InterMetalDB: A Database and Browser of Intermolecular Metal Binding Sites in Macromolecules with Structural Information

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.

Metalloproteins and metalloproteomics in health and disease

Metalloproteins represents more than one third of human proteome, with huge variation in physiological functions and pathological implications, depending on the metal/metals involved and tissue context. Their functions range from catalysis, bioenergetics, redox, to DNA repair, cell proliferation, signaling, transport of vital elements, and immunity. The human metalloproteomic studies revealed that many families of metalloproteins along with individual metalloproteins are dysregulated under several clinical conditions. Also, several sorts of interaction between redox- active or redox- inert metalloproteins are observed in health and disease. Metalloproteins profiling shows distinct alterations in neurodegenerative diseases, cancer, inflammation, infection, diabetes mellitus, among other diseases. This makes metalloproteins -either individually or as families- a promising target for several therapeutic approaches. Inhibitors and activators of metalloenzymes, metal chelators, along with artificial metalloproteins could be versatile in diagnosis and treatment of several diseases, in addition to other biomedical and industrial applications.

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/.

Hunting down zinc(II)-binding sites in proteins with distance matrices

MOTIVATION

In recent years, high-throughput sequencing technologies have made available the genome sequences of a huge variety of organisms. However, the functional annotation of the encoded proteins often still relies on low-throughput and costly experimental studies. Bioinformatics approaches offer a promising alternative to accelerate this process. In this work, we focus on the binding of zinc(II) ions, which is needed for 5%-10% of any organism's proteins to achieve their physiologically relevant form.

RESULTS

To implement a predictor of zinc(II)-binding sites in the 3D structures of proteins, we used a neural network, followed by a filter of the network output against the local structure of all known sites. The latter was implemented as a function comparing the distance matrices of the Cα and Cβ atoms of the sites. We called the resulting tool Master of Metals (MOM). The structural models for the entire proteome of an organism generated by AlphaFold can be used as input to our tool in order to achieve annotation at the whole organism level within a few hours. To demonstrate this, we applied MOM to the yeast proteome, obtaining a precision of about 76%, based on data for homologous proteins.

AVAILABILITY AND IMPLEMENTATION

Master of Metals has been implemented in Python and is available at https://github.com/cerm-cirmmp/Master-of-metals.

Zn(II) to Ag(I) Swap in Rad50 Zinc Hook Domain Leads to Interprotein Complex Disruption through the Formation of Highly Stable Agx(Cys)y Cores

The widespread application of silver nanoparticles in medicinal and daily life products increases the exposure to Ag(I) of thiol-rich biological environments, which help control the cellular metallome. A displacement of native metal cofactors from their cognate protein sites is a known phenomenon for carcinogenic and otherwise toxic metal ions. Here, we examined the interaction of Ag(I) with the peptide model of the interprotein zinc hook (Hk) domain of Rad50 protein from Pyrococcus furiosus, a key player in DNA double-strand break (DSB) repair. The binding of Ag(I) to 14 and 45 amino acid long peptide models of apo- and Zn(Hk)₂ was experimentally investigated by UV-vis spectroscopy, circular dichroism, isothermal titration calorimetry, and mass spectrometry. The Ag(I) binding to the Hk domain was found to disrupt its structure via the replacement of the structural Zn(II) ion by multinuclear Ag_x(Cys)_y complexes. The ITC analysis indicated that the formed Ag(I)-Hk species are at least 5 orders of magnitude stronger than the otherwise extremely stable native Zn(Hk)₂ domain. These results show that Ag(I) ions may easily disrupt the interprotein zinc binding sites as an element of silver toxicity at the cellular level.

Metalloallostery and Transition Metal Signaling: Bioinorganic Copper Chemistry Beyond Active Sites

Transition metal chemistry is essential to life, where metal binding to DNA, RNA, and proteins underpins all facets of the central dogma of biology. In this context, metals in proteins are typically studied as static active site cofactors. However, the emergence of transition metal signaling, where mobile metal pools can transiently bind to biological targets beyond active sites, is expanding this conventional view of bioinorganic chemistry. This Minireview focuses on the concept of metalloallostery, using copper as a canonical example of how metals can regulate protein function by binding to remote allosteric sites (e.g., exosites). We summarize advances in and prospects for the field, including imaging dynamic transition metal signaling pools, allosteric inhibition or activation of protein targets by metal binding, and metal-dependent signaling pathways that underlie nutrient vulnerabilities in diseases spanning obesity, fatty liver disease, cancer, and neurodegeneration.

Bioinformatics and computational analyses of kidney stone modulatory proteins lead to solid experimental evidence and therapeutic potential

In recent biomedical research, bioinformatics and computational analyses have played essential roles for examining experimental findings and database information. Several bioinformatic tools have been developed and made publicly available for analyzing protein sequence, structure, functional motif/domain, and interactions network. Such properties are very helpful to define biochemical and functional roles of the protein(s) of interest. During the past few decades, bioinformatics and computational biotechnology have been widely applied to kidney stone research. This review summarizes commonly used tools and evidence of bioinformatics and computational biotechnology applied to kidney stone disease (KSD) with special emphasis on analyses of the stone modulatory proteins that play critical roles in kidney stone formation. Such analyses lead to solid experimental evidence to demonstrate mechanisms underlying their stone modulatory activities. The findings obtained from such analyses may also lead to better understanding of KSD pathogenesis and to further development of new therapeutic and preventive strategies.

Metalloproteome of human-infective RNA viruses: a study towards understanding the role of metal ions in virology

Metalloproteins and metal-based inhibitors have been shown to effectively combat infectious diseases, particularly those caused by RNA viruses. In this study, a diverse set of bioinformatics methods was employed to identify metal-binding proteins of human RNA viruses. Seventy-three viral proteins with a high probability of being metal-binding proteins were identified. These proteins included 40 zinc-, 47 magnesium- and 14 manganese-binding proteins belonging to 29 viral species and eight significant viral families, including Coronaviridae, Flaviviridae and Retroviridae. Further functional characterization has revealed that these proteins play a critical role in several viral processes, including viral replication, fusion and host viral entry. They fall under the essential categories of viral proteins, including polymerase and protease enzymes. Magnesium ion is abundantly predicted to interact with these viral enzymes, followed by zinc. In addition, this study also examined the evolutionary aspects of predicted viral metalloproteins, offering essential insights into the metal utilization patterns among different viral species. The analysis indicates that the metal utilization patterns are conserved within the functional classes of the proteins. In conclusion, the findings of this study provide significant knowledge on viral metalloproteins that can serve as a valuable foundation for future research in this area.

An Extremely Stable Interprotein Tetrahedral Hg(Cys)4 Core Forms in the Zinc Hook Domain of Rad50 Protein at Physiological pH

In nature, thiolate-based systems are the primary targets of divalent mercury (Hg^II ) toxicity. The formation of Hg(Cys)_x cores in catalytic and structural protein centers mediates mercury's toxic effects and ultimately leads to cellular damage. Multiple studies have revealed distinct Hg^II -thiolate coordination preferences, among which linear Hg^II complexes are the most commonly observed in solution at physiological pH. Trigonal or tetrahedral geometries are formed at basic pH or in tight intraprotein Cys-rich metal sites. So far, no interprotein tetrahedral Hg^II complex formed at neutral pH has been reported. Rad50 protein is a part of the multiprotein MRN complex, a major player in DNA damage-repair processes. Its central region consists of a conserved CXXC motif that enables dimerization of two Rad50 molecules by coordinating Zn^II . Dimerized motifs form a unique interprotein zinc hook domain (Hk) that is critical for the biological activity of the MRN. Using a series of length-differentiated peptide models of the Pyrococcus furiosus zinc hook domain, we investigated its interaction with Hg^II . Using UV-Vis, CD, PAC, and ¹⁹⁹ Hg NMR spectroscopies as well as anisotropy decay, we discovered that all Rad50 fragments preferentially form homodimeric Hg(Hk)₂ species with a distorted tetrahedral HgS₄ coordination environment at physiological pH; this is the first example of an interprotein mercury site displaying tetrahedral geometry in solution. At higher Hg^II content, monomeric HgHk complexes with linear geometry are formed. The Hg(Cys)₄ core of Rad50 is extremely stable and does not compete with cyanides, NAC, or DTT. Applying ITC, we found that the stability constant of the Rad50 Hg(Hk)₂ complex is approximately three orders of magnitude higher than those of the strongest Hg^II complexes known to date.

Relations between Structure and Zn(II) Binding Affinity Shed Light on the Mechanisms of Rad50 Hook Domain Functioning and Its Phosphorylation

The metal binding at protein–protein interfaces is still uncharted territory in intermolecular interactions. To date, only a few protein complexes binding Zn(II) in an intermolecular manner have been deeply investigated. The most notable example of such interfaces is located in the highly conserved Rad50 protein, part of the Mre11-Rad50-Nbs1 (MRN) complex, where Zn(II) is required for homodimerization (Zn(Rad50)2). The high stability of Zn(Rad50)2 is conserved not only for the protein derived from the thermophilic archaeon Pyrococcus furiosus (logK12 = 20.95 for 130-amino-acid-long fragment), which was the first one studied, but also for the human paralog studied here (logK12 = 19.52 for a 183-amino-acid-long fragment). As we reported previously, the extremely high stability results from the metal-coupled folding process where particular Rad50 protein fragments play a critical role. The sequence–structure–stability analysis based on human Rad50 presented here separates the individual structural components that increase the stability of the complex, pointing to amino acid residues far away from the Zn(II) binding site as being largely responsible for the complex stabilization. The influence of the individual components is very well reflected by the previously published crystal structure of the human Rad50 zinc hook (PDB: 5GOX). In addition, we hereby report the effect of phosphorylation of the zinc hook domain, which exerts a destabilizing effect on the domain. This study identifies factors governing the stability of metal-mediated protein–protein interactions and illuminates their molecular basis.

The zinc proteome of SARS-CoV-2

Zinc is an essential element for human health. Among its many functions, zinc(II) modulates the immune response to infections and, at high concentrations or in the presence of ionophores, inhibits the replication of various RNA viruses. Structural biology studies on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) revealed that zinc(II) is the most common metal ion that binds to viral proteins. However, the number of zinc(II)-binding sites identified by experimental methods is far from exhaustive, as metal ions may be lost during protein purification protocols. To better define the zinc(II)-binding proteome of coronavirus, we leveraged the wealth of deposited structural data and state-of-the-art bioinformatics methods. Through this in silico approach, 15 experimental zinc(II) sites were identified and a further 22 were predicted in Spike, open reading frame (ORF)3a/d, ORF8, and several nonstructural proteins, highlighting an essential role of zinc(II) in viral replication. Furthermore, the structural relationships between viral and eukaryotic sites (typically zinc fingers) indicate that SARS-CoV-2 can compete with human proteins for zinc(II) binding. Given the double-edged effect of zinc(II) ions, both essential and toxic to coronavirus, only the complete elucidation of the structural and regulatory zinc(II)-binding sites can guide selective antiviral strategies based on zinc supplementation.

Structural Bioinformatics and Deep Learning of Metalloproteins: Recent Advances and Applications

All living organisms require metal ions for their energy production and metabolic and biosynthetic processes. Within cells, the metal ions involved in the formation of adducts interact with metabolites and macromolecules (proteins and nucleic acids). The proteins that require binding to one or more metal ions in order to be able to carry out their physiological function are called metalloproteins. About one third of all protein structures in the Protein Data Bank involve metalloproteins. Over the past few years there has been tremendous progress in the number of computational tools and techniques making use of 3D structural information to support the investigation of metalloproteins. This trend has been boosted by the successful applications of neural networks and machine/deep learning approaches in molecular and structural biology at large. In this review, we discuss recent advances in the development and availability of resources dealing with metalloproteins from a structure-based perspective. We start by addressing tools for the prediction of metal-binding sites (MBSs) using structural information on apo-proteins. Then, we provide an overview of the methods for and lessons learned from the structural comparison of MBSs in a fold-independent manner. We then move to describing databases of metalloprotein/MBS structures. Finally, we summarizing recent ML/DL applications enhancing the functional interpretation of metalloprotein structures.

The Role of the Metabolism of Zinc and Manganese Ions in Human Cancerogenesis

Metal ion homeostasis is fundamental for life. Specifically, transition metals iron, manganese and zinc play a pivotal role in mitochondrial metabolism and energy generation, anti-oxidation defense, transcriptional regulation and the immune response. The misregulation of expression or mutations in ion carriers and the corresponding changes in Mn²⁺ and Zn²⁺ levels suggest that these ions play a pivotal role in cancer progression. Moreover, coordinated changes in Mn²⁺ and Zn²⁺ ion carriers have been detected, suggesting that particular mechanisms influenced by both ions might be required for the growth of cancer cells, metastasis and immune evasion. Here, we present a review of zinc and manganese pathophysiology suggesting that these ions might cooperatively regulate cancerogenesis. Zn and Mn effects converge on mitochondria-induced apoptosis, transcriptional regulation and the cGAS-STING signaling pathway, mediating the immune response. Both Zn and Mn influence cancer progression and impact treatment efficacy in animal models and clinical trials. We predict that novel strategies targeting the regulation of both Zn and Mn in cancer will complement current therapeutic strategies.

A Comprehensive Review of Computation-Based Metal-Binding Prediction Approaches at the Residue Level

Clear evidence has shown that metal ions strongly connect and delicately tune the dynamic homeostasis in living bodies. They have been proved to be associated with protein structure, stability, regulation, and function. Even small changes in the concentration of metal ions can shift their effects from natural beneficial functions to harmful. This leads to degenerative diseases, malignant tumors, and cancers. Accurate characterizations and predictions of metalloproteins at the residue level promise informative clues to the investigation of intrinsic mechanisms of protein-metal ion interactions. Compared to biophysical or biochemical wet-lab technologies, computational methods provide open web interfaces of high-resolution databases and high-throughput predictors for efficient investigation of metal-binding residues. This review surveys and details 18 public databases of metal-protein binding. We collect a comprehensive set of 44 computation-based methods and classify them into four categories, namely, learning-, docking-, template-, and meta-based methods. We analyze the benchmark datasets, assessment criteria, feature construction, and algorithms. We also compare several methods on two benchmark testing datasets and include a discussion about currently publicly available predictive tools. Finally, we summarize the challenges and underlying limitations of the current studies and propose several prospective directions concerning the future development of the related databases and methods.

The Mechanism of Metal Homeostasis in Plants: A New View on the Synergistic Regulation Pathway of Membrane Proteins, Lipids and Metal Ions

Heavy metal stress (HMS) is one of the most destructive abiotic stresses which seriously affects the growth and development of plants. Recent studies have shown significant progress in understanding the molecular mechanisms underlying plant tolerance to HMS. In general, three core signals are involved in plants' responses to HMS; these are mitogen-activated protein kinase (MAPK), calcium, and hormonal (abscisic acid) signals. In addition to these signal components, other regulatory factors, such as microRNAs and membrane proteins, also play an important role in regulating HMS responses in plants. Membrane proteins interact with the highly complex and heterogeneous lipids in the plant cell environment. The function of membrane proteins is affected by the interactions between lipids and lipid-membrane proteins. Our review findings also indicate the possibility of membrane protein-lipid-metal ion interactions in regulating metal homeostasis in plant cells. In this review, we investigated the role of membrane proteins with specific substrate recognition in regulating cell metal homeostasis. The understanding of the possible interaction networks and upstream and downstream pathways is developed. In addition, possible interactions between membrane proteins, metal ions, and lipids are discussed to provide new ideas for studying metal homeostasis in plant cells.