MIPS: metal interactions in protein structures

Databases of ligand-binding pockets and protein-ligand interactions

Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket-finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.

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.

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.

MRPC (Missing Regions in Polypeptide Chains): a knowledgebase

Missing regions in protein crystal structures are those regions that cannot be resolved, mainly owing to poor electron density (if the three-dimensional structure was solved using X-ray crystallography). These missing regions are known to have high B factors and could represent loops with a possibility of being part of an active site of the protein molecule. Thus, they are likely to provide valuable information and play a crucial role in the design of inhibitors and drugs and in protein structure analysis. In view of this, an online database, Missing Regions in Polypeptide Chains (MRPC), has been developed which provides information about the missing regions in protein structures available in the Protein Data Bank. In addition, the new database has an option for users to obtain the above data for non-homologous protein structures (25 and 90%). A user-friendly graphical interface with various options has been incorporated, with a provision to view the three-dimensional structure of the protein along with the missing regions using JSmol. The MRPC database is updated regularly (currently once every three months) and can be accessed freely at the URL http://cluster.physics.iisc.ac.in/mrpc.

Development of METAL-ACTIVE SITE and ZINCCLUSTER tool to predict active site pockets

The advent of whole genome sequencing leads to increasing number of proteins with known amino acid sequences. Despite many efforts, the number of proteins with resolved three dimensional structures is still low. One of the challenging tasks the structural biologists face is the prediction of the interaction of metal ion with any protein for which the structure is unknown. Based on the information available in Protein Data Bank, a site (METALACTIVE INTERACTION) has been generated which displays information for significant high preferential and low-preferential combination of endogenous ligands for 49 metal ions. User can also gain information about the residues present in the first and second coordination sphere as it plays a major role in maintaining the structure and function of metalloproteins in biological system. In this paper, a novel computational tool (ZINCCLUSTER) is developed, which can predict the zinc metal binding sites of proteins even if only the primary sequence is known. The purpose of this tool is to predict the active site cluster of an uncharacterized protein based on its primary sequence or a 3D structure. The tool can predict amino acids interacting with a metal or vice versa. This tool is based on the occurrence of significant triplets and it is tested to have higher prediction accuracy when compared to that of other available techniques.

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.

Remnants of an Ancient Metabolism without Phosphate

Phosphate is essential for all living systems, serving as a building block of genetic and metabolic machinery. However, it is unclear how phosphate could have assumed these central roles on primordial Earth, given its poor geochemical accessibility. We used systems biology approaches to explore the alternative hypothesis that a protometabolism could have emerged prior to the incorporation of phosphate. Surprisingly, we identified a cryptic phosphate-independent core metabolism producible from simple prebiotic compounds. This network is predicted to support the biosynthesis of a broad category of key biomolecules. Its enrichment for enzymes utilizing iron-sulfur clusters, and the fact that thermodynamic bottlenecks are more readily overcome by thioester rather than phosphate couplings, suggest that this network may constitute a "metabolic fossil" of an early phosphate-free nonenzymatic biochemistry. Our results corroborate and expand previous proposals that a putative thioester-based metabolism could have predated the incorporation of phosphate and an RNA-based genetic system. PAPERCLIP.

Sodium and Potassium Interactions with Nucleic Acids

Metal ions are essential cofactors for the structure and functions of nucleic acids. Yet, the early discovery in the 70s of the crucial role of Mg(2+) in stabilizing tRNA structures has occulted for a long time the importance of monovalent cations. Renewed interest in these ions was brought in the late 90s by the discovery of specific potassium metal ions in the core of a group I intron. Their importance in nucleic acid folding and catalytic activity is now well established. However, detection of K(+) and Na(+) ions is notoriously problematic and the question about their specificity is recurrent. Here we review the different methods that can be used to detect K(+) and Na(+) ions in nucleic acid structures such as X-ray crystallography, nuclear magnetic resonance or molecular dynamics simulations. We also discuss specific versus non-specific binding to different structures through various examples.

Heterogeneous behavior of metalloproteins toward metal ion binding and selectivity: insights from molecular dynamics studies

About one-third of the existing proteins require metal ions as cofactors for their catalytic activities and structural complexities. While many of them bind only to a specific metal, others bind to multiple (different) metal ions. However, the exact mechanism of their metal preference has not been deduced to clarity. In this study, we used molecular dynamics (MD) simulations to investigate whether a cognate metal (bound to the structure) can be replaced with other similar metal ions. We have chosen seven different proteins (phospholipase A2, sucrose phosphatase, pyrazinamidase, cysteine dioxygenase (CDO), plastocyanin, monoclonal anti-CD4 antibody Q425, and synaptotagmin 1 C2B domain) bound to seven different divalent metal ions (Ca(2+), Mg(2+), Zn(2+), Fe(2+), Cu(2+), Ba(2+), and Sr(2+), respectively). In total, 49 MD simulations each of 50 ns were performed and each trajectory was analyzed independently. Results demonstrate that in some cases, cognate metal ions can be exchanged with similar metal ions. On the contrary, some proteins show binding affinity specifically to their cognate metal ions. Surprisingly, two proteins CDO and plastocyanin which are known to bind Fe(2+) and Cu(2+), respectively, do not exhibit binding affinity to any metal ion. Furthermore, the study reveals that in some cases, the active site topology remains rigid even without cognate metals, whereas, some require them for their active site stability. Thus, it will be interesting to experimentally verify the accuracy of these observations obtained computationally. Moreover, the study can help in designing novel active sites for proteins to sequester metal ions particularly of toxic nature.

Analyses of cobalt-ligand and potassium-ligand bond lengths in metalloproteins: trends and patterns

Cobalt and potassium are biologically important metal elements that are present in a large array of proteins. Cobalt is mostly found in vivo associated with a corrin ring, which represents the core of the vitamin B12 molecule. Potassium is the most abundant metal in the cytosol, and it plays a crucial role in maintaining membrane potential as well as correct protein function. Here, we report a thorough analysis of the geometric properties of cobalt and potassium coordination spheres that was performed with high resolution on a representative set of structures from the Protein Data Bank and complemented by quantum mechanical calculations realized at the DFT level of theory (B3LYP/ SDD) on mononuclear model systems. The results allowed us to draw interesting conclusions on the structural characteristics of both Co and K centers, and to evaluate the importance of effects such as their association energies and intrinsic thermodynamic stabilities. Overall, the results obtained provide useful data for enhancing the atomic models normally applied in theoretical and computational studies of Co or K proteins performed at the quantum mechanical level, and for developing molecular mechanical parameters for treating Co or K coordination spheres in molecular mechanics or molecular dynamics studies.

Does aluminium bind to histidine? An NMR investigation of amyloid β12 and amyloid β16 fragments

Aluminium and zinc are known to be the major triggering agents for aggregation of amyloid peptides leading to plaque formation in Alzheimer's disease. While zinc binding to histidine in Aβ (amyloid β) fragments has been implicated as responsible for aggregation, not much information is available on the interaction of aluminium with histidine. In the NMR study of the N-terminal Aβ fragments, DAEFRHDSGYEV (Aβ12) and DAEFRHDSGYEVHHQK (Aβ16) presented here, the interactions of the fragments with aluminium have been investigated. Significant chemical shifts were observed for few residues near the C-terminus when aluminium chloride was titrated with Aβ12 and Aβ16 peptides. Surprisingly, it is nonhistidine residues which seem to be involved in aluminium binding. Based on NMR constrained structure obtained by molecular modelling, aluminium-binding pockets in Aβ12 were around charged residues such as Asp, Glu. The results are discussed in terms of native structure propagation, and the relevance of histidine residues in the sequences for metal-binding interactions. We expect that the study of such short amyloid peptide fragments will not only provide clues for plaque formation in aggregated conditions but also facilitate design of potential drugs for these targets.

Mespeus--a database of metal interactions with proteins

Modeling and analogy are commonly used to identify the part that a metal may play in the structure or function of a new protein which has been recognized by structural genomics. Mespeus ( http://mespeus.bch.ed.ac.uk/MESPEUS_10/) lists metal protein interactions whose geometry has been experimentally determined and allows them to be visualized. This can contribute to the modeling process. The use of Mespeus is described with a series of examples.

Validation of metal-binding sites in macromolecular structures with the CheckMyMetal web server

Metals have vital roles in both the mechanism and architecture of biological macromolecules. Yet structures of metal-containing macromolecules in which metals are misidentified and/or suboptimally modeled are abundant in the Protein Data Bank (PDB). This shows the need for a diagnostic tool to identify and correct such modeling problems with metal-binding environments. The CheckMyMetal (CMM) web server (http://csgid.org/csgid/metal_sites/) is a sophisticated, user-friendly web-based method to evaluate metal-binding sites in macromolecular structures using parameters derived from 7,350 metal-binding sites observed in a benchmark data set of 2,304 high-resolution crystal structures. The protocol outlines how the CMM server can be used to detect geometric and other irregularities in the structures of metal-binding sites, as well as how it can alert researchers to potential errors in metal assignment. The protocol also gives practical guidelines for correcting problematic sites by modifying the metal-binding environment and/or redefining metal identity in the PDB file. Several examples where this has led to meaningful results are described in the ANTICIPATED RESULTS section. CMM was designed for a broad audience--biomedical researchers studying metal-containing proteins and nucleic acids--but it is equally well suited for structural biologists validating new structures during modeling or refinement. The CMM server takes the coordinates of a metal-containing macromolecule structure in the PDB format as input and responds within a few seconds for a typical protein structure with 2-5 metal sites and a few hundred amino acids.

Molecular basis for manganese sequestration by calprotectin and roles in the innate immune response to invading bacterial pathogens

The S100A8/S100A9 heterodimer calprotectin (CP) functions in the host response to pathogens through a mechanism termed "nutritional immunity." CP binds Mn(2+) and Zn(2+) with high affinity and starves bacteria of these essential nutrients. Combining biophysical, structural, and microbiological analysis, we identified the molecular basis of Mn(2+) sequestration. The asymmetry of the CP heterodimer creates a single Mn(2+)-binding site from six histidine residues, which distinguishes CP from all other Mn(2+)-binding proteins. Analysis of CP mutants with altered metal-binding properties revealed that, despite both Mn(2+) and Zn(2+) being essential metals, maximal growth inhibition of multiple bacterial pathogens requires Mn(2+) sequestration. These data establish the importance of Mn(2+) sequestration in defense against infection, explain the broad-spectrum antimicrobial activity of CP relative to other S100 proteins, and clarify the impact of metal depletion on the innate immune response to infection.

The processing of repetitive extragenic palindromes: the structure of a repetitive extragenic palindrome bound to its associated nuclease

Extragenic sequences in genomes, such as microRNA and CRISPR, are vital players in the cell. Repetitive extragenic palindromic sequences (REPs) are a class of extragenic sequences, which form nucleotide stem-loop structures. REPs are found in many bacterial species at a high copy number and are important in regulation of certain bacterial functions, such as Integration Host Factor recruitment and mRNA turnover. Although a new clade of putative transposases (RAYTs or TnpA_REP) is often associated with an increase in these repeats, it is not clear how these proteins might have directed amplification of REPs. We report here the structure to 2.6 Å of TnpA_REP from Escherichia coli MG1655 bound to a REP. Sequence analysis showed that TnpA_REP is highly related to the IS200/IS605 family, but in contrast to IS200/IS605 transposases, TnpA_REP is a monomer, is auto-inhibited and is active only in manganese. These features suggest that, relative to IS200/IS605 transposases, it has evolved a different mechanism for the movement of discrete segments of DNA and has been severely down-regulated, perhaps to prevent REPs from sweeping through genomes.

MetLigDB: a web-based database for the identification of chemical groups to design metalloprotein inhibitors

MetLigDB (http://silver.sejong.ac.kr/MetLigDB) is a publicly accessible web-based database through which the interactions between a variety of chelating groups and various central metal ions in the active site of metalloproteins can be explored in detail. Additional information can also be retrieved, including protein and inhibitor names, the amino acid residues coordinated to the central metal ion, and the binding affinity of the inhibitor for the target metalloprotein. Although many metalloproteins have been considered promising targets for drug discovery, it is difficult to discover new inhibitors because of the difficulty in designing a suitable chelating moiety to impair the catalytic activity of the central metal ion. Because both common and specific chelating groups can be identified for varying metal ions and the associated coordination environments, MetLigDB is expected to give users insight into designing new inhibitors of metalloproteins for drug discovery.