MetalS(3), a database-mining tool for the identification of structurally similar metal sites

COLLAPSE: A representation learning framework for identification and characterization of protein structural sites

The identification and characterization of the structural sites which contribute to protein function are crucial for understanding biological mechanisms, evaluating disease risk, and developing targeted therapies. However, the quantity of known protein structures is rapidly outpacing our ability to functionally annotate them. Existing methods for function prediction either do not operate on local sites, suffer from high false positive or false negative rates, or require large site-specific training datasets, necessitating the development of new computational methods for annotating functional sites at scale. We present COLLAPSE (Compressed Latents Learned from Aligned Protein Structural Environments), a framework for learning deep representations of protein sites. COLLAPSE operates directly on the 3D positions of atoms surrounding a site and uses evolutionary relationships between homologous proteins as a self-supervision signal, enabling learned embeddings to implicitly capture structure-function relationships within each site. Our representations generalize across disparate tasks in a transfer learning context, achieving state-of-the-art performance on standardized benchmarks (protein-protein interactions and mutation stability) and on the prediction of functional sites from the Prosite database. We use COLLAPSE to search for similar sites across large protein datasets and to annotate proteins based on a database of known functional sites. These methods demonstrate that COLLAPSE is computationally efficient, tunable, and interpretable, providing a general-purpose platform for computational protein analysis.

Biological Effects of Human Exposure to Environmental Cadmium

Cadmium (Cd) is a toxic metal for the human organism and for all ecosystems. Cd is naturally found at low levels; however, higher amounts of Cd in the environment result from human activities as it spreads into the air and water in the form of micropollutants as a consequence of industrial processes, pollution, waste incineration, and electronic waste recycling. The human body has a limited ability to respond to Cd exposure since the metal does not undergo metabolic degradation into less toxic species and is only poorly excreted. The extremely long biological half-life of Cd essentially makes it a cumulative toxin; chronic exposure causes harmful effects from the metal stored in the organs. The present paper considers exposure and potential health concerns due to environmental cadmium. Exposure to Cd compounds is primarily associated with an elevated risk of lung, kidney, prostate, and pancreatic cancer. Cd has also been linked to cancers of the breast, urinary system, and bladder. The multiple mechanisms of Cd-induced carcinogenesis include oxidative stress with the inhibition of antioxidant enzymes, the promotion of lipid peroxidation, and interference with DNA repair systems. Cd²⁺ can also replace essential metal ions, including redox-active ones. A total of 12 cancer types associated with specific genes coding for the Cd-metalloproteome were identified in this work. In addition, we summarize the proper treatments of Cd poisoning, based on the use of selected Cd detoxifying agents and chelators, and the potential for preventive approaches to counteract its chronic exposure.

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.

Structure and activity of a thermally stable mutant of Acanthamoeba actophorin

Actophorin, which was recently tested for crystallization under microgravity on the International Space Station, was subjected to mutagenesis to identify a construct with improved biophysical properties that were expected to improve the extent of diffraction. First, 20 mutations, including one C-terminal deletion of three residues, were introduced individually into actophorin, resulting in modest increases in thermal stability of between +0.5°C and +2.2°C. All but two of the stabilizing mutants increased both the rates of severing F-actin filaments and of spontaneous polymerization of pyrenyl G-actin in vitro. When the individual mutations were combined into a single actophorin variant, Acto-2, the overall thermal stability was 22°C higher than that of wild-type actophorin. When an inactivating S2P mutation in Acto-2 was restored, Acto-2/P2S was more stable by 20°C but was notably more active than the wild-type protein. The inactivating S2P mutation reaffirms the importance that Ser2 plays in the F-actin-severing reaction. The crystal structure of Acto-2 was solved to 1.7 Å resolution in a monoclinic space group, a first for actophorin. Surprisingly, despite the increase in thermal stability, the extended β-turn region, which is intimately involved in interactions with F-actin, is disordered in one copy of Acto-2 in the asymmetric unit. These observations emphasize the complex interplay among protein thermal stability, function and dynamics.

Identifying metal binding amino acids based on backbone geometries as a tool for metalloprotein engineering

Metal cofactors within proteins perform a versatile set of essential cellular functions. In order to take advantage of the diverse functionality of metalloproteins, researchers have been working to design or modify metal binding sites in proteins to rationally tune the function or activity of the metal cofactor. This study has performed an analysis on the backbone atom geometries of metal-binding amino acids among 10 different metal binding sites within the entire protein data bank. A set of 13 geometric parameters (features) was identified that is capable of predicting the presence of a metal cofactor in the protein structure with overall accuracies of up to 97% given only the relative positions of their backbone atoms. The decision tree machine-learning algorithm used can quickly analyze an entire protein structure for the presence of sets of primary metal coordination spheres upon mutagenesis, independent of their original amino acid identities. The methodology was designed for application in the field of metalloprotein engineering. A cluster analysis using the data set was also performed and demonstrated that the features chosen are useful for identifying clusters of structurally similar metal-binding sites.

DeepCys: Structure-based multiple cysteine function prediction method trained on deep neural network: Case study on domains of unknown functions belonging to COX2 domains

Cysteine (Cys) is the most reactive amino acid participating in a wide range of biological functions. In-silico predictions complement the experiments to meet the need of functional characterization. Multiple Cys function prediction algorithm is scarce, in contrast to specific function prediction algorithms. Here we present a deep neural network-based multiple Cys function prediction, available on web-server (DeepCys) (https://deepcys.herokuapp.com/). DeepCys model was trained and tested on two independent datasets curated from protein crystal structures. This prediction method requires three inputs, namely, PDB identifier (ID), chain ID and residue ID for a given Cys and outputs the probabilities of four cysteine functions, namely, disulphide, metal-binding, thioether and sulphenylation and predicts the most probable Cys function. The algorithm exploits the local and global protein properties, like, sequence and secondary structure motifs, buried fractions, microenvironments and protein/enzyme class. DeepCys outperformed most of the multiple and specific Cys function algorithms. This method can predict maximum number of cysteine functions. Moreover, for the first time, explicitly predicts thioether function. This tool was used to elucidate the cysteine functions on domains of unknown functions belonging to cytochrome C oxidase subunit-II like transmembrane domains. Apart from the web-server, a standalone program is also available on GitHub (https://github.com/vam-sin/deepcys).

Leveraging computational genomics to understand the molecular basis of metal homeostasis

Genome-based data is helping to reveal the diverse strategies plants and algae use to maintain metal homeostasis. In addition to acquisition, distribution and storage of metals, acclimating to feast or famine can involve a wealth of genes that we are just now starting to understand. The fast-paced acquisition of genome-based data, however, is far outpacing our ability to experimentally characterize protein function. Computational genomic approaches are needed to fill the gap between what is known and unknown. To avoid misconstruing bioinformatically derived data, which is the root cause of the inaccurate functional annotations that plague databases, functional inferences from diverse sources and contextualization of that evidence with a robust understanding of protein family evolution is needed. Phylogenomic- and comparative-genomic-based studies can aid in the interpretation of experimental data or provide a spark for the discovery of a new function. These analyses not only lead to novel insight into a target protein's function but can generate thought-provoking insights across protein families.

ProteinsPlus: interactive analysis of protein-ligand binding interfaces

Due to the increasing amount of publicly available protein structures searching, enriching and investigating these data still poses a challenging task. The ProteinsPlus web service (https://proteins.plus) offers a broad range of tools addressing these challenges. The web interface to the tool collection focusing on protein–ligand interactions has been geared towards easy and intuitive access to a large variety of functionality for life scientists. Since our last publication, the ProteinsPlus web service has been extended by additional services as well as it has undergone substantial infrastructural improvements. A keyword search functionality was added on the start page of ProteinsPlus enabling users to work on structures without knowing their PDB code. The tool collection has been augmented by three tools: StructureProfiler validates ligands and active sites using selection criteria of well-established protein–ligand benchmark data sets, WarPP places water molecules in the ligand binding sites of a protein, and METALizer calculates, predicts and scores coordination geometries of metal ions based on surrounding complex atoms. Additionally, all tools provided by ProteinsPlus are available through a REST service enabling the automated integration in structure processing and modeling pipelines.

Crystallographic characterization of a tri-Asp metal-binding site at the three-fold symmetry axis of LarE

Detailed crystallographic characterization of a tri-aspartate metal-binding site previously identified on the three-fold symmetry axis of a hexameric enzyme, LarE from Lactobacillus plantarum, was conducted. By screening an array of monovalent, divalent, and trivalent metal ions, we demonstrated that this metal binding site stoichiometrically binds Ca²⁺, Mn²⁺, Fe²⁺/Fe³⁺, Co²⁺, Ni²⁺, Cu²⁺, Zn²⁺, and Cd²⁺, but not monovalent metal ions, Cr³⁺, Mg²⁺, Y³⁺, Sr²⁺ or Ba²⁺. Extensive database searches resulted in only 13 similar metal binding sites in other proteins, indicative of the rareness of tri-aspartate architectures, which allows for engineering such a selective multivalent metal ion binding site into target macromolecules for structural and biophysical characterization.

MetalPDB in 2018: a database of metal sites in biological macromolecular structures

MetalPDB (http://metalweb.cerm.unifi.it/) is a database providing information on metal-binding sites detected in the three-dimensional (3D) structures of biological macromolecules. MetalPDB represents such sites as 3D templates, called Minimal Functional Sites (MFSs), which describe the local environment around the metal(s) independently of the larger context of the macromolecular structure. The 2018 update of MetalPDB includes new contents and tools. A major extension is the inclusion of proteins whose structures do not contain metal ions although their sequences potentially contain a known MFS. In addition, MetalPDB now provides extensive statistical analyses addressing several aspects of general metal usage within the PDB, across protein families and in catalysis. Users can also query MetalPDB to extract statistical information on structural aspects associated with individual metals, such as preferred coordination geometries or aminoacidic environment. A further major improvement is the functional annotation of MFSs; the annotation is manually performed via a password-protected annotator interface. At present, ∼50% of all MFSs have such a functional annotation. Other noteworthy improvements are bulk query functionality, through the upload of a list of PDB identifiers, and ftp access to MetalPDB contents, allowing users to carry out in-depth analyses on their own computational infrastructure.

A Histidine Switch for Zn-Induced Aggregation of γ-Crystallins Reveals a Metal-Bridging Mechanism That Is Relevant to Cataract Disease

Cataract disease results from non-amyloid aggregation of eye lens proteins and is the leading cause of blindness in the world. Zinc concentrations in cataractous lenses are increased significantly relative to those in healthy lenses. It was recently reported that Zn(II) ions induce the aggregation of one of the more abundant proteins in the core of the lens, human γD-crystallin. Here, the mechanism of Zn-induced aggregation has been revealed through a comparative study of three homologous human lens γ-crystallins and a combination of spectroscopic, electron microscopy, and site-directed mutagenesis studies. This work reveals that a single His residue acts as a "switch" for the Zn-induced non-amyloid aggregation of human γ-crystallins. Aggregation can be reversed by a chelating agent, revealing a metal-bridging mechanism. This study sheds light on an aberrant Zn-crystallin interaction that promotes aggregation, a process that is relevant to cataract disease.

Structure, function and evolution of the hemerythrin-like domain superfamily

Hemerythrin-like proteins have generally been studied for their ability to reversibly bind oxygen through their binuclear nonheme iron centers. However, in recent years, it has become increasingly evident that some members of the hemerythrin-like superfamily also participate in many other biological processes. For instance, the binuclear nonheme iron site of YtfE, a hemerythrin-like protein involved in the repair of iron centers in Escherichia coli, catalyzes the reduction of nitric oxide to nitrous oxide, and the human F-box/LRR-repeat protein 5, which contains a hemerythrin-like domain, is involved in intracellular iron homeostasis. Furthermore, structural data on hemerythrin-like domains from two proteins of unknown function, PF0695 from Pyrococcus furiosus and NMB1532 from Neisseria meningitidis, show that the cation-binding sites, typical of hemerythrin, can be absent or be occupied by metal ions other than iron. To systematically investigate this functional and structural diversity of the hemerythrin-like superfamily, we have collected hemerythrin-like sequences from a database comprising fully sequenced proteomes and generated a cluster map based on their all-against-all pairwise sequence similarity. Our results show that the hemerythrin-like superfamily comprises a large number of protein families which can be classified into three broad groups on the basis of their cation-coordinating residues: (a) signal-transduction and oxygen-carrier hemerythrins (H-HxxxE-HxxxH-HxxxxD); (b) hemerythrin-like (H-HxxxE-H-HxxxE); and, (c) metazoan F-box proteins (H-HExxE-H-HxxxE). Interestingly, all but two hemerythrin-like families exhibit internal sequence and structural symmetry, suggesting that a duplication event may have led to the origin of the hemerythrin domain.

To what extent do structural changes in catalytic metal sites affect enzyme function?

About half of known enzymatic reactions involve metals. Enzymes belonging to the same superfamily often evolve to catalyze different reactions on the same structural scaffold. The work presented here investigates how functional differentiation, within superfamilies that contain metalloenzymes, relates to structural changes at the catalytic metal site. In general, when the catalytic metal site is unchanged across the enzymes of a superfamily, the functional differentiation within the superfamily tends to be low and the mechanism conserved. Conversely, all types of structural changes in the metal binding site are observed for superfamilies with high functional differentiation. Overall, the catalytic role of the metal ions appears to be one of the most conserved features of the enzyme mechanism within metalloenzyme superfamilies. In particular, when the catalytic role of the metal ion does not involve a redox reaction (i.e. there is no exchange of electrons with the substrate), this role is almost always maintained even when the site undergoes significant structural changes. In these enzymes, functional diversification is most often associated with modifications in the surrounding protein matrix, which has changed so much that the enzyme chemistry is significantly altered. On the other hand, in more than 50% of the examples where the metal has a redox role in catalysis, changes at the metal site modify its catalytic role. Further, we find that there are no examples in our dataset where metal sites with a redox role are lost during evolution.

SYNOPSIS

In this paper we investigate how functional diversity within superfamilies of metalloenzymes relates to structural changes at the catalytic metal site. Evolution tends to strictly conserve the metal site. When changes occur, they do not modify the catalytic role of non-redox metals whereas they affect the role of redox-active metals.

Structural database resources for biological macromolecules

This Briefing reviews the widely used, currently active, up-to-date databases derived from the worldwide Protein Data Bank (PDB) to facilitate browsing, finding and exploring its entries. These databases contain visualization and analysis tools tailored to specific kinds of molecules and interactions, often including also complex metrics precomputed by experts or external programs, and connections to sequence and functional annotation databases. Importantly, updates of most of these databases involves steps of curation and error checks based on specific expertise about the subject molecules or interactions, and removal of sequence redundancy, both leading to better data sets for mining studies compared with the full list of raw PDB entries. The article presents the databases in groups such as those aimed to facilitate browsing through PDB entries, their molecules and their general information, those built to link protein structure with sequence and dynamics, those specific for transmembrane proteins, nucleic acids, interactions of biomacromolecules with each other and with small molecules or metal ions, and those concerning specific structural features or specific protein families. A few webservers directly connected to active databases, and a few databases that have been discontinued but would be important to have back, are also briefly commented on. Along the Briefing, sample cases where these databases have been used to aid structural studies or advance our knowledge about biological macromolecules are referenced. A few specific examples are also given where using these databases is easier and more informative than using raw PDB data.

Computational approaches for de novo design and redesign of metal-binding sites on proteins

Metal ions play pivotal roles in protein structure, function and stability. The functional and structural diversity of proteins in nature expanded with the incorporation of metal ions or clusters in proteins. Approximately one-third of these proteins in the databases contain metal ions. Many biological and chemical processes in nature involve metal ion-binding proteins, aka metalloproteins. Many cellular reactions that underpin life require metalloproteins. Most of the remarkable, complex chemical transformations are catalysed by metalloenzymes. Realization of the importance of metal-binding sites in a variety of cellular events led to the advancement of various computational methods for their prediction and characterization. Furthermore, as structural and functional knowledgebase about metalloproteins is expanding with advances in computational and experimental fields, the focus of the research is now shifting towards de novo design and redesign of metalloproteins to extend nature’s own diversity beyond its limits. In this review, we will focus on the computational toolbox for prediction of metal ion-binding sites, de novo metalloprotein design and redesign. We will also give examples of tailor-made artificial metalloproteins designed with the computational toolbox.

Contemplating a role for titanium in organisms

Titanium is the ninth most abundant element in the Earth's crust and some organisms sequester it avidly, though no essential biological role has yet been recognized. This Minireview addresses how the properties of titanium, especially in an oxic aqueous environment, might make a biological role difficult to recognize. It further considers how new -omic technologies might overcome the limitations of the past and help to reveal a specific role for this metal. While studies with well established model organisms have their rightful place, organisms that are known avid binders or sequesterers of titanium should be promising places to investigate a biological role.

Structural and functional characterization of a calcium-activated cation channel from Tsukamurella paurometabola

The selectivity filter is an essential functional element of K⁺ channels that is highly conserved both in terms of its primary sequence and its three-dimensional structure. Here, we investigate the properties of an ion channel from the Gram-positive bacterium Tsukamurella paurometabola with a selectivity filter formed by an uncommon proline-rich sequence. Electrophysiological recordings show that it is a non-selective cation channel and that its activity depends on Ca²⁺ concentration. In the crystal structure, the selectivity filter adopts a novel conformation with Ca²⁺ ions bound within the filter near the pore helix where they are coordinated by backbone oxygen atoms, a recurrent motif found in multiple proteins. The binding of Ca²⁺ ion in the selectivity filter controls the widening of the pore as shown in crystal structures and in molecular dynamics simulations. The structural, functional and computational data provide a characterization of this calcium-gated cationic channel.

Tetrameric cationic channels specificity is determined by the sequence and structural conformation of their selectivity filter. Here, the authors show that a cationic channel from Tsukamurella paurometabola is non-selective due to a Ca²⁺-binding motif within its unusual proline-rich filter.

Minimal Functional Sites in Metalloproteins and Their Usage in Structural Bioinformatics

Metal ions play a functional role in numerous biochemical processes and cellular pathways. Indeed, about 40% of all enzymes of known 3D structure require a metal ion to be able to perform catalysis. The interactions of the metals with the macromolecular framework determine their chemical properties and reactivity. The relevant interactions involve both the coordination sphere of the metal ion and the more distant interactions of the so-called second sphere, i.e., the non-bonded interactions between the macromolecule and the residues coordinating the metal (metal ligands). The metal ligands and the residues in their close spatial proximity define what we call a minimal functional site (MFS). MFSs can be automatically extracted from the 3D structures of metal-binding biological macromolecules deposited in the Protein Data Bank (PDB). They are 3D templates that describe the local environment around a metal ion or metal cofactor and do not depend on the overall macromolecular structure. MFSs provide a different view on metal-binding proteins and nucleic acids, completely focused on the metal. Here we present different protocols and tools based upon the concept of MFS to obtain deeper insight into the structural and functional properties of metal-binding macromolecules. We also show that structure conservation of MFSs in metalloproteins relates to local sequence similarity more strongly than to overall protein similarity.

Hidden relationships between metalloproteins unveiled by structural comparison of their metal sites

Metalloproteins account for a substantial fraction of all proteins. They incorporate metal atoms, which are required for their structure and/or function. Here we describe a new computational protocol to systematically compare and classify metal-binding sites on the basis of their structural similarity. These sites are extracted from the MetalPDB database of minimal functional sites (MFSs) in metal-binding biological macromolecules. Structural similarity is measured by the scoring function of the available MetalS2 program. Hierarchical clustering was used to organize MFSs into clusters, for each of which a representative MFS was identified. The comparison of all representative MFSs provided a thorough structure-based classification of the sites analyzed. As examples, the application of the proposed computational protocol to all heme-binding proteins and zinc-binding proteins of known structure highlighted the existence of structural subtypes, validated known evolutionary links and shed new light on the occurrence of similar sites in systems at different evolutionary distances. The present approach thus makes available an innovative viewpoint on metalloproteins, where the functionally crucial metal sites effectively lead the discovery of structural and functional relationships in a largely protein-independent manner.

Structural basis for misfolding in myocilin-associated glaucoma

Olfactomedin (OLF) domain-containing proteins play roles in fundamental cellular processes and have been implicated in disorders ranging from glaucoma, cancers and inflammatory bowel disorder, to attention deficit disorder and childhood obesity. We solved crystal structures of the OLF domain of myocilin (myoc-OLF), the best studied such domain to date. Mutations in myoc-OLF are causative in the autosomal dominant inherited form of the prevalent ocular disorder glaucoma. The structures reveal a new addition to the small family of five-bladed β-propellers. Propellers are most well known for their ability to act as hubs for protein-protein interactions, a function that seems most likely for myoc-OLF, but they can also act as enzymes. A calcium ion, sodium ion and glycerol molecule were identified within a central hydrophilic cavity that is accessible via movements of surface loop residues. By mapping familial glaucoma-associated lesions onto the myoc-OLF structure, three regions sensitive to aggregation have been identified, with direct applicability to differentiating between neutral and disease-causing non-synonymous mutations documented in the human population worldwide. Evolutionary analysis mapped onto the myoc-OLF structure reveals conserved and divergent regions for possible overlapping and distinctive functional protein-protein or protein-ligand interactions across the broader OLF domain family. While deciphering the specific normal biological functions, ligands and binding partners for OLF domains will likely continue to be a challenging long-term experimental pursuit, atomic detail structural knowledge of myoc-OLF is a valuable guide for understanding the implications of glaucoma-associated mutations and will help focus future studies of this biomedically important domain family.