De novo metalloprotein design

Retuning the potential of the electrochemical leaf

The electrochemical leaf enables the electrification and control of multi-enzyme cascades by exploiting two discoveries: (i) the ability to electrify the photosynthetic enzyme ferredoxin NADP+ reductase (FNR), driving it to catalyse the interconversion of NADP+/NADPH whilst it is entrapped in a highly porous, metal oxide electrode, and (ii) the evidence that additional enzymes can be co-entrapped in the electrode pores where, through one NADP(H)-dependent enzyme, extended cascades can be driven by electrical connection to FNR, via NADP(H) recycling. By changing a critical active-site tyrosine to serine, FNR's exclusivity for NADP(H) is swapped for unphosphorylated NAD(H). Here we present an electrochemical study of this variant FNR, and show that in addition to the intended inversion of cofactor preference, this change to the active site has altered FNR's tuning of the flavin reduction potential, making it less reductive. Exploiting the ability to monitor the variant's activity with NADP(H) as a function of potential has revealed a trapped intermediate state, relieved only by applying a negative overpotential, which allows catalysis to proceed. Inhibition by NADP+ (very tightly bound) with respect to NAD(H) turnover was also revealed and interestingly, this inhibition changes depending on the applied potential. These findings are of critical importance for future exploitation of the electrochemical leaf.

Development of Nanozymatic Characteristics in Metal-Doped Oxide Nanomaterials

Nanozymes are nanoscale materials that exhibit enzymatic-like activity, combining the benefits of nanomaterials with biocatalytic effects. The addition of metals to nanomaterials can enhance their nanozyme activity by mimicking the active sites of enzymes, providing structural support and promoting redox activity. In this study, nanostructured oxide and silicate-phosphate nanomaterials with varying manganese and copper additions were characterized. The objective was to assess the influence of metal modifications (Mn and Cu) on the acquisition of the nanozymatic activity by selected nanomaterials. An increase in manganese content in each material enhanced proteolytic activity (from 20 to 40 mUnit/mg for BG-Mn), while higher copper addition in glassy materials increased activity by 40%. Glassy materials exhibited approximately twice the 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid radical activity (around 40 μmol/mL) compared to that of oxide materials. The proteolytic and antioxidant activities discussed in the study can be considered indicators for evaluating the enzymatic properties of the nanomaterials. Observations conducted on nanomaterials may aid in the development of materials with enhanced catalytic efficiency and a wide range of applications.

Structure-driven development of a biomimetic rare earth artificial metalloprotein

The 2011 discovery of the first rare earth-dependent enzyme in methylotrophic Methylobacterium extorquens AM1 prompted intensive research toward understanding the unique chemistry at play in these systems. This enzyme, an alcohol dehydrogenase (ADH), features a La3+ ion closely associated with redox-active coenzyme pyrroloquinoline quinone (PQQ) and is structurally homologous to the Ca2+-dependent ADH from the same organism. AM1 also produces a periplasmic PQQ-binding protein, PqqT, which we have now structurally characterized to 1.46-Å resolution by X-ray diffraction. This crystal structure reveals a Lys residue hydrogen-bonded to PQQ at the site analogously occupied by a Lewis acidic cation in ADH. Accordingly, we prepared K142A- and K142D-PqqT variants to assess the relevance of this site toward metal binding. Isothermal titration calorimetry experiments and titrations monitored by UV-Vis absorption and emission spectroscopies support that K142D-PqqT binds tightly (Kd = 0.6 ± 0.2 μM) to La3+ in the presence of bound PQQ and produces spectral signatures consistent with those of ADH enzymes. These spectral signatures are not observed for WT- or K142A-variants or upon addition of Ca2+ to PQQ ⸦ K142D-PqqT. Addition of benzyl alcohol to La3+-bound PQQ ⸦ K142D-PqqT (but not Ca2+-bound PQQ ⸦ K142D-PqqT, or La3+-bound PQQ ⸦ WT-PqqT) produces spectroscopic changes associated with PQQ reduction, and chemical trapping experiments reveal the production of benzaldehyde, supporting ADH activity. By creating a metal binding site that mimics native ADH enzymes, we present a rare earth-dependent artificial metalloenzyme primed for future mechanistic, biocatalytic, and biosensing applications.

Application of artificial backbone connectivity in the development of metalloenzyme mimics

Metal-dependent enzymes are abundant and vital catalytic agents in nature. The functional versatility of metalloenzymes has made them common targets for improvement by protein engineering as well as mimicry by de novo designed sequences. In both strategies, the incorporation of non-canonical cofactors and/or non-canonical side chains has proved a useful tool. Less explored-but similarly powerful-is the utilization of non-canonical covalent modifications to the polypeptide backbone itself. Such efforts can entail either introduction of limited artificial monomers in natural chains to produce heterogeneous backbones or construction of completely abiotic oligomers that adopt defined folds. Herein, we review recent research applying artificial protein-like backbones in the construction of metalloenzyme mimics, highlighting progress as well as open questions in this emerging field.

Biohybrid materials comprising an artificial peroxidase and differently shaped gold nanoparticles

The immobilization of biocatalysts on inorganic supports allows the development of bio-nanohybrid materials with defined functional properties. Gold nanomaterials (AuNMs) are the main players in this field, due to their fascinating shape-dependent properties that account for their versatility. Even though incredible progress has been made in the preparation of AuNMs, few studies have been carried out to analyze the impact of particle morphology on the behavior of immobilized biocatalysts. Herein, the artificial peroxidase Fe(iii)-Mimochrome VI*a (FeMC6*a) was conjugated to two different anisotropic gold nanomaterials, nanorods (AuNRs) and triangular nanoprisms (AuNTs), to investigate how the properties of the nanosupport can affect the functional behavior of FeMC6*a. The conjugation of FeMC6*a to AuNMs was performed by a click-chemistry approach, using FeMC6*a modified with pegylated aza-dibenzocyclooctyne (FeMC6*a-PEG4@DBCO), which was allowed to react with azide-functionalized AuNRs and AuNTs, synthesized from citrate-capped AuNMs. To this end, a literature protocol for depleting CTAB from AuNRs was herein reported for the first time to prepare citrate-AuNTs. The overall results suggest that the nanomaterial shape influences the nanoconjugate functional properties. Besides giving new insights into the effect of the surfaces on the artificial peroxidase properties, these results open up the way for creating novel nanostructures with potential applications in the field of sensing devices.

Selection of a promiscuous minimalist cAMP phosphodiesterase from a library of de novo designed proteins

The ability of unevolved amino acid sequences to become biological catalysts was key to the emergence of life on Earth. However, billions of years of evolution separate complex modern enzymes from their simpler early ancestors. To probe how unevolved sequences can develop new functions, we use ultrahigh-throughput droplet microfluidics to screen for phosphoesterase activity amidst a library of more than one million sequences based on a de novo designed 4-helix bundle. Characterization of hits revealed that acquisition of function involved a large jump in sequence space enriching for truncations that removed >40% of the protein chain. Biophysical characterization of a catalytically active truncated protein revealed that it dimerizes into an α-helical structure, with the gain of function accompanied by increased structural dynamics. The identified phosphodiesterase is a manganese-dependent metalloenzyme that hydrolyses a range of phosphodiesters. It is most active towards cyclic AMP, with a rate acceleration of ~109 and a catalytic proficiency of >1014 M-1, comparable to larger enzymes shaped by billions of years of evolution.

Will We Witness Enzymatic or Pd-(Oligo)Peptide Catalysis in Suzuki Cross-Coupling Reactions?

Despite the development of numerous advanced ligands for Pd-catalyzed Suzuki cross-coupling reaction, the potential of (oligo)peptides serving as ligands remains unexplored. This study demonstrates via density functional theory (DFT) modeling that (oligo)peptide ligands can drive superior activity compared to classic phosphines in these reactions. The utilization of natural amino acids such as Met, SeMet, and His leads to strong binding of the Pd center, thereby ensuring substantial stability of the system. The increasing sustainability and economic viability of (oligo)peptide synthesis open new prospects for applying Pd-(oligo)peptide systems as greener catalysts. The feasibility of de novo engineering an artificial Pd-based enzyme for Suzuki cross-coupling is discussed, laying the groundwork for future innovations in catalytic systems.

Fluorescent Protein-Based Sensors for Detecting Essential Metal Ions across the Tree of Life

Genetically encoded fluorescent metal ion sensors are powerful tools for elucidating metal dynamics in living systems. Over the last 25 years since the first examples of genetically encoded fluorescent protein-based calcium indicators, this toolbox of probes has expanded to include other essential and non-essential metal ions. Collectively, these tools have illuminated fundamental aspects of metal homeostasis and trafficking that are crucial to fields ranging from neurobiology to human nutrition. Despite these advances, much of the application of metal ion sensors remains limited to mammalian cells and tissues and a limited number of essential metals. Applications beyond mammalian systems and in vivo applications in living organisms have primarily used genetically encoded calcium ion sensors. The aim of this Perspective is to provide, with the support of historical and recent literature, an updated and critical view of the design and use of fluorescent protein-based sensors for detecting essential metal ions in various organisms. We highlight the historical progress and achievements with calcium sensors and discuss more recent advances and opportunities for the detection of other essential metal ions. We also discuss outstanding challenges in the field and directions for future studies, including detecting a wider variety of metal ions, developing and implementing a broader spectral range of sensors for multiplexing experiments, and applying sensors to a wider range of single- and multi-species biological systems.

Co(II) Substitution Enhances the Esterase Activity of a de Novo Designed Zn(II) Carbonic Anhydrase

Carbonic Anhydrases (CAs) have been a target for de novo protein designers due to the simplicity of the active site and rapid rate of the reaction. The first reported mimic contained a Zn(II) bound to three histidine imidazole nitrogens and an exogenous water molecule, hence closely mimicking the native enzymes' first coordination sphere. Co(II) has served as an alternative metal to interrogate CAs due to its d7 electronic configuration for more detailed solution characterization. We present here the Co(II) substituted [Co(II)(H2O/OH-)]N(TRIL2WL23H)3 n+ that behaves similarly to native Co(II) substituted human-CAs. Like the Zn(II) analogue, the cobalt-derivative at slightly basic pH is incapable of hydrolyzing p-nitrophenylacetate (pNPA); however, as the pH is increased a significant activity develops, which at pH values above 10 eventually yields a catalytic efficiency that exceeds that of the [Zn(II)(OH-)]N(TRIL2WL23H)3 + peptide complex. X-ray absorption analysis is consistent with an octahedral species at pH 7.5 that converts to a 5-coordinate species by pH 11. UV-vis spectroscopy can monitor this transition, giving a pKa for the conversion of 10.3. We assign this conversion to the formation of a 5-coordinate Co(II)(Nimid)3(OH)(H2O) species. The pH dependent kinetic analysis indicates the maximal rate (kcat), and thus the catalytic efficiency (kcat/Km), follow the same pH profile as the spectroscopic conversion to the pentacoordinate species. This correlation suggests that the chemically irreversible ester hydrolysis corresponds to the rate determining process.

In silico design of misfolding resistant proteins: the role of structural similarity of a competing conformational ensemble in the optimization of frustration

Most state-of-the-art in silico design methods fail due to misfolding of designed sequences to a conformation other than the target. Thus, a method to design misfolding resistant proteins will provide a better understanding of the misfolding phenomenon and will also increase the success rate of in silico design methods. In this work, we optimize the conformational ensemble to be selected for negative design purposes based on the similarity of the conformational ensemble to the target. Five ensembles with different degrees of similarity to the target are created and destabilized and the target is stabilized while designing sequences using mean field theory and Monte Carlo simulation methods. The results suggest that the degree of similarity of the non-native conformations to the target plays a prominent role in designing misfolding resistant protein sequences. The design procedures that destabilize the conformational ensemble with moderate similarity to the target have proven to be more promising. Incorporation of either highly similar or highly dissimilar conformations to the target conformation into the non-native ensemble to be destabilized may lead to sequences with a higher misfolding propensity. This will significantly reduce the conformational space to be considered in any protein design procedure. Interestingly, the results suggest that a sequence with higher frustration in the target structure does not necessarily lead to a misfold prone sequence. A successful design method may purposefully choose a frustrated sequence in the target conformation if that sequence is even more frustrated in the competing non-native conformations.

MetalHawk: Enhanced Classification of Metal Coordination Geometries by Artificial Neural Networks

The chemical properties of metal complexes are strongly dependent on the number and geometrical arrangement of ligands coordinated to the metal center. Existing methods for determining either coordination number or geometry rely on a trade-off between accuracy and computational costs, which hinders their application to the study of large structure data sets. Here, we propose MetalHawk (https://github.com/vrettasm/MetalHawk), a machine learning-based approach to perform simultaneous classification of metal site coordination number and geometry through artificial neural networks (ANNs), which were trained using the Cambridge Structural Database (CSD) and Metal Protein Data Bank (MetalPDB). We demonstrate that the CSD-trained model can be used to classify sites belonging to the most common coordination numbers and geometry classes with balanced accuracy equal to 96.51% for CSD-deposited metal sites. The CSD-trained model was also found to be capable of classifying bioinorganic metal sites from the MetalPDB database, with balanced accuracy equal to 84.29% on the whole PDB data set and to 91.66% on manually reviewed sites in the PDB validation set. Moreover, we report evidence that the output vectors of the CSD-trained model can be considered as a proxy indicator of metal-site distortions, showing that these can be interpreted as a low-dimensional representation of subtle geometrical features present in metal site structures.

Real-time detection of 20 amino acids and discrimination of pathologically relevant peptides with functionalized nanopore

Precise identification and quantification of amino acids is crucial for many biological applications. Here we report a copper(II)-functionalized Mycobacterium smegmatis porin A (MspA) nanopore with the N91H substitution, which enables direct identification of all 20 proteinogenic amino acids when combined with a machine-learning algorithm. The validation accuracy reaches 99.1%, with 30.9% signal recovery. The feasibility of ultrasensitive quantification of amino acids was also demonstrated at the nanomolar range. Furthermore, the capability of this system for real-time analyses of two representative post-translational modifications (PTMs), one unnatural amino acid and ten synthetic peptides using exopeptidases, including clinically relevant peptides associated with Alzheimer's disease and cancer neoantigens, was demonstrated. Notably, our strategy successfully distinguishes peptides with only one amino acid difference from the hydrolysate and provides the possibility to infer the peptide sequence.

PinMyMetal: A hybrid learning system to accurately model metal binding sites in macromolecules

Metal ions are vital components in many proteins for the inference and engineering of protein function, with coordination complexity linked to structural (4-residue predominate), catalytic (3-residue predominate), or regulatory (2-residue predominate) roles. Computational tools for modeling metal ions in protein structures, especially for transient, reversible, and concentration-dependent regulatory sites, remain immature. We present PinMyMetal (PMM), a sophisticated hybrid machine learning system for predicting zinc ion localization and environment in macromolecular structures. Compared to other predictors, PMM excels in predicting regulatory sites (median deviation of 0.34 Å), demonstrating superior accuracy in locating catalytic sites (median deviation of 0.27 Å) and structural sites (median deviation of 0.14 Å). PMM assigns a certainty score to each predicted site based on local structural and physicochemical features independent of homolog presence. Interactive validation through our server, CheckMyMetal, expands PMM's scope, enabling it to pinpoint and validates diverse functional zinc sites from different structure sources (predicted structures, cryo-EM and crystallography). This facilitates residue-wise assessment and robust metal binding site design. The lightweight PMM system demands minimal computing resources and is available at https://PMM.biocloud.top. While currently trained on zinc, the PMM workflow can easily adapt to other metals through expanded training data.

Relationship of Thermostability and Binding Affinity in Metal-binding WW-Domain Minireceptors

The design of metallo-miniproteins advances our understanding of the structural and functional roles of metals in proteins. We recently designed a metal-binding WW domain, WW-CA-Nle, which displays three histidine residues on its surface for coordination of divalent metals Ni(II), Zn(II) and Cu(II). However, WW-CA-Nle is a molten globule in the apo state and thus showed only moderate binding affinities with Kd values in the μM regime. In this report, we hypothesize that improved thermal stability of the apo state of the metal binding WW-domain scaffold should lead to improved preorganization of the metal-binding site and consequently to higher metal-binding affinities. By redesigning WW-CA-Nle, we obtained WW-CA variants, WW-CA-min and WW-CA-ANG, which were fully folded in the apo states and displayed moderate to excellent thermostabilities in the apo and holo states. We were able to show that the improved thermal stabilities led to improved metal binding, which was reflected in Kd values that were at least one order of magnitude lower compared to WW-CA-Nle. EPR spectroscopy and ITC measurements revealed a better defined and predisposed metal binding site in WW-CA-ANG.

Tunnel engineering of gas-converting enzymes for inhibitor retardation and substrate acceleration

Carbon monoxide dehydrogenase (CODH), formate dehydrogenase (FDH), hydrogenase (H2ase), and nitrogenase (N2ase) are crucial enzymatic catalysts that facilitate the conversion of industrially significant gases such as CO, CO2, H2, and N2. The tunnels in the gas-converting enzymes serve as conduits for these low molecular weight gases to access deeply buried catalytic sites. The identification of the substrate tunnels is imperative for comprehending the substrate selectivity mechanism underlying these gas-converting enzymes. This knowledge also holds substantial value for industrial applications, particularly in addressing the challenges associated with separation and utilization of byproduct gases. In this comprehensive review, we delve into the emerging field of tunnel engineering, presenting a range of approaches and analyses. Additionally, we propose methodologies for the systematic design of enzymes, with the ultimate goal of advancing protein engineering strategies.

Thermodynamics of Metal-Acetate Interactions

Metal ions play crucial roles in protein- and ligand-mediated interactions. They not only act as catalysts to facilitate biological processes but are also important as protein structural elements. Accurately predicting metal ion interactions in computational studies has always been a challenge, and various methods have been suggested to improve these interactions. One such method is the 12-6-4 Lennard-Jones (LJ)-type nonbonded model. Using this model, it has been possible to successfully reproduce the experimental properties of metal ions in aqueous solution. The model includes induced dipole interactions typically ignored in the standard 12-6 LJ nonbonded model. In this we expand the applicability of this model to metal ion-carboxylate interactions. Using 12-6-4 parameters that reproduce the solvation free energies of the metal ions leads to an overestimation of metal ion-acetate interactions, thus, prompting us to fine-tune the model to specifically handle the latter. We also show that the standard 12-6 LJ model significantly falls short in reproducing the experimental binding free energy between acetate and 11 metal ions (Ni(II), Mg(II), Cu(II), Zn(II), Co(II), Cu(I), Fe(II), Mn(II), Cd(II), Ca(II), and Ag(I)). In this study, we describe optimized C4 parameters for the 12-6-4 LJ nonbonded model to be used with three widely employed water models (Transferable Intermolecular Potential with 3 Points (TIP3P), Simple Point Charge Extended (SPC/E), and Optimal Point Charge (OPC) water models). These parameters can accurately match the experimental binding free energy between 11 metal ions and acetate. These parameters can be applied to the study of metalloproteins and transition metal ion channels and transporters, as acetate serves as a representative of the negatively charged amino acid side chains from aspartate and glutamate.

Formation of Supplementary Metal-Binding Centers in Proteins under Stress Conditions

In many proteins, supplementary metal-binding centers appear under stress conditions. They are known as aberrant or atypical sites. Physico-chemical properties of proteins are significantly changed after such metal binding, and very stable protein aggregates are formed, in which metals act as "cross-linking" agents. Supplementary metal-binding centers in proteins often arise as a result of posttranslational modifications caused by reactive oxygen and nitrogen species and reactive carbonyl compounds. New chemical groups formed as a result of these modifications can act as ligands for binding metal ions. Special attention is paid to the role of cysteine SH-groups in the formation of supplementary metal-binding centers, since these groups are the main target for the action of reactive species. Supplementary metal binding centers may also appear due to unmasking of amino acid residues when protein conformation changing. Appearance of such centers is usually considered as a pathological process. Such unilateral approach does not allow to obtain an integral view of the phenomenon, ignoring cases when formation of metal complexes with altered proteins is a way to adjust protein properties, activity, and stability under the changed redox conditions. The role of metals in protein aggregation is being studied actively, since it leads to formation of non-membranous organelles, liquid condensates, and solid conglomerates. Some proteins found in such aggregates are typical for various diseases, such as Alzheimer's and Huntington's diseases, amyotrophic lateral sclerosis, and some types of cancer.

An Artificial Miniaturized Peroxidase for Signal Amplification in Lateral Flow Immunoassays

Signal amplification strategies are widely used for improving the sensitivity of lateral flow immunoassays (LFiAs). Herein, the artificial miniaturized peroxidase Fe(III)-MimochromeVI*a (FeMC6*a), immobilized on gold nanoparticles (AuNPs), is used as a strategy to obtain catalytic signal amplification in sandwich immunoassays on lateral flow strips. The assay scheme uses AuNPs decorated with the mini-peroxidase FeMC6*a and anti-human-IgG as a detection antibody (dAb), for the detection of human-IgG, as a model analyte. Recognition of the analyte by the capture and detection antibodies is first evidenced by the appearance of a red color in the test line (TL), due to the accumulation of AuNPs. Subsequent addition of 3,3',5,5'-tetramethylbenzidine (TMB) induces an increase of the test line color, due to the TMB being converted into an insoluble colored product, catalyzed by FeMC6*a. This work shows that FeMC6*a acts as an efficient catalyst in paper, increasing the sensitivity of an LFiA up to four times with respect to a conventional LFiA. Furthermore, FeMC6*a achieves lower limits of detection that are found in control experiments where it is replaced with horseradish peroxidase (HRP), its natural counterpart. This study represents a significant proof-of-concept for the development of more sensitive LFiAs, for different analytes, based on properly designed artificial metalloenzymes.

A designed Copper Histidine-brace enzyme for oxidative depolymerization of polysaccharides as a model of lytic polysaccharide monooxygenase

The "Histidine-brace" (His-brace) copper-binding site, composed of Cu(His)2 with a backbone amine, is found in metalloproteins with diverse functions. A primary example is lytic polysaccharide monooxygenase (LPMO), a class of enzymes that catalyze the oxidative depolymerization of polysaccharides, providing not only an energy source for native microorganisms but also a route to more effective industrial biomass conversion. Despite its importance, how the Cu His-brace site performs this unique and challenging oxidative depolymerization reaction remains to be understood. To answer this question, we have designed a biosynthetic model of LPMO by incorporating the Cu His-brace motif into azurin, an electron transfer protein. Spectroscopic studies, including ultraviolet-visible (UV-Vis) absorption and electron paramagnetic resonance, confirm copper binding at the designed His-brace site. Moreover, the designed protein is catalytically active towards both cellulose and starch, the native substrates of LPMO, generating degraded oligosaccharides with multiturnovers by C1 oxidation. It also performs oxidative cleavage of the model substrate 4-nitrophenyl-D-glucopyranoside, achieving a turnover number ~9% of that of a native LPMO assayed under identical conditions. This work presents a rationally designed artificial metalloenzyme that acts as a structural and functional mimic of LPMO, which provides a promising system for understanding the role of the Cu His-brace site in LPMO activity and potential application in polysaccharide degradation.

Primary and Secondary Coordination Sphere Effects on the Structure and Function of S-Nitrosylating Azurin

Much progress has been made in understanding the roles of the secondary coordination sphere (SCS) in tuning redox potentials of metalloproteins. In contrast, the impact of SCS on reactivity is much less understood. A primary example is how copper proteins can promote S-nitrosylation (SNO), which is one of the most important dynamic post-translational modifications, and is crucial in regulating nitric oxide storage and transportation. Specifically, the factors that instill CuII with S-nitrosylating capabilities and modulate activity are not well understood. To address this issue, we investigated the influence of the primary and secondary coordination sphere on CuII-catalyzed S-nitrosylation by developing a series of azurin variants with varying catalytic capabilities. We have employed a multidimensional approach involving electronic absorption, S and Cu K-edge XAS, EPR, and resonance Raman spectroscopies together with QM/MM computational analysis to examine the relationships between structure and molecular mechanism in this reaction. Our findings have revealed that kinetic competency is correlated with three balancing factors, namely Cu-S bond strength, Cu spin localization, and relative S(ps) vs S(pp) contributions to the ground state. Together, these results support a reaction pathway that proceeds through the attack of the Cu-S bond rather than electrophilic addition to CuII or radical attack of SCys. The insights gained from this work provide not only a deeper understanding of SNO in biology but also a basis for designing artificial and tunable SNO enzymes to regulate NO and prevent diseases due to SNO dysregulation.

Diversifying the functions of heme proteins with non-porphyrin cofactors

Heme proteins perform diverse biochemical functions using a single iron porphyrin cofactor. This versatility makes them attractive platforms for the development of new functional proteins. While directed evolution and metal substitution have expanded the properties, reactivity, and applications of heme proteins, the incorporation of porphyrin analogs remains an underexplored approach. This review discusses the replacement of heme with non-porphyrin cofactors, such as porphycene, corrole, tetradehydrocorrin, phthalocyanine, and salophen, and the attendant properties of these conjugates. While structurally similar, each ligand exhibits distinct optical and redox properties, as well as unique chemical reactivity. These hybrids serve as model systems to elucidate the effects of the protein environment on the electronic structure, redox potentials, optical properties, or other features of the porphyrin analog. Protein encapsulation can confer distinct chemical reactivity or selectivity of artificial metalloenzymes that cannot be achieved with the small molecule catalyst alone. Additionally, these conjugates can interfere with heme acquisition and uptake in pathogenic bacteria, providing an inroad to innovative antibiotic strategies. Together, these examples illustrate the diverse functionality that can be achieved by cofactor substitution. The further expansion of this approach will access unexplored chemical space, enabling the development of superior catalysts and the creation of heme proteins with emergent properties.

The design of functional proteins using tensorized energy calculations

In protein design, the energy associated with a huge number of sequence-conformer perturbations has to be routinely estimated. Hence, enhancing the throughput and accuracy of these energy calculations can profoundly improve design success rates and enable tackling more complex design problems. In this work, we explore the possibility of tensorizing the energy calculations and apply them in a protein design framework. We use this framework to design enhanced proteins with anti-cancer and radio-tracing functions. Particularly, we designed multispecific binders against ligands of the epidermal growth factor receptor (EGFR), where the tested design could inhibit EGFR activity in vitro and in vivo. We also used this method to design high-affinity Cu2+ binders that were stable in serum and could be readily loaded with copper-64 radionuclide. The resulting molecules show superior functional properties for their respective applications and demonstrate the generalizable potential of the described protein design approach.

Xenobiotic Bi3+ Coordination by Cysteine-Rich Metallothionein-3 Reveals a Cooperatively Formed Thiolate-Sharing Bi2S5 Cluster

The field of designing artificial metalloproteins has yet to effectively tackle the incorporation of multimetal clusters, which is a key component of natural metalloproteins, such as metallothioneins (MTs) and calmodulin. MT is a physiological, essential, cysteine-rich metalloprotein that binds to a variety of metals but is only known to form metal-thiolate clusters with Cd2+, Zn2+, and Cu+. Bismuth is a xenobiotic metal and a component of metallodrugs used to treat gastric ulcers and cancer, as well as an emerging metal used in industrial practices. Electrospray ionization mass spectrometry, UV-visible spectroscopy, and extended X-ray absorption fine structure spectroscopy were used to probe the Bi3+ binding site structures in apo-MT3 (brain-located MT) at pH 7.4 and 2 and provide the complete set of binding affinities. We discovered the highly cooperative formation of a novel Bi3+ species, Bi2MT3, under physiological conditions, where each Bi3+ ion is coordinated by three cysteinyl thiolates, with one of the thiolates bridging between the two Bi3+ ions. This cluster structure was associated with a strong visible region absorption band, which was disrupted by the addition of Zn2+ and reversibly disrupted by acidification and increased temperature. This is the first reported presence of bridging cysteines for a xenobiotic metal in MT3 and the Bi2MT structure is the first Bi cluster found in a metalloprotein.

An expandable, modular de novo protein platform for precision redox engineering

The electron-conducting circuitry of life represents an as-yet untapped resource of exquisite, nanoscale biomolecular engineering. Here, we report the characterization and structure of a de novo diheme "maquette" protein, 4D2, which we subsequently use to create an expanded, modular platform for heme protein design. A well-folded monoheme variant was created by computational redesign, which was then utilized for the experimental validation of continuum electrostatic redox potential calculations. This demonstrates how fundamental biophysical properties can be predicted and fine-tuned. 4D2 was then extended into a tetraheme helical bundle, representing a 7 nm molecular wire. Despite a molecular weight of only 24 kDa, electron cryomicroscopy illustrated a remarkable level of detail, indicating the positioning of the secondary structure and the heme cofactors. This robust, expressible, highly thermostable and readily designable modular platform presents a valuable resource for redox protein design and the future construction of artificial electron-conducting circuitry.

Atomically Accurate Design of Metalloproteins with Predefined Coordination Geometries

We report a new computational protein design method for the construction of oligomeric protein assemblies around metal centers with predefined coordination geometries. We apply this method to design two homotrimeric assemblies, Tet4 and TP1, with tetrahedral and trigonal-pyramidal tris(histidine) metal coordination geometries, respectively, and demonstrate that both assemblies form the targeted metal centers with ≤0.2 Å accuracy. Although Tet4 and TP1 are constructed from the same parent protein building block, they are distinct in terms of their overall architectures, the environment surrounding the metal centers, and their metal-based reactivities, illustrating the versatility of our approach.

Design and Selection of Heterodimerizing Helical Hairpins for Synthetic Biology

Synthetic biology applications would benefit from protein modules of reduced complexity that function orthogonally to cellular components. As many subcellular processes depend on peptide-protein or protein-protein interactions, de novo designed polypeptides that can bring together other proteins controllably are particularly useful. Thanks to established sequence-to-structure relationships, helical bundles provide good starting points for such designs. Typically, however, such designs are tested in vitro and function in cells is not guaranteed. Here, we describe the design, characterization, and application of de novo helical hairpins that heterodimerize to form 4-helix bundles in cells. Starting from a rationally designed homodimer, we construct a library of helical hairpins and identify complementary pairs using bimolecular fluorescence complementation in E. coli. We characterize some of the pairs using biophysics and X-ray crystallography to confirm heterodimeric 4-helix bundles. Finally, we demonstrate the function of an exemplar pair in regulating transcription in both E. coli and mammalian cells.

Study and design of amino acid-based radical enzymes using unnatural amino acids

Radical enzymes harness the power of reactive radical species by placing them in a protein scaffold, and they are capable of catalysing many important reactions. New native radical enzymes, especially those with amino acid-based radicals, in the category of non-heme iron enzymes (including ribonucleotide reductases), heme enzymes, copper enzymes, and FAD-radical enzymes have been discovered and characterized. We discussed recent research efforts to discover new native amino acid-based radical enzymes, and to study the roles of radicals in processes such as enzyme catalysis and electron transfer. Furthermore, design of radical enzymes in a small and simple scaffold not only allows us to study the radical in a well-controlled system and test our understanding of the native enzymes, but also allows us to create powerful enzymes. In the study and design of amino acid-based radical enzymes, the use of unnatural amino acids allows precise control of pKa values and reduction potentials of the residue, as well as probing the location of the radical through spectroscopic methods, making it a powerful research tool. Our understanding of amino acid-based radical enzymes will allow us to tailor them to create powerful catalysts and better therapeutics.

Metal3D: a general deep learning framework for accurate metal ion location prediction in proteins

Metal ions are essential cofactors for many proteins and play a crucial role in many applications such as enzyme design or design of protein-protein interactions because they are biologically abundant, tether to the protein using strong interactions, and have favorable catalytic properties. Computational design of metalloproteins is however hampered by the complex electronic structure of many biologically relevant metals such as zinc . In this work, we develop two tools - Metal3D (based on 3D convolutional neural networks) and Metal1D (solely based on geometric criteria) to improve the location prediction of zinc ions in protein structures. Comparison with other currently available tools shows that Metal3D is the most accurate zinc ion location predictor to date with predictions within 0.70 ± 0.64 Å of experimental locations. Metal3D outputs a confidence metric for each predicted site and works on proteins with few homologes in the protein data bank. Metal3D predicts a global zinc density that can be used for annotation of computationally predicted structures and a per residue zinc density that can be used in protein design workflows. Currently trained on zinc, the framework of Metal3D is readily extensible to other metals by modifying the training data.

Selective Oxidation of Halophenols Catalyzed by an Artificial Miniaturized Peroxidase

The development of artificial enzymes for application in sustainable technologies, such as the transformation of environmental pollutants or biomass, is one of the most challenging goals in metalloenzyme design. In this work, we describe the oxidation of mono-, di-, tri- and penta-halogenated phenols catalyzed by the artificial metalloenzyme Fe-MC6*a. It promoted the dehalogenation of 4-fluorophenol into the corresponding 1,4-benzoquinone, while under the same experimental conditions, 4-chloro, 4-bromo and 4-iodophenol were selectively converted into higher molecular weight compounds. Analysis of the 4-chlorophenol oxidation products clarified that oligomers based on C-O bonds were exclusively formed in this case. All results show that Fe-MC6*a holds intriguing enzymatic properties, as it catalyzes halophenol oxidation with substrate-dependent chemoselectivity.

Designed Rubredoxin miniature in a fully artificial electron chain triggered by visible light

Designing metal sites into de novo proteins has significantly improved, recently. However, identifying the minimal coordination spheres, able to encompass the necessary information for metal binding and activity, still represents a great challenge, today. Here, we test our understanding with a benchmark, nevertheless difficult, case. We assemble into a miniature 28-residue protein, the quintessential elements required to fold properly around a FeCys4 redox center, and to function efficiently in electron-transfer. This study addresses a challenge in de novo protein design, as it reports the crystal structure of a designed tetra-thiolate metal-binding protein in sub-Å agreement with the intended design. This allows us to well correlate structure to spectroscopic and electrochemical properties. Given its high reduction potential compared to natural and designed FeCys4-containing proteins, we exploit it as terminal electron acceptor of a fully artificial chain triggered by visible light.

Homochiral versus Heterochiral Dimeric Helical Foldamer Bundles: Chlorinated-Solvent-Dependent Self-Sorting

Aromatic oligoamide sequences programmed to fold into stable helical conformations were designed to display a linear array of hydrogen-bond donors and acceptors at their surface. Sequences were prepared by solid-phase synthesis. Solution ¹ H NMR spectroscopic studies and solid-state crystallographic structures demonstrated the formation of stable hydrogen-bond-mediated dimeric helix bundles that could be either heterochiral (with a P and an M helix) or homochiral (with two P or two M helices). Formation of the hetero- or homochiral dimers could be driven quantitatively using different chlorinated solvents-exemplifying a remarkable case of either social or narcissistic chiral self-sorting or upon imposing absolute handedness to the helices to forbid PM species.

Engineering excitonically coupled dimers in an artificial protein for light harvesting via computational modeling

In photosynthesis, pigment-protein complexes achieve outstanding photoinduced charge separation efficiencies through a set of strategies in which excited states delocalization over multiple pigments ("excitons") and charge-transfer states play key roles. These concepts, and their implementation in bioinspired artificial systems, are attracting increasing attention due to the vast potential that could be tapped by realizing efficient photochemical reactions. In particular, de novo designed proteins provide a diverse structural toolbox that can be used to manipulate the geometric and electronic properties of bound chromophore molecules. However, achieving excitonic and charge-transfer states requires closely spaced chromophores, a non-trivial aspect since a strong binding with the protein matrix needs to be maintained. Here, we show how a general-purpose artificial protein can be optimized via molecular dynamics simulations to improve its binding capacity of a chlorophyll derivative, achieving complexes in which chromophores form two closely spaced and strongly interacting dimers. Based on spectroscopy results and computational modeling, we demonstrate each dimer is excitonically coupled, and propose they display signatures of charge-transfer state mixing. This work could open new avenues for the rational design of chromophore-protein complexes with advanced functionalities.

Inside-Out Design of Zinc-Binding Proteins with Non-Native Backbones

The de novo design of functional proteins requires specification of tertiary structure and incorporation of molecular binding sites. Here, we develop an inside-out design strategy in the molecular modeling program Rosetta that begins with amino acid side chains from one or two α-helices making well-defined contacts with a ligand. A full-sized protein is then built around the ligand by adding additional helices that promote the formation of a protein core and allow additional contacts with the ligand. The protocol was tested by designing 12 zinc-binding proteins, each with 4-5 helices. Four of the designs were folded and bound to zinc with equilibrium dissociation constants varying between 95 nM and 1.1 μM. The design with the tightest affinity for zinc, N12, adopts a unique conformation in the folded state as assessed with nuclear magnetic resonance (NMR) and the design model closely matches (backbone root-mean-square deviation (RMSD) < 1 Å) an AlphaFold model of the sequence. Retrospective analysis with AlphaFold suggests that the sequences of many of the failed designs did not encode the desired tertiary packing.

GPDOCK: highly accurate docking strategy for metalloproteins based on geometric probability

Accurately predicting the interaction modes for metalloproteins remains extremely challenging in structure-based drug design and mechanism analysis of enzymatic catalysis due to the complexity of metal coordination in metalloproteins. Here, we report a docking method for metalloproteins based on geometric probability (GPDOCK) with unprecedented accuracy. The docking tests of 10 common metal ions with 9360 metalloprotein-ligand complexes demonstrate that GPDOCK has an accuracy of 94.3% in predicting binding pose. What is more, it can accurately realize the docking of metalloproteins with ligand when one or two water molecules are engaged in the metal ion coordination. Since GPDOCK only depends on the three-dimensional structure of metalloprotein and ligand, structure-based machine learning model is employed for the scoring of binding poses, which significantly improves computational efficiency. The proposed docking strategy can be an effective and efficient tool for drug design and further study of binding mechanism of metalloproteins. The manual of GPDOCK and the code for the logistical regression model used to re-rank the docking results are available at https://github.com/wangkai-zhku/GPDOCK.git.

A De Novo-Designed Type 3 Copper Protein Tunes Catechol Substrate Recognition and Reactivity

De novo metalloprotein design is a remarkable approach to shape protein scaffolds toward specific functions. Here, we report the design and characterization of Due Rame 1 (DR1), a de novo designed protein housing a di-copper site and mimicking the Type 3 (T3) copper-containing polyphenol oxidases (PPOs). To achieve this goal, we hierarchically designed the first and the second di-metal coordination spheres to engineer the di-copper site into a simple four-helix bundle scaffold. Spectroscopic, thermodynamic, and functional characterization revealed that DR1 recapitulates the T3 copper site, supporting different copper redox states, and being active in the O₂ -dependent oxidation of catechols to o-quinones. Careful design of the residues lining the substrate access site endows DR1 with substrate recognition, as revealed by Hammet analysis and computational studies on substituted catechols. This study represents a premier example in the construction of a functional T3 copper site into a designed four-helix bundle protein.

Copper-Containing Artificial Polyenzymes as a Clickase for Bioorthogonal Chemistry

Artificial polyenzymes (ArPoly) are tailored combinations of universal protein scaffolds and polymers newly proposed as promising alternatives to natural enzymes to expand the biocatalyst toolbox. The concept of ArPoly has been continuously extended to metal-containing ArPoly to overcome the drawbacks faced by conventional artificial metalloenzymes. Herein, we present a sustainable route to synthesize a novel water-soluble metalloenzyme for copper-catalyzed azide-alkyne cycloadditions in water with remarkable selectivity. In this case, synthetic l-proline monomers were polymerized onto bovine serum albumen in an aqueous medium via copper-mediated "grafting-from" atom-transfer radical polymerization, resulting in protein-polymer-copper conjugates named ArPoly_clickase. The copper in ArPoly_clickase plays pivotal bifunctional roles, not only as the catalyst for polymerization but also as the coordinated active site for alkyne-azide click catalysis. ArPoly_clickase showcases high efficiency, substrate generality, regioselectivity, and ease of product separation for "click chemistry" in water. Notably, ArPoly_clickase displays good biocompatibility without imposing copper toxicity on living cells, which offers the prospect for the upcoming bioorthogonal chemistry.

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.

Artificial Metalloproteins: At the Interface between Biology and Chemistry

Artificial metalloproteins (ArMs) have recently gained significant interest due to their potential to address issues in a broad scope of applications, including biocatalysis, biotechnology, protein assembly, and model chemistry. ArMs are assembled by the incorporation of a non-native metallocofactor into a protein scaffold. This can be achieved by a number of methods that apply tools of chemical biology, computational de novo design, and synthetic chemistry. In this Perspective, we highlight select systems in the hope of demonstrating the breadth of ArM design strategies and applications and emphasize how these systems address problems that are otherwise difficult to do so with strictly biochemical or synthetic approaches.

Single-Molecule Force Spectroscopy Reveals the Dynamic HgS Coordination Site in the De Novo-Designed Metalloprotein α3DIV

The de novo-designed metalloprotein α3DIV binds to mercury via three cysteine residues under dynamic conditions. An unusual trigonal three-coordinate HgS3 site is formed in the protein in basic solution, whereas a linear two-coordinate HgS2 site is formed in acidic solution. Furthermore, it is unknown whether the two coordinated cysteines in the HgS2 site are fixed or not, which may lead to more dynamics. However, the signal for HgS2 sites with different cysteines may be similar or may be averaged and indistinguishable. To circumvent this problem, we adopt a single-molecule approach to study one mercury site at a time. Using atomic force microscopy-based single-molecule force spectroscopy, the protein is unfolded, and the HgS site is ruptured. The results confirm the formation of HgS3 and HgS2 sites at different pH values. Moreover, it is found that any two of the three cysteines in the protein bind to mercury in the HgS2 site.

Machine Learning Approaches for Metalloproteins

Metalloproteins are a family of proteins characterized by metal ion binding, whereby the presence of these ions confers key catalytic and ligand-binding properties. Due to their ubiquity among biological systems, researchers have made immense efforts to predict the structural and functional roles of metalloproteins. Ultimately, having a comprehensive understanding of metalloproteins will lead to tangible applications, such as designing potent inhibitors in drug discovery. Recently, there has been an acceleration in the number of studies applying machine learning to predict metalloprotein properties, primarily driven by the advent of more sophisticated machine learning algorithms. This review covers how machine learning tools have consolidated and expanded our comprehension of various aspects of metalloproteins (structure, function, stability, ligand-binding interactions, and inhibitors). Future avenues of exploration are also discussed.