MetalPDB: a database of metal sites in biological macromolecular structures

Structural basis of microcystinase activity for biodegrading microcystin-LR

Microcystinase (MlrA) catalyzes the first and most important biodegradation step of hepatotoxic microcystin-LR (MC-LR) produced and released from cyanobacterial cells, and the underlying catalytic mechanism is not completely understood yet. MlrA was postulated previously to be a metalloprotease with an active site of H²⁶⁰AIH²⁶³NE²⁶⁵, a variant of the common metal-binding motif of HEXXH. Through comparison with representative modes in HEXXH-containing metalloproteases, molecular dynamics simulation, homology modeling, and docking, the active sites of MlrA involved in the MC-LR biodegradation by Sphingomonas sp. USTB-05 were predicted. Site-directed mutants of MlrA were constructed for verification then. The results show that MlrA is likely not a metalloprotease, but a glutamate protease belonging to type II CAAX prenyl endopeptidases. Combined with the biodegradation of MC-LR by MlrA and its mutants, a complete enzymatic mechanism for MC-LR biodegradation by MlrA is proposed: Glu¹⁷² and His²⁰⁵ activate a water molecule facilitating a nucleophilic attack on the Adda-Arg peptide bond of MC-LR; Trp¹⁷⁶ and Trp²⁰¹ contact the carboxylate side chain of Glu¹⁷²and, by raising its pKa potentially, accelerate the reaction rates; His²⁶⁰ and Asn²⁶⁴ (located in the previous postulated active center of H²⁶⁰AIH²⁶³NE²⁶⁵) function as an oxyanion hole to stabilize the transition states. This study reveals the enzymatic mechanism of MlrA for catalyzing MC-LR in both the representative modes and the experiments of site-directed mutagenesis.

Catalytic Cycle of Neisseria meningitidis CMP-Sialic Acid Synthetase Illustrated by High-Resolution Protein Crystallography

Cytidine 5'-monophosphate (CMP)-sialic acid synthetase (CSS) is an essential enzyme involved in the biosynthesis of carbohydrates and glycoconjugates containing sialic acids, a class of α-keto acids that are generally terminal key recognition residues by many proteins that play important biological and pathological roles. The CSS from Neisseria meningitidis (NmCSS) has been commonly used with other enzymes such as sialic acid aldolase and/or sialyltransferase in synthesizing a diverse array of compounds containing sialic acid or its naturally occurring and non-natural derivatives. To better understand its catalytic mechanism and substrate promiscuity, four NmCSS crystal structures trapped at various stages of the catalytic cycle with bound substrates, substrate analogues, and products have been obtained and are presented here. These structures suggest a mechanism for an "open" and "closed" conformational transition that occurs as sialic acid binds to the NmCSS/cytidine-5'-triphosphate (CTP) complex. The closed conformation positions critical residues to help facilitate the nucleophilic attack of sialic acid C2-OH to the α-phosphate of CTP, which is also aided by two observed divalent cations. Product formation drives the active site opening, promoting the release of products.

Zinc binding proteome of a phytopathogen Xanthomonas translucens pv. undulosa

Xanthomonas translucens pv. undulosa (Xtu) is a proteobacteria which causes bacterial leaf streak (BLS) or bacterial chaff disease in wheat and barley. The constant competition for zinc (Zn) metal nutrients contributes significantly in plant-pathogen interactions. In this study, we have employed a systematic in silico approach to study the Zn-binding proteins of Xtu. From the whole proteome of Xtu, we have identified approximately 7.9% of proteins having Zn-binding sequence and structural motifs. Further, 115 proteins were found homologous to plant-pathogen interaction database. Among these 115 proteins, 11 were predicted as putative secretory proteins. The functional diversity in Zn-binding proteins was revealed by functional domain, gene ontology and subcellular localization analysis. The roles of Zn-binding proteins were found to be varied in the range from metabolism, proteolysis, protein biosynthesis, transport, cell signalling, protein folding, transcription regulation, DNA repair, response to oxidative stress, RNA processing, antimicrobial resistance, DNA replication and DNA integration. This study provides preliminary information on putative Zn-binding proteins of Xtu which may further help in designing new metal-based antimicrobial agents for controlling BLS and bacterial chaff infections on staple crops.

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.

Biophysical approaches for the study of metal-protein interactions

Protein-protein interactions play important roles for a variety of cell functions, often involving metal ions; in fact, metal-ion binding mediates and regulates the activity of a wide range of biomolecules. Enlightening all of the specific features of metal-protein and metal-mediated protein-protein interactions can be a very challenging task; a detailed knowledge of the thermodynamic and spectroscopic parameters and the structural changes of the protein is normally required. For this purpose, many experimental techniques are employed, embracing all fields of Analytical and Bioinorganic Chemistry. In addition, the use of peptide models, reproducing the primary sequence of the metal-binding sites, is also proved to be useful. In this paper, a review of the most useful techniques for studying ligand-protein interactions with a special emphasis on metal-protein interactions is provided, with a critical summary of their strengths and limitations.

Methylated Histidines Alter Tautomeric Preferences that Influence the Rates of Cu Nitrite Reductase Catalysis in Designed Peptides

Copper proteins have the capacity to serve as both redox active catalysts and purely electron transfer centers. A longstanding question in this field is how the function of histidine ligated Cu centers are modulated by δ vs ε-nitrogen ligation of the imidazole. Evaluating the impact of these coordination modes on structure and function by comparative analysis of deposited crystal structures is confounded by factors such as differing protein folds and disparate secondary coordination spheres that make direct comparison of these isomers difficult. Here, we present a series of de novo designed proteins using the noncanonical amino acids 1-methyl-histidine and 3-methyl-histidine to create Cu nitrite reductases where δ- or ε-nitrogen ligation is enforced by the opposite nitrogen's methylation as a means of directly comparing these two ligation states in the same protein fold. We find that ε-nitrogen ligation allows for a better nitrite reduction catalyst, displaying 2 orders of magnitude higher activity than the δ-nitrogen ligated construct. Methylation of the δ nitrogen, combined with a secondary sphere mutation we have previously published, has produced a new record for efficiency within a homogeneous aqueous system, improving by 1 order of magnitude the previously published most efficient construct. Furthermore, we have measured Michaelis-Menten kinetics on these highly active constructs, revealing that the remaining barriers to matching the catalytic efficiency ( kcat/ KM) of native Cu nitrite reductase involve both substrate binding ( KM) and catalysis ( kcat).

High-resolution archaellum structure reveals a conserved metal-binding site

Many archaea swim by means of archaella. While the archaellum is similar in function to its bacterial counterpart, its structure, composition, and evolution are fundamentally different. Archaella are related to archaeal and bacterial type IV pili. Despite recent advances, our understanding of molecular processes governing archaellum assembly and stability is still incomplete. Here, we determine the structures of Methanococcus archaella by X‐ray crystallography and cryo‐EM. The crystal structure of Methanocaldococcus jannaschii FlaB1 is the first and only crystal structure of any archaellin to date at a resolution of 1.5 Å, which is put into biological context by a cryo‐EM reconstruction from Methanococcus maripaludis archaella at 4 Å resolution created with helical single‐particle analysis. Our results indicate that the archaellum is predominantly composed of FlaB1. We identify N‐linked glycosylation by cryo‐EM and mass spectrometry. The crystal structure reveals a highly conserved metal‐binding site, which is validated by mass spectrometry and electron energy‐loss spectroscopy. We show in vitro that the metal‐binding site, which appears to be a widespread property of archaellin, is required for filament integrity.

Simple Coordination Geometry Descriptors Allow to Accurately Predict Metal-Binding Sites in Proteins

With more than a third of the genome encoding for metal-containing biomolecules, the in silico prediction of how metal ions bind to proteins is crucial in chemistry, biology, and medicine. To date, algorithms for metal-binding site prediction are mainly based on sequence analysis. Those methods have reached enough quality to predict the correct region of the protein and the coordinating residues involved in metal-binding, but they do not provide three-dimensional (3D) models. On the contrary, the prediction of accurate 3D models for protein-metal adducts by structural bioinformatics and molecular modeling techniques is still a challenge. Here, we present an update of our multipurpose molecular modeling suite, GaudiMM, to locate metal-binding sites in proteins. The approach is benchmarked on 105 X-ray structures with resolution lower than 2.0 Å. Results predict the correct binding site of the metal in the biological scaffold for all the entries in the data set. Generated 3D models of the protein-metal coordination complexes reach root-mean-square deviation values under 1.0 Å between calculated and experimental structures. The whole process is purely based on finding poses that satisfy metal-derived geometrical rules without needing sequence or fine electronic inputs. Additional post-optimizations, including receptor flexibility, have been tested and suggest that more extensive searches, required when the host structures present a low level of pre-organization, are also possible. With this new update, GaudiMM is now able to look for metal-binding sites in biological scaffolds and clearly shows how explicitly considering the geometric particularities of the first coordination sphere of the metal in a docking process provides excellent results.

Zinc regulates ERp44-dependent protein quality control in the early secretory pathway

Zinc ions (Zn²⁺) are imported into the early secretory pathway by Golgi-resident transporters, but their handling and functions are not fully understood. Here, we show that Zn²⁺ binds with high affinity to the pH-sensitive chaperone ERp44, modulating its localization and ability to retrieve clients like Ero1α and ERAP1 to the endoplasmic reticulum (ER). Silencing the Zn²⁺ transporters that uptake Zn²⁺ into the Golgi led to ERp44 dysfunction and increased secretion of Ero1α and ERAP1. High-resolution crystal structures of Zn²⁺-bound ERp44 reveal that Zn²⁺ binds to a conserved histidine-cluster. The consequent large displacements of the regulatory C-terminal tail expose the substrate-binding surface and RDEL motif, ensuring client capture and retrieval. ERp44 also forms Zn²⁺-bridged homodimers, which dissociate upon client binding. Histidine mutations in the Zn²⁺-binding sites compromise ERp44 activity and localization. Our findings reveal a role of Zn²⁺ as a key regulator of protein quality control at the ER-Golgi interface.

Zinc ions (Zn²⁺) are imported by Golgi-resident transporters but the function of zinc in the early secretory pathway has remained unknown. Here the authors find that Zn²⁺ regulates protein quality control in the early secretory pathway by demonstrating that the pH-sensitive chaperone ERp44 binds Zn²⁺ and solving the Zn²⁺-bound ERp44 structure.

ZincBind-the database of zinc binding sites

Zinc is one of the most important biologically active metals. Ten per cent of the human genome is thought to encode a zinc binding protein and its uses encompass catalysis, structural stability, gene expression and immunity. At present, there is no specific resource devoted to identifying and presenting all currently known zinc binding sites. Here we present ZincBind, a database of zinc binding sites and its web front-end. Using the structural data in the Protein Data Bank, ZincBind identifies every instance of zinc binding to a protein, identifies its binding site and clusters sites based on 90% sequence identity. There are currently 24 992 binding sites, clustered into 7489 unique sites. The data are available over the web where they can be browsed and downloaded, and via a REST API. ZincBind is regularly updated and will continue to be updated with new data and features.

The shielding effect of metal complexes on the binding affinities of ligands to metalloproteins

The contributions of metal–ligand interactions to the ligand binding affinities are largely reduced by the shielding effects of metal complexes.

A Model for Manganese interaction with Deinococcus radiodurans proteome network involved in ROS response and defense

A complex network of regulatory proteins takes part in the mechanism underlying the radioresistance of Deinoccocus radiodurans bacterium (DR). The interaction of Mn(II) ions with DR-proteins and peptides seems to be responsible for proteins protection from oxidative damage induced by Reactive Oxygen Species during irradiation. In the present work we describe a combined approach of bioinformatic strategies based on structural data and annotation to predict the Mn(II)-binding proteins encoded by the genome of DR and, in parallel, the same predictions for other bacteria were performed; the comparison revealed that, in most of the cases, the content of Mn(II)-binding proteins is significantly higher in radioresistant than in radiosensitive bacteria. Moreover, we report the in silico protein-protein interaction network of the putative Mn(II)-proteins, remodeled in order to enhance the knowledge about the impact of Mn-binding proteins in DR ability to protect also DNA from various damaging agents such as ionizing radiation, UV radiation and oxidative stress.

Design of metalloproteins and novel protein folds using variational autoencoders

The design of novel proteins has many applications but remains an attritional process with success in isolated cases. Meanwhile, deep learning technologies have exploded in popularity in recent years and are increasingly applicable to biology due to the rise in available data. We attempt to link protein design and deep learning by using variational autoencoders to generate protein sequences conditioned on desired properties. Potential copper and calcium binding sites are added to non-metal binding proteins without human intervention and compared to a hidden Markov model. In another use case, a grammar of protein structures is developed and used to produce sequences for a novel protein topology. One candidate structure is found to be stable by molecular dynamics simulation. The ability of our model to confine the vast search space of protein sequences and to scale easily has the potential to assist in a variety of protein design tasks.

SwitCCh: Metal-Site Design for Controlling the Assembly of a Coiled-Coil Homodimer

Conformational change of proteins in response to chemical or physical signals is the underlying principle of many regulatory and transport mechanisms in biological systems. The ability to design proteins the conformational state of which can be precisely and reversibly controlled would facilitate the development of molecular machines tailored for specific applications. Here we explore metal-binding site design to engineer a peptide-based conformational switch called SwitCCh that assembles into a homodimeric coiled-coil in response to the addition of Zn^II ions or low pH. Addition of Zn^II promoted formation of a parallel homodimer with an increase in thermal stability by more than 30 °C. The peptide could be reversibly cycled between the coiled-coil and random conformation. Furthermore, the SwitCCh peptide was orthogonal to the previously developed coiled-coil dimer set, indicating it could be used for regulated self-assembly of coiled-coil based nanostructures and materials.

Development of de Novo Copper Nitrite Reductases: Where We Are and Where We Need To Go

The development of redox-active metalloprotein catalysts is a challenging objective of de novo protein design. Within this Perspective we detail our efforts to create a redox-active Cu nitrite reductase (NiR) by incorporating Cu into the hydrophobic interior of well-defined three-stranded coiled coils (3SCCs). The scaffold contains three histidine residues that provide a layer of three nitrogen donors that mimic the type 2 catalytic site of NiR. We have found that this strategy successfully produces an active and stable CuNiR model that functions for over 1000 turnovers. Spectroscopic evidence indicates that the Cu(I) site has a lower coordination number in comparison to the enzyme, whereas the Cu(II) geometry may more faithfully reproduce the NiR type 2 center. Mutations at the helical interface successfully produce a hydrogen bond between an interfacial Glu residue and the Culigating His residue, which allows for the tuning of the redox potential over a 100 mV range. We successfully created constructs with as much as a 120-fold improvement from the original design by modifying the steric bulk above or below the Cu binding site. These systems are now the most active water-soluble and stable artificial NiR catalysts yet produced. Several avenues for improving the catalytic efficiency of later designs are detailed within this Perspective, including adjustment of their resting oxidation state, the use of asymmetric scaffolds to allow for single amino acid mutation within the second coordination sphere, and the design of hydrogen-bonding networks to tune residue orientation and electronics. Through these studies the TRI-H system has given insight into the difficulties that arise in creating a de novo redox active enzyme. Work to improve upon this model will provide strategies by which redox-active de novo enzymes may be tuned and detail how native enzymes accomplish catalytic efficiencies through proton gated redox catalysis.

In silico Study of Iron, Zinc and Copper Binding Proteins of Pseudomonas syringae pv. lapsa: Emphasis on Secreted Metalloproteins

The phytopathogenic bacteria, Pseudomonas syringae pv. lapsa (P. syringae pv. lapsa) infects the staple food crop wheat. Metalloproteins play important roles in plant-pathogen interactions. Hence, the present work is aimed to predict and analyze the iron (Fe), zinc (Zn), and copper (Cu) binding proteins of P. syringae pv. lapsa which help in its growth, adaptation, survival and pathogenicity. A total of 232 Fe, 307 Zn, and 38 Cu-binding proteins have been identified. The functional annotation, subcellular localization and gene ontology enriched network analysis revealed their role in wide range of biological activities of the phytopathogen. Among the identified metalloproteins, a total of 29 Fe-binding, 31 Zn-binding, and 5 Cu-binding proteins were found to be secreted in nature. These putative secreted metalloproteins may perform diverse cellular and biological functions ranging from transport, response to oxidative stress, proteolysis, antimicrobial resistance, metabolic processes, protein folding and DNA repair. The observations obtained here may provide initial information required to draft new schemes to control microbial infections of staple food crops and will further help in developing sustainable agriculture.

Assigning crystallographic electron densities with free energy calculations-The case of the fluoride channel Fluc

Approximately 90% of the structures in the Protein Data Bank (PDB) were obtained by X-ray crystallography or electron microscopy. Whereas the overall quality of structure is considered high, thanks to a wide range of tools for structure validation, uncertainties may arise from density maps of small molecules, such as organic ligands, ions or water, which are non-covalently bound to the biomolecules. Even with some experience and chemical intuition, the assignment of such disconnected electron densities is often far from obvious. In this study, we suggest the use of molecular dynamics (MD) simulations and free energy calculations, which are well-established computational methods, to aid in the assignment of ambiguous disconnected electron densities. Specifically, estimates of (i) relative binding affinities, for instance between an ion and water, (ii) absolute binding free energies, i.e., free energies for transferring a solute from bulk solvent to a binding site, and (iii) stability assessments during equilibrium simulations may reveal the most plausible assignments. We illustrate this strategy using the crystal structure of the fluoride specific channel (Fluc), which contains five disconnected electron densities previously interpreted as four fluoride and one sodium ion. The simulations support the assignment of the sodium ion. In contrast, calculations of relative and absolute binding free energies as well as stability assessments during free MD simulations suggest that four of the densities represent water molecules instead of fluoride. The assignment of water is compatible with the loss of these densities in the non-conductive F82I/F85I mutant of Fluc. We critically discuss the role of the ion force fields for the calculations presented here. Overall, these findings indicate that MD simulations and free energy calculations are helpful tools for modeling water and ions into crystallographic density maps.

IDPM: an online database for ion distribution in protein molecules

Background

Interactions between ions and proteins have been extensively studied, yet most of the studies focus on the ion binding site. The binding mechanism for many ion binding sites can be clearly described from high resolution structures. Although knowledge accumulated on a case-by-case basis is valuable, it is also important to study the ion-protein interaction statistically. From experimentally determined structures, it is possible to examine the ion distribution around each amino acid. Such distributions can reveal relation between ions and amino acids, so it is desirable to carry out a systematic survey of ‘ion-amino acid’ pairing interaction and share the information with a publicly available database.

Results

The survey in the Protein Data Bank (PDB) revealed that approximately 40% of molecules records contain at least one ion. To reduce the bias resulted from protein redundancy, the statistics were extracted from a non-redundant dataset by excluding the proteins with similar sequences. Based on the structures of protein molecules and the location of ions, the statistical distributions of ions around each proteinogenic amino acid type were investigated and further summarized in a database. To systematically quantify the interactions between ions and each amino acid, the positions of ions were mapped to the coordinate system centered at each neighboring amino acid. It was found that the distribution of ions follows the expected rules governed by the physicochemical interactions in general. Large variations were observed, reflecting the preference in ‘ion-amino acid’ interactions. The analysis program is written in the Python programming language. The statistical results and program are available from the online database: ion distribution in protein molecules (IDPM) at http://liulab.csrc.ac.cn/idpm/.

Conclusion

The spatial distribution of ions around amino acids is documented and analyzed. The statistics can be useful for identifying ion types for a given site in biomolecules, and can be potentially used in ion position prediction for given structures.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2110-9) contains supplementary material, which is available to authorized users.

Trace Elements and Healthcare: A Bioinformatics Perspective

Biological trace elements are essential for human health. Imbalance in trace element metabolism and homeostasis may play an important role in a variety of diseases and disorders. While the majority of previous researches focused on experimental verification of genes involved in trace element metabolism and those encoding trace element-dependent proteins, bioinformatics study on trace elements is relatively rare and still at the starting stage. This chapter offers an overview of recent progress in bioinformatics analyses of trace element utilization, metabolism, and function, especially comparative genomics of several important metals. The relationship between individual elements and several diseases based on recent large-scale systematic studies such as genome-wide association studies and case-control studies is discussed. Lastly, developments of ionomics and its recent application in human health are also introduced.

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.

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.

Prediction of zinc binding sites in proteins using sequence derived information

Zinc is one the most abundant catalytic cofactor and also an important structural component of a large number of metallo-proteins. Hence prediction of zinc metal binding sites in proteins can be a significant step in annotation of molecular function of a large number of proteins. Majority of existing methods for zinc-binding site predictions are based on a data-set of proteins, which has been compiled nearly a decade ago. Hence there is a need to develop zinc-binding site prediction system using the current updated data to include recently added proteins. Herein, we propose a support vector machine-based method, named as ZincBinder, for prediction of zinc metal-binding site in a protein using sequence profile information. The predictor was trained using fivefold cross validation approach and achieved 85.37% sensitivity with 86.20% specificity during training. Benchmarking on an independent non-redundant data-set, which was not used during training, showed better performance of ZincBinder vis-à-vis existing methods. Executable versions, source code, sample datasets, and usage instructions are available at http://proteininformatics.org/mkumar/znbinder/.

Shared gene-network signatures between the human heavy metal proteome and neurological disorders and cancer types

In this work, for the first time, the human heavy metal proteome was predicted.

The structure of urease inactivated by Ag(i): a new paradigm for enzyme inhibition by heavy metals

The molecular details of the inactivation of urease, a nickel-dependent virulence factor for human pathogens and negatively affecting the efficiency of soil nitrogen fertilization, are elucidated through the crystal structure of the enzyme complex with Ag(i).

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.

The Metal Drives the Chemistry: Dual Functions of Acireductone Dioxygenase

Acireductone dioxygenase (ARD) from the methionine salvage pathway (MSP) is a unique enzyme that exhibits dual chemistry determined solely by the identity of the divalent transition-metal ion (Fe²⁺ or Ni²⁺) in the active site. The Fe²⁺-containing isozyme catalyzes the on-pathway reaction using substrates 1,2-dihydroxy-3-keto-5-methylthiopent-1-ene (acireductone) and dioxygen to generate formate and the ketoacid precursor of methionine, 2-keto-4-methylthiobutyrate, whereas the Ni²⁺-containing isozyme catalyzes an off-pathway shunt with the same substrates, generating methylthiopropionate, carbon monoxide, and formate. The dual chemistry of ARD was originally discovered in the bacterium Klebsiella oxytoca, but it has recently been shown that mammalian ARD enzymes (mouse and human) are also capable of catalyzing metal-dependent dual chemistry in vitro. This is particularly interesting, since carbon monoxide, one of the products of off-pathway reaction, has been identified as an antiapoptotic molecule in mammals. In addition, several biochemical and genetic studies have indicated an inhibitory role of human ARD in cancer. This comprehensive review describes the biochemical and structural characterization of the ARD family, the proposed experimental and theoretical approaches to establishing mechanisms for the dual chemistry, insights into the mechanism based on comparison with structurally and functionally similar enzymes, and the applications of this research to the field of artificial metalloenzymes and synthetic biology.

Perspectives and expectations in structural bioinformatics of metalloproteins

Recent papers highlight the presence of large numbers of compressed angles in metal ion coordination geometries for metalloprotein entries in the worldwide Protein Data Bank, due mainly to multidentate coordination. The prevalence of these compressed angles has raised the controversial idea that significantly populated aberrant or even novel coordination geometries may exist. Some of these papers have undergone severe criticism, apparently due to views held that only canonical coordination geometries exist in significant numbers. While criticism of controversial ideas is warranted and to be expected, we believe that a line was crossed where unfair criticism was put forth to discredit an inconvenient result that compressed angles exist in large numbers, which does not support the dogmatic canonical coordination geometry view. We present a review of the major controversial results and their criticisms, pointing out both good suggestions that have been incorporated in new analyses, but also unfair criticism that was put forth to support a particular view. We also suggest that better science is enabled through: (i) a more collegial and collaborative approach in future critical reviews and (ii) the requirement for a description of methods and data including source code and visualizations that enables full reproducibility of results. Proteins 2017; 85:938-944. © 2016 Wiley Periodicals, Inc.

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.

Aberrant coordination geometries discovered in the most abundant metalloproteins

Metalloproteins bind and utilize metal ions for a variety of biological purposes. Due to the ubiquity of metalloprotein involvement throughout these processes across all domains of life, how proteins coordinate metal ions for different biochemical functions is of great relevance to understanding the implementation of these biological processes. Toward these ends, we have improved our methodology for structurally and functionally characterizing metal binding sites in metalloproteins. Our new ligand detection method is statistically much more robust, producing estimated false positive and false negative rates of ∼0.11% and ∼1.2%, respectively. Additional improvements expand both the range of metal ions and their coordination number that can be effectively analyzed. Also, the inclusion of additional quality control filters has significantly improved structure-function Spearman correlations as demonstrated by rho values greater than 0.90 for several metal coordination analyses and even one rho value above 0.95. Also, improvements in bond-length distributions have revealed bond-length modes specific to chemical functional groups involved in multidentation. Using these improved methods, we analyzed all single metal ion binding sites with Zn, Mg, Ca, Fe, and Na ions in the wwPDB, producing statistically rigorous results supporting the existence of both a significant number of unexpected compressed angles and subsequent aberrant metal ion coordination geometries (CGs) within structurally known metalloproteins. By recognizing these aberrant CGs in our clustering analyses, high correlations are achieved between structural and functional descriptions of metal ion coordination. Moreover, distinct biochemical functions are associated with aberrant CGs versus nonaberrant CGs. Proteins 2017; 85:885-907. © 2016 Wiley Periodicals, Inc.

Cadmium(II) inhibition of human uracil-DNA glycosylase by catalytic water supplantation

Toxic metals are known to inhibit DNA repair but the underlying mechanisms of inhibition are still not fully understood. DNA repair enzymes such as human uracil-DNA glycosylase (hUNG) perform the initial step in the base excision repair (BER) pathway. In this work, we showed that cadmium [Cd(II)], a known human carcinogen, inhibited all activity of hUNG at 100 μM. Computational analyses based on 2 μs equilibrium, 1.6 μs steered molecular dynamics (SMD), and QM/MM MD determined that Cd(II) ions entered the enzyme active site and formed close contacts with both D145 and H148, effectively replacing the catalytic water normally found in this position. Geometry refinement by density functional theory (DFT) calculations showed that Cd(II) formed a tetrahedral structure with D145, P146, H148, and one water molecule. This work for the first time reports Cd(II) inhibition of hUNG which was due to replacement of the catalytic water by binding the active site D145 and H148 residues. Comparison of the proposed metal binding site to existing structural data showed that D145:H148 followed a general metal binding motif favored by Cd(II). The identified motif offered structural insights into metal inhibition of other DNA repair enzymes and glycosylases.

Validation and correction of Zn-CysxHisy complexes

Many crystal structures in the Protein Data Bank contain zinc ions in a geometrically distorted tetrahedral complex with four Cys and/or His ligands. A method is presented to automatically validate and correct these zinc complexes. Analysis of the corrected zinc complexes shows that the average Zn-Cys distances and Cys-Zn-Cys angles are a function of the number of cysteines and histidines involved. The observed trends can be used to develop more context-sensitive targets for model validation and refinement.

MetalPredator: a web server to predict iron-sulfur cluster binding proteomes

MOTIVATION

The prediction of the iron-sulfur proteome is highly desirable for biomedical and biological research but a freely available tool to predict iron-sulfur proteins has not been developed yet.

RESULTS

We developed a web server to predict iron-sulfur proteins from protein sequence(s). This tool, called MetalPredator, is able to process complete proteomes rapidly with high recall and precision.

AVAILABILITY AND IMPLEMENTATION

The web server is freely available at: http://metalweb.cerm.unifi.it/tools/metalpredator/

CONTACT

andreini@cerm.unifi.it

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

Data Mining of Macromolecular Structures

The use of macromolecular structures is widespread for a variety of applications, from teaching protein structure principles all the way to ligand optimization in drug development. Applying data mining techniques on these experimentally determined structures requires a highly uniform, standardized structural data source. The Protein Data Bank (PDB) has evolved over the years toward becoming the standard resource for macromolecular structures. However, the process selecting the data most suitable for specific applications is still very much based on personal preferences and understanding of the experimental techniques used to obtain these models. In this chapter, we will first explain the challenges with data standardization, annotation, and uniformity in the PDB entries determined by X-ray crystallography. We then discuss the specific effect that crystallographic data quality and model optimization methods have on structural models and how validation tools can be used to make informed choices. We also discuss specific advantages of using the PDB_REDO databank as a resource for structural data. Finally, we will provide guidelines on how to select the most suitable protein structure models for detailed analysis and how to select a set of structure models suitable for data mining.

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.

Microbial Metalloproteomics

Metalloproteomics is a rapidly developing field of science that involves the comprehensive analysis of all metal-containing or metal-binding proteins in a biological sample. The purpose of this review is to offer a comprehensive overview of the research involving approaches that can be categorized as inductively coupled plasma (ICP)-MS based methods, X-ray absorption/fluorescence, radionuclide based methods and bioinformatics. Important discoveries in microbial proteomics will be reviewed, as well as the outlook to new emerging approaches and research areas.

Quantifying Integrated Proteomic Responses to Iron Stress in the Globally Important Marine Diazotroph Trichodesmium

Trichodesmium is a biogeochemically important marine cyanobacterium, responsible for a significant proportion of the annual 'new' nitrogen introduced into the global ocean. These non-heterocystous filamentous diazotrophs employ a potentially unique strategy of near-concurrent nitrogen fixation and oxygenic photosynthesis, potentially burdening Trichodesmium with a particularly high iron requirement due to the iron-binding proteins involved in these processes. Iron availability may therefore have a significant influence on the biogeography of Trichodesmium. Previous investigations of molecular responses to iron stress in this keystone marine microbe have largely been targeted. Here a holistic approach was taken using a label-free quantitative proteomics technique (MSE) to reveal a sophisticated multi-faceted proteomic response of Trichodesmium erythraeum IMS101 to iron stress. Increased abundances of proteins known to be involved in acclimation to iron stress and proteins known or predicted to be involved in iron uptake were observed, alongside decreases in the abundances of iron-binding proteins involved in photosynthesis and nitrogen fixation. Preferential loss of proteins with a high iron content contributed to overall reductions of 55-60% in estimated proteomic iron requirements. Changes in the abundances of iron-binding proteins also suggested the potential importance of alternate photosynthetic pathways as Trichodesmium reallocates the limiting resource under iron stress. Trichodesmium therefore displays a significant and integrated proteomic response to iron availability that likely contributes to the ecological success of this species in the ocean.

Crystal Structures of Mycobacterium tuberculosis CysQ, with Substrate and Products Bound

In many organisms, 3'-phosphoadenosine 5'-phosphate (PAP) is a product of two reactions in the sulfur activation pathway. The sulfurylation of biomolecules, catalyzed by sulfotransferases, uses 3'-phosphoadenosine 5'-phosphosulfate (PAPS) as a sulfate donor, producing the sulfated biomolecule and PAP product. Additionally, the first step in sulfate reduction for many bacteria and fungi reduces the sulfate moiety of PAPS, producing PAP and sulfite, which is subsequently reduced to sulfide. PAP is removed by the phosphatase activity of CysQ, a 3',5'-bisphosphate nucleotidase, yielding AMP and phosphate. Because excess PAP alters the equilibrium of the sulfur pathway and inhibits sulfotransferases, PAP concentrations can affect the levels of sulfur-containing metabolites. Therefore, CysQ, a divalent cation metal-dependent phosphatase, is a major regulator of this pathway. CysQ (Rv2131c) from Mycobacterium tuberculosis (Mtb) was successfully expressed, purified, and crystallized in a variety of ligand-bound states. Here we report six crystal structures of Mtb CysQ, including a ligand-free structure, a lithium-inhibited state with substrate PAP bound, and a product-bound complex with AMP, phosphate, and three Mg(2+) ions bound. Comparison of these structures together with homologues of the superfamily has provided insight into substrate specificity, metal coordination, and catalytic mechanism.

Metal binding spectrum and model structure of the Bacillus anthracis virulence determinant MntA

The potentially lethal human pathogen Bacillus anthracis expresses a putative metal import system, MntBCA, which belongs to the large family of ABC transporters. MntBCA is essential for virulence of Bacillus anthracis: deletion of MntA, the system's substrate binding protein, yields a completely non-virulent strain. Here we determined the metal binding spectrum of MntA. In contrast to what can be inferred from growth complementation studies we find no evidence that MntA binds Fe(2+) or Fe(3+). Rather, MntA binds a variety of other metal ions, including Mn(2+), Zn(2+), Cd(2+), Co(2+), and Ni(2+) with affinities ranging from 10(-6) to 10(-8) M. Binding of Zn(2+) and Co(2+) have a pronounced thermo-stabilizing effect on MntA, with Mn(2+) having a milder effect. The thermodynamic stability of MntA, competition experiments, and metal binding and release experiments all suggest that Mn(2+) is the metal that is likely transported by MntBCA and is therefore the limiting factor for virulence of Bacillus anthracis. A homology-model of MntA shows a single, highly conserved metal binding site, with four residues that participate in metal coordination: two histidines, a glutamate, and an aspartate. The metals bind to this site in a mutually exclusive manner, yet surprisingly, mutational analysis shows that for proper coordination each metal requires a different subset of these four residues. ConSurf evolutionary analysis and structural comparison of MntA and its homologues suggest that substrate binding proteins (SBPs) of metal ions use a pair of highly conserved prolines to interact with their cognate ABC transporters. This proline pair is found exclusively in ABC import systems of metal ions.

The crystal structure of Helicobacter pylori HP1029 highlights the functional diversity of the sialic acid-related DUF386 family

The proteins of the YhcH/YjgK/YiaL (DUF386) family have been implicated in the bacterial metabolism of host-derived sialic acids and biofilm formation, although their precise biochemical function remains enigmatic. We present here the crystal structure of protein HP1029 from Helicobacter pylori. The protein is a homodimer, in which each monomer comprises a molecular core formed by 12 antiparallel β-strands arranged in two β-sheets flanked by helices. The sandwich formed by the sheets assumes the shape of a funnel opened at one end, with a zinc ion present at the bottom of the funnel. The crystal structure unequivocally shows that HP1029 belongs to the DUF386 family. Although no bioinformatics evidence has been found for sialic acid catabolism in H. pylori, the genomic context of HP1029 in Helicobacter and related organisms suggests a possible role in the metabolism of bacterial surface saccharides, such as pseudaminic acid and its derivatives.

A less-biased analysis of metalloproteins reveals novel zinc coordination geometries

Zinc metalloproteins are involved in many biological processes and play crucial biochemical roles across all domains of life. Local structure around the zinc ion, especially the coordination geometry (CG), is dictated by the protein sequence and is often directly related to the function of the protein. Current methodologies in characterizing zinc metalloproteins' CG consider only previously reported CG models based mainly on nonbiological chemical context. Exceptions to these canonical CG models are either misclassified or discarded as “outliers.” Thus, we developed a less‐biased method that directly handles potential exceptions without pre‐assuming any CG model. Our study shows that numerous exceptions could actually be further classified and that new CG models are needed to characterize them. Also, these new CG models are cross‐validated by strong correlation between independent structural and functional annotation distance metrics, which is partially lost if these new CGs models are ignored. Furthermore, these new CG models exhibit functional propensities distinct from the canonical CG models. Proteins 2015; 83:1470–1487. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

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.