ions are essential to the function of metalloproteins. Thus, understanding the factors that determine these binding characteristics is of major interest for both fundamental mechanistic investigations and guiding of the design of novel metalloproteins. In this work, we perform QM cluster model calculations and quantum mechanics/molecular mechanics (QM/MM) free energy simulations to understand the binding selectivity of Ca2+ and Mg2+ in the wild-type carp parvalbumin and its mutant. While a nonpolarizable MM model (CHARMM36) does not lead to the correct experimental trend, treatment of the metal binding site with the DFTB3 model in a QM/MM framework leads to relative binding free energies (ΔΔGbind) comparable with experimental data. For the wild-type (WT) protein, the calculated ΔΔGbind is ∼6.6 kcal/mol in comparison with the experimental value of 5.6 kcal/mol. The good agreement highlights the value of a QM description of the metal binding site and supports the role of electronic polarization and charge transfer to metal binding selectivity. For the D51A/E101D/F102W mutant, different binding site models lead to considerable variations in computed binding affinities. With a coordination number of seven for Ca2+, which is shown by QM/MM metadynamics simulations to be the dominant coordination number for the mutant, the calculated relative binding affinity is ∼4.8 kcal/mol, in fair agreement with the experimental value of 1.6 kcal/mol. The WT protein is observed to feature a flexible binding site that accommodates a range of coordination numbers for Ca2+, which is essential to the high binding selectivity for Ca2+ over Mg2+. In the mutant, the E101D mutation reduces the flexibility of the binding site and limits the dominant coordination number of Ca2+ to be seven, thereby leading to reduced binding selectivity against Mg2+. Our results highlight that the binding selectivity of metal ions depends on both the structural and dynamical properties of the protein binding site.

Discovery of Novel Metalloenzyme Inhibitors Based on Property Characterization: Strategy and Application for HDAC1 Inhibitors.

Metalloenzymes are ubiquitously present in the human body and are relevant to a variety of diseases. However, the development of metalloenzyme inhibitors is limited by low specificity and poor drug-likeness associated with metal-binding fragments (MBFs). A generalized drug discovery strategy was established, which is characterized by the property characterization of zinc-dependent metalloenzyme inhibitors (ZnMIs). Fifteen potential Zn2+-binding fragments (ZnBFs) were identified, and a customized pharmacophore feature was defined based on these ZnBFs. The customized feature was set as a required feature and applied to a search for novel inhibitors for histone deacetylase 1 (HDAC1). Ten potential HDAC1 inhibitors were recognized, and one of them (compound 9) was a known potent HDAC1 inhibitor. The results demonstrated the effectiveness of our strategy to identify novel inhibitors for zinc-dependent metalloenzymes.

Electron-Transferring Metalloenzymes and their Potential Biotechnological Applications.

Modern societies rely heavily on centralized industrial processes to generate a multitude of products ranging from electrical energy to synthetic chemical building blocks to construction materials. To date, these processes have relied extensively on energy produced from fossil fuels, which has led to dramatically increased quantities of greenhouse gases (including carbon dioxide) being released into the atmosphere; the effects of the ensuing change to our climate are easily observed in day-to-day life. Some of the reactions catalyzed by these industrial processes can be catalyzed in nature by metal-containing enzymes (metalloenzymes) that have evolved over the course of up to 3.8 billion years to do so under mild physiological conditions using Earth-abundant metals. While such metalloenzymes could in principle facilitate the implementation of carbon-neutral processes around the globe, either in "bio-inspired" catalyst design or even by direct exploitation, many remaining questions surrounding their mechanisms often preclude both options. Here, our recent efforts in understanding and applying metalloenzymes that catalyze reactions such as dinitrogen reduction to ammonia or proton reduction to molecular hydrogen are discussed. In closing, an opinion on the question: "Can these types of enzymes really be used in new biotechnologies?" is offered.

Unlocking Precision Docking for Metalloproteins.

Metalloproteins play a fundamental role in molecular biology, contributing to various biological processes. However, the discovery of high-affinity ligands targeting metalloproteins has been delayed due, in part, to a lack of suitable tools and data. Molecular docking, a widely used technique for virtual screening of small-molecule ligand interactions with proteins, often faces challenges when applied to metalloproteins due to the particular nature of the ligand metal bond. To address these limitations associated with docking metalloproteins, we introduce a knowledge-driven docking approach known as "metalloprotein bias docking" (MBD), which extends the AutoDock Bias technique. We assembled a comprehensive data set of metalloprotein-ligand complexes from 15 different metalloprotein families, encompassing Ca, Co, Fe, Mg, Mn, and Zn metal ions. Subsequently, we conducted a performance analysis of our MBD method and compared it to the conventional docking (CD) program AutoDock4, applied to various metalloprotein targets within our data set. Our results demonstrate that MBD outperforms CD, significantly enhancing accuracy, selectivity, and precision in ligand pose prediction. Additionally, we observed a positive correlation between our predicted ligand free energies and the corresponding experimental values. These findings underscore the potential of MBD as a valuable tool for the effective exploration of metalloprotein-ligand interactions.

Structural, Biochemical, and Computational Characterization of Sulfamides as Bimetallic Peptidase Inhibitors.

The sulfonamide function is used extensively as a general building block in various inhibitory scaffolds and, more specifically, as a zinc-binding group (ZBG) of metalloenzyme inhibitors. Here, we provide biochemical, structural, and computational characterization of a metallopeptidase in complex with inhibitors, where the mono- and bisubstituted sulfamide functions are designed to directly engage zinc ions of a bimetallic enzyme site. Structural data showed that while monosubstituted sulfamides coordinate active-site zinc ions via the free negatively charged amino group in a canonical manner, their bisubstituted counterparts adopt an atypical binding pattern divergent from expected positioning of corresponding tetrahedral reaction intermediates. Accompanying quantum mechanics calculations revealed that electroneutrality of the sulfamide function is a major factor contributing to the markedly lower potency of bisubstituted compounds by considerably lowering their interaction energy with the enzyme. Overall, while bisubstituted uncharged sulfamide functions can bolster favorable pharmacological properties of a given inhibitor, their use as ZBGs in metalloenzyme inhibitors might be less advantageous due to their suboptimal metal-ligand properties.

On the hunt for metalloenzyme inhibitors: Investigating the presence of metal-coordinating compounds in screening libraries and chemical spaces.

Metalloenzymes play vital roles in various biological processes, requiring the search for inhibitors to develop treatment options for diverse diseases. While compound library screening is a conventional approach, the exploration of virtual chemical spaces housing trillions of compounds has emerged as an alternative strategy. In this study, we investigated the suitability of selected screening libraries and chemical spaces for discovering inhibitors of metalloenzymes featuring common ions (Mg2+, Mn2+, and Zn2+). First, metal-coordinating groups from ligands interacting with ions in the Protein Data Bank were extracted. Subsequently, the prevalence of these groups in two focused screening libraries (Life Chemicals' chelator library, comprising 6,428 compounds, and Otava's chelator fragment library, with 1,784 fragments) as well as two chemical spaces (GalaXi and REAL space, containing billions of virtual products) was investigated. In total, 1,223 metal-coordinating groups were identified, with about a quarter of these groups found within the examined libraries and spaces. Our results indicate that these can serve as valuable starting points for drug discovery targeting metalloenzymes. In addition, this study suggests ways to improve libraries and spaces for better success in finding potential inhibitors for metalloenzymes.

Bridging the Coordination Chemistry of Small Compounds and Metalloproteins Using Machine Learning.

Metalloproteins require metal ions as cofactors to catalyze specific reactions with remarkable efficiency and specificity. In various electron transfer reactions, metals in the active sites change their oxidation states to facilitate the biochemical reactions. Cryogenic electron microscopy, X-ray, and X-ray free electron laser (XFEL) crystallography are used to image metalloproteins to understand the reaction mechanisms. However, radiation damage in cryoEM and X-ray crystallography, and the challenge of generating homogeneous crystals and keeping the appropriate experimental conditions for all the crystals in XFEL crystallography, may alter the oxidation states. Here, we build machine learning models trained on a large data set from the Cambridge Crystallographic Data Center to evaluate the metal oxidation states. The models yield high accuracy scores (from 82% to 94%) for all metals in the small molecules. Then, they were used to predict the oxidation states of more than 30 000 metal clusters in metalloproteins with Fe, Mn, Co, and Cu in their active sites. We found that most of the metals exist in the lower oxidation states (Fe2+ 77%, Mn2+ 85%, Co2+ 65%, and Cu+ 64%), and these populations correlate with the standard reduction potentials of the metal ions. Furthermore, we found no clear correlation between these populations and the resolution of the structures, which suggests no significant dependence of these predictions on the resolution. Our models represent a valuable tool for evaluating the oxidation states of the metals in metalloproteins imaged with different techniques. The data files and the machine learning code are available in a public GitHub repository: https://github.com/mamin03/OxitationStatesMetalloprotein.git.

Protein3D: Enabling analysis and extraction of metal-containing sites from the Protein Data Bank with molSimplify.

Metalloenzymes catalyze a wide range of chemical transformations, with the active site residues playing a key role in modulating chemical reactivity and selectivity. Unlike smaller synthetic catalysts, a metalloenzyme active site is embedded in a larger protein, which makes interrogation of electronic properties and geometric features with quantum mechanical calculations challenging. Here we implement the ability to fetch crystallographic structures from the Protein Data Bank and analyze the metal binding sites in the program molSimplify. We show the usefulness of the newly created protein3D class to extract the local environment around non-heme iron enzymes containing a two histidine motif and prepare 372 structures for quantum mechanical calculations. Our implementation of protein3D serves to expand the range of systems molSimplify can be used to analyze and will enable high-throughput study of metal-containing active sites in proteins.

MESPEUS: a database of metal coordination groups in proteins.

MESPEUS is a freely accessible database which uses carefully selected metal coordination groups found in metalloprotein structures taken from the Protein Data Bank. The database contains geometrical information of metal sites within proteins, including 40 metal types. In order to completely determine the metal coordination, the symmetry-related units of a given protein structure are taken into account and are generated using the appropriate space group symmetry operations. This permits a more complete description of the metal coordination geometry by including all coordinating atoms. The user-friendly web interface allows users to directly search for a metal site of interest using several useful options, including searching for metal elements, metal-donor distances, coordination number, donor residue group, and structural resolution. These searches can be carried out singly or in combination. The details of a metal site and the metal site(s) in the whole structure can be graphically displayed using the interactive web interface. MESPEUS is automatically updated monthly by synchronizing with the PDB database. An investigation for the Mg-ATP interaction is given to demonstrate how MESPEUS can be used to extract information about metal sites by selecting structure and coordination features. MESPEUS is available at http://mespeus.nchu.edu.tw/.

Benzylic C(sp3 )-H Bond Oxidation with Ketone Selectivity by a Cobalt(IV)-Oxo Embedded in a ß-Barrel Protein.

Artificial metalloenzymes have emerged as biohybrid catalysts that allow to combine the reactivity of a metal catalyst with the flexibility of protein scaffolds. This work reports the artificial metalloenzymes based on the ß-barrel protein nitrobindin NB4, in which a cofactor [CoII X(Me3 TACD-Mal)]+ X- (X=Cl, Br; Me3 TACD=N,N' ,N''-trimethyl-1,4,7,10-tetraazacyclododecane, Mal=CH2 CH2 CH2 NC4 H2 O2 ) was covalently anchored via a Michael addition reaction. These biohybrid catalysts showed higher efficiency than the free cobalt complexes for the oxidation of benzylic C(sp3 )-H bonds in aqueous media. Using commercially available oxone (2KHSO5 ⋅ KHSO4 ⋅ K2 SO4 ) as oxidant, a total turnover number of up to 220 and 97 % ketone selectivity were achieved for tetralin. As catalytically active intermediate, a mononuclear terminal cobalt(IV)-oxo species [Co(IV)=O]2+ was generated by reacting the cobalt(II) cofactor with oxone in aqueous solution and characterized by ESI-TOF MS.

Atomic-level design of metalloenzyme-like active pockets in metal-organic frameworks for bioinspired catalysis.

Natural metalloenzymes with astonishing reaction activity and specificity underpin essential life transformations. Nevertheless, enzymes only operate under mild conditions to keep sophisticated structures active, limiting their potential applications. Artificial metalloenzymes that recapitulate the catalytic activity of enzymes can not only circumvent the enzymatic fragility but also bring versatile functions into practice. Among them, metal-organic frameworks (MOFs) featuring diverse and site-isolated metal sites and supramolecular structures have emerged as promising candidates for metalloenzymes to move toward unparalleled properties and behaviour of enzymes. In this review, we systematically summarize the significant advances in MOF-based metalloenzyme mimics with a special emphasis on active pocket engineering at the atomic level, including primary catalytic sites and secondary coordination spheres. Then, the deep understanding of catalytic mechanisms and their advanced applications are discussed. Finally, a perspective on this emerging frontier research is provided to advance bioinspired catalysis.

Chemistry meets biology in the coordination dynamics of metalloproteins.

Metal sites in proteins are often presented in an idealized way that does not capture the intrinsic dynamic behavior of the protein or the extrinsic factors that affect changes in the coordination of the metal ion in biological space and time. The bioinorganic chemistry possible in healthy and diseased living organisms is limited by prevailing pH values, redox potentials, and availability and concentrations of metal ions and ligands. Changes in any of these parameters and protein-protein or protein-ligand interactions can result in differences in the type of metal ion bound, metal occupancy, and coordination number or geometry. This article addresses the plasticity and complexity of metal coordination in proteins when these parameters are considered. It uses three examples of zinc sites with sulfur donor atoms from cysteines in mammalian proteins: alcohol dehydrogenases, metallothioneins, and zinc transporters of the ZnT (SLC30A) family. Coordination dynamics of the metal sites in these proteins has different purposes; in alcohol dehydrogenases for the metal ion to perform its different roles in the catalytic cycle, in metallothioneins for serving as a metal buffer, and in ZnT zinc transporters for sensing metal ions and moving them through the protein and thus biological membranes. Defining the biological and chemical parameters that determine and affect coordination dynamics of metal ions in proteins will inform future investigations of metalloproteins.

In vitro Production of Hemin-Based Artificial Metalloenzymes.

Developing enzyme alternatives is pivotal to improving and enabling new processes in biotechnology and industry. Artificial metalloenzymes (ArMs) are combinations of protein scaffolds with metal elements, such as metal nanoclusters or metal-containing molecules with specific catalytic properties, which can be customized. Here, we engineered an ArM based on the consensus tetratricopeptide repeat (CTPR) scaffold by introducing a unique histidine residue to coordinate the hemin cofactor. Our results show that this engineered system exhibits robust peroxidase-like catalytic activity driven by the hemin. The expression of the scaffold and subsequent coordination of hemin was achieved by recombinant expression in bulk and through in vitro transcription and translation systems in water-in-oil drops. The ability to synthesize this system in emulsio paves the way to improve its properties by means of droplet microfluidic screenings, facilitating the exploration of the protein combinatorial space to discover improved or novel catalytic activities.

Advancing Our Understanding of Pyranopterin-Dithiolene Contributions to Moco Enzyme Catalysis.

The pyranopterin dithiolene ligand is remarkable in terms of its geometric and electronic structure and is uniquely found in mononuclear molybdenum and tungsten enzymes. The pyranopterin dithiolene is found coordinated to the metal ion, deeply buried within the protein, and non-covalently attached to the protein via an extensive hydrogen bonding network that is enzyme-specific. However, the function of pyranopterin dithiolene in enzymatic catalysis has been difficult to determine. This focused account aims to provide an overview of what has been learned from the study of pyranopterin dithiolene model complexes of molybdenum and how these results relate to the enzyme systems. This work begins with a summary of what is known about the pyranopterin dithiolene ligand in the enzymes. We then introduce the development of inorganic small molecule complexes that model aspects of a coordinated pyranopterin dithiolene and discuss the results of detailed physical studies of the models by electronic absorption, resonance Raman, X-ray absorption and NMR spectroscopies, cyclic voltammetry, X-ray crystallography, and chemical reactivity.

History of Maturation of Prokaryotic Molybdoenzymes-A Personal View.

In prokaryotes, the role of Mo/W enzymes in physiology and bioenergetics is widely recognized. It is worth noting that the most diverse family of Mo/W enzymes is exclusive to prokaryotes, with the probable existence of several of them from the earliest forms of life on Earth. The structural organization of these enzymes, which often include additional redox centers, is as diverse as ever, as is their cellular localization. The most notable observation is the involvement of dedicated chaperones assisting with the assembly and acquisition of the metal centers, including Mo/W-bisPGD, one of the largest organic cofactors in nature. This review seeks to provide a new understanding and a unified model of Mo/W enzyme maturation.