-HH and -HAAAH motifs act as fishing nets for biologically relevant metal ions in metallopeptides

Histidine are one of the most common residues involved in transition metal ion binding in the active sites of metalloenzymes. In order to mimic enzymatic metal binding sites, it is crucial to understand the basic coordination modes of histidine residues, distributed at different positions in the peptide sequence. We show that: (i) the separation of two histidines has a large effect on complex stability - a sequence with adjusting histidine residues forms more stable complexes with Zn(II) than the one in which the residues are separated, while the contrary is observed for Cu(II) complexes, in which amide nitrogens participate in metal binding. No pronounced effect is observed for Ni(II) complexes, where the amides participate in binding at higher pH; (ii) non-coordinating amino acid residues (basic, acidic and aromatic ones) have a significant impact on complex stability; charged and aromatic residues may enhance Zn(II) binding, while the contrary is observed for the amide-binding Cu(II); (iii) cysteine containing sequences are much more effective Zn(II) and Ni(II) binding motifs at pH above 8, while histidine containing ligands are more suitable for effective Zn(II) and Ni(II) binding at lower pH.

A Key Role in Catalysis and Enzyme Thermostability of a Conserved Helix H5 Motif of Human Glutathione Transferase A1-1

Glutathione transferases (GSTs) are promiscuous enzymes whose main function is the detoxification of electrophilic compounds. These enzymes are characterized by structural modularity that underpins their exploitation as dynamic scaffolds for engineering enzyme variants, with customized catalytic and structural properties. In the present work, multiple sequence alignment of the alpha class GSTs allowed the identification of three conserved residues (E137, K141, and S142) at α-helix 5 (H5). A motif-directed redesign of the human glutathione transferase A1-1 (hGSTA1-1) was performed through site-directed mutagenesis at these sites, creating two single- and two double-point mutants (E137H, K141H, K141H/S142H, and E137H/K141H). The results showed that all the enzyme variants displayed enhanced catalytic activity compared to the wild-type enzyme hGSTA1-1, while the double mutant hGSTA1-K141H/S142H also showed improved thermal stability. X-ray crystallographic analysis revealed the molecular basis of the effects of double mutations on enzyme stability and catalysis. The biochemical and structural analysis presented here will contribute to a deeper understanding of the structure and function of alpha class GSTs.

BioMetAll: Identifying Metal-Binding Sites in Proteins from Backbone Preorganization

With a large amount of research dedicated to decoding how metallic species bind to proteins, in silico methods are interesting allies for experimental procedures. To date, computational predictors mostly work by identifying the best possible sequence or structural match of the target protein with metal-binding templates. These approaches are fundamentally focused on the first coordination sphere of the metal. Here, we present the BioMetAll predictor that is based on a different postulate: the formation of a potential metal-binding site is related to the geometric organization of the protein backbone. We first report the set of convenient geometric descriptors of the backbone needed for the algorithm and their parameterization from a statistical analysis. Then, the successful benchmark of BioMetAll on a set of more than 90 metal-binding X-ray structures is presented. Because BioMetAll allows structural predictions regardless of the exact geometry of the side chains, it appears extremely valuable for systems whose structures (either experimental or theoretical) are not optimal for metal-binding sites. We report here its application on three different challenging cases: (i) the modulation of metal-binding sites during conformational transition in human serum albumin, (ii) the identification of possible routes of metal migration in hemocyanins, and (iii) the prediction of mutations to generate convenient metal-binding sites for de novo biocatalysts. This study shows that BioMetAll offers a versatile platform for numerous fields of research at the interface between inorganic chemistry and biology and allows to highlight the role of the preorganization of the protein backbone as a marker for metal binding. BioMetAll is an open-source application available at https://github.com/insilichem/biometall.

Molecular Modeling for Artificial Metalloenzyme Design and Optimization

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

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

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

Peptidylglycine monooxygenase activity of monomeric species of growth hormone

C-terminal α-amidation of peptides is an important event in the course of pro-hormone and neuropeptide processing; it is a modification that contributes to the biological activity and stability of about 25 peptides in neural and endocrine systems. This laboratory has shown that bovine growth hormone (bGH) also has a catalytic function, i.e. peptidylglycine monooxygenase activity, which is the first step in the alpha-amidation of glycine-extended peptides. We report here that the peptidylglycine monooxygenase activity of monomeric bovine pituitary GH, in the presence of ascorbate, is stimulated by combination with oligomeric forms of bGH one of which is a hetero-oligomer with metallothionein. Three species of recombinant monomeric GH (bovine, human and chicken) also catalyze this monooxygenase reaction. Tetrahydrobiopterin also functions as a reductant - with a significantly greater turnover than achieved with ascorbate. These findings clarify the role of GH in peptidylglycine monooxygenation and provide an explanation for earlier observations that peptide amidation is not totally obliterated in the absence of ascorbate, in cultured pituitary cells or in vivo. The evolution of bifunctional GH is also discussed, as are some of the significances of the peptidylglycine monooxygenase activity of human GH in relation to peptides such as oxytocin, glucagon-like peptide-1 and peptide PYY.

Histidine-based copper tetrapeptides as enantioselective catalysts for aldol reactions

Copper(ii)-peptides are widely used as industrial catalysts such as in the aerobic oxidation of organic molecules, formation of new C–H bonds and in the azide–alkyne cycloaddition reaction. The length of peptides and the effect of adding copper metal into peptides were questioned in their field of applications. Five novel histidine-based tetrapeptides with the sequences HAAD (P1), HAFD (P2), HAVD (P3), AGHD (P4) and PGHD (P5) were synthesized using the solid phase peptide scheme and analysed with high performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS) with percentage purities as high as 99.5%. All the peptides were positively charged (+1) and the molecular weight calculated from m/z values of MS results coincided with the theoretical molecular weight of the peptides. Copper(ii)-peptides derived from these peptides and copper(ii) acetate monohydrate (CuP1–CuP5) in a 1 : 2 ratio was synthesised, purified and characterised by ultraviolet-visible spectroscopy (UV-Vis), ultraviolet-fluorescence spectroscopy (fluorescence) and fourier transform infrared spectroscopy (FTIR), circular dichroism spectroscopy (CD) and optical rotation polarimetry. It provided the necessary information on the secondary structure and the successful binding of copper(ii) to the specific amino acids, hence leading to the putative geometry of copper(ii)-peptides and the difference in the chirality of amino acids, peptides and copper(ii)-peptides. The catalytic activities of the synthesised complexes were evaluated. CuP1 & CuP3 catalysed both the asymmetric aldol reactions with high enantioselectivity of p-nitrobenzaldehyde with cyclohexanone (% ee = 87.3 & 80.3, respectively) and of p-anisaldehyde with cyclohexanone (% ee = 95.5 & 90.9, respectively).

P5 with the sequence H₂N-PGHD-CONH.

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.

Design and engineering of artificial oxygen-activating metalloenzymes

Many efforts are being made in the design and engineering of metalloenzymes with catalytic properties fulfilling the needs of practical applications. Progress in this field has recently been accelerated by advances in computational, molecular and structural biology. This review article focuses on the recent examples of oxygen-activating metalloenzymes, developed through the strategies of de novo design, miniaturization processes and protein redesign. Considerable progress in these diverse design approaches has produced many metal-containing biocatalysts able to adopt the functions of native enzymes or even novel functions beyond those found in Nature.

Enzyme repurposing of a hydrolase as an emergent peroxidase upon metal binding

Adding a metal cofactor to a protein bearing a latent metal binding site endows the macromolecule with nascent catalytic activity.

As an alternative to Darwinian evolution relying on catalytic promiscuity, a protein may acquire auxiliary function upon metal binding, thus providing it with a novel catalytic machinery. Here we show that addition of cupric ions to a 6-phosphogluconolactonase 6-PGLac bearing a putative metal binding site leads to the emergence of peroxidase activity (k_cat 7.8 × 10^–2 s^–1, K_M 1.1 × 10^–5 M). Both X-ray crystallographic and EPR data of the copper-loaded enzyme Cu·6-PGLac reveal a bis-histidine coordination site, located within a shallow binding pocket capable of accommodating the o-dianisidine substrate.

Metal-binding promiscuity in artificial metalloenzyme design

This review presents recent examples of metal-binding promiscuity in protein scaffolds and highlights the effect of metal variation on catalytic functionality. Naturally evolved binding sites, as well as unnatural amino acids and cofactors can bind a diverse range of metals, including non-biological transition elements. Computational screening and rational design have been successfully used to create promiscuous binding-sites. Incorporation of non-native metals into proteins expands the catalytic range of transformations catalysed by enzymes and enhances their potential for application in chemicals synthesis.

Secondary structure preferences of mn (2+) binding sites in bacterial proteins

3D structures of proteins with coordinated Mn²⁺ ions from bacteria with low, average, and high genomic GC-content have been analyzed (149 PDB files were used). Major Mn²⁺ binders are aspartic acid (6.82% of Asp residues), histidine (14.76% of His residues), and glutamic acid (3.51% of Glu residues). We found out that the motif of secondary structure “beta strand-major binder-random coil” is overrepresented around all the three major Mn²⁺ binders. That motif may be followed by either alpha helix or beta strand. Beta strands near Mn²⁺ binding residues should be stable because they are enriched by such beta formers as valine and isoleucine, as well as by specific combinations of hydrophobic and hydrophilic amino acid residues characteristic to beta sheet. In the group of proteins from GC-rich bacteria glutamic acid residues situated in alpha helices frequently coordinate Mn²⁺ ions, probably, because of the decrease of Lys usage under the influence of mutational GC-pressure. On the other hand, the percentage of Mn²⁺ sites with at least one amino acid in the “beta strand-major binder-random coil” motif of secondary structure (77.88%) does not depend on genomic GC-content.

The copper(II) and zinc(II) coordination mode of HExxH and HxxEH motif in small peptides: the role of carboxylate location and hydrogen bonding network

Copper(II) and zinc(II) complexes with two hexapeptides encompassing HExxH and HxxEH motif were characterized by means of a combined experimental and theoretical approach. Parallel tempering and density functional theory (DFT) investigations show the presence of different hydrogen bonding networks between the copper(II) and zinc(II) complexes with the two peptides, suggesting a significant contribution of these non-covalent interactions to the stability constant values. The glutamate carboxylate group has a direct role in metal ion binding. The location of this amino acid along the sequence of the investigated peptides is critical to determine thermodynamic and spectroscopic features of the copper(II) complex species, whereas is less relevant in the zinc(II) complexes formation. Electrospray ionization mass spectrometry (ESI-MS) characterization of the zinc(II) complex species show that in the [ZnH-2L] two deprotonated amide nitrogen atoms are involved in the metal coordination environment, an uncommon behavior in zinc(II) complexes for multi-histidine ligands.

OpenStructure: an integrated software framework for computational structural biology

Research projects in structural biology increasingly rely on combinations of heterogeneous sources of information, e.g. evolutionary information from multiple sequence alignments, experimental evidence in the form of density maps and proximity constraints from proteomics experiments. The OpenStructure software framework, which allows the seamless integration of information of different origin, has previously been introduced. The software consists of C++ libraries which are fully accessible from the Python programming language. Additionally, the framework provides a sophisticated graphics module that interactively displays molecular structures and density maps in three dimensions. In this work, the latest developments in the OpenStructure framework are outlined. The extensive capabilities of the framework will be illustrated using short code examples that show how information from molecular-structure coordinates can be combined with sequence data and/or density maps. The framework has been released under the LGPL version 3 license and is available for download from http://www.openstructure.org.