ZincBind-the database of zinc binding sites.
Ontology highlight
ABSTRACT:
SUBMITTER: Ireland SM
PROVIDER: S-EPMC6361820 | biostudies-literature | 2019 Jan
REPOSITORIES: biostudies-literature
Publications
ZincBind-the database of zinc binding sites.
Ireland Sam M SM Martin Andrew C R ACR
Database : the journal of biological databases and curation 20190101
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 e ...[more]
Similar Datasets
Project description:microRNAs (miRNAs) are an abundant class of small endogenous non-coding RNAs (ncRNAs) of ∼22 nucleotides (nts) in length. These small regulatory molecules are involved in diverse developmental, physiological and pathological processes. miRNAs target mRNAs (mRNAs) for translational repression and/or mRNA degradation. Predictions of miRNA binding sites facilitate experimental validation of miRNA targets. Models developed with data from CLIP studies have been used for predictions of miRNA binding sites in the whole transcriptomes of human, mouse and worm. The prediction results have been assembled into STarMirDB, a new database of miRNA binding sites available at http://sfold.wadsworth.org/starmirDB.php . STarMirDB can be searched by miRNAs or mRNAs separately or in combination. The search results are categorized into seed and seedless sites in 3' UTR, CDS and 5' UTR. For each predicted site, STarMirDB provides a comprehensive list of sequence, thermodynamic and target structural features that are known to influence miRNA: target interaction. A high resolution PDF diagram of the conformation of the miRNA:target hybrid is also available for visualization and publication. The results of a database search are available through both an interactive viewer and downloadable text files.
| S-EPMC4962797 | biostudies-literature
Project description:Metals play a variety of roles in biological processes, and hence their presence in a protein structure can yield vital functional information. Because the residues that coordinate a metal often undergo conformational changes upon binding, detection of binding sites based on simple geometric criteria in proteins without bound metal is difficult. However, aspects of the physicochemical environment around a metal binding site are often conserved even when this structural rearrangement occurs. We have developed a Bayesian classifier using known zinc binding sites as positive training examples and nonmetal binding regions that nonetheless contain residues frequently observed in zinc sites as negative training examples. In order to allow variation in the exact positions of atoms, we average a variety of biochemical and biophysical properties in six concentric spherical shells around the site of interest. At a specificity of 99.8%, this method achieves 75.5% sensitivity in unbound proteins at a positive predictive value of 73.6%. We also test its accuracy on predicted protein structures obtained by homology modeling using templates with 30%-50% sequence identity to the target sequences. At a specificity of 99.8%, we correctly identify at least one zinc binding site in 65.5% of modeled proteins. Thus, in many cases, our model is accurate enough to identify metal binding sites in proteins of unknown structure for which no high sequence identity homologs of known structure exist. Both the source code and a Web interface are available to the public at http://feature.stanford.edu/metals.
| S-EPMC2144590 | biostudies-literature
Project description:Background: Zinc binding proteins make up a significant proportion of the proteomes of most organisms and, within those proteins, zinc performs rôles in catalysis and structure stabilisation. Identifying the ability to bind zinc in a novel protein can offer insights into its functions and the mechanism by which it carries out those functions. Computational means of doing so are faster than spectroscopic means, allowing for searching at much greater speeds and scales, and thereby guiding complimentary experimental approaches. Typically, computational models of zinc binding predict zinc binding for individual residues rather than as a single binding site, and typically do not distinguish between different classes of binding site-missing crucial properties indicative of zinc binding. Methods: Previously, we created ZincBindDB, a continuously updated database of known zinc binding sites, categorised by family (the set of liganding residues). Here, we use this dataset to create ZincBindPredict, a set of machine learning methods to predict the most common zinc binding site families for both structure and sequence. Results: The models all achieve an MCC ≥ 0.88, recall ≥ 0.93 and precision ≥ 0.91 for the structural models (mean MCC = 0.97), while the sequence models have MCC ≥ 0.64, recall ≥ 0.80 and precision ≥ 0.83 (mean MCC = 0.87), with the models for binding sites containing four liganding residues performing much better than this. Conclusions: The predictors outperform competing zinc binding site predictors and are available online via a web interface and a GraphQL API.
| S-EPMC7918553 | biostudies-literature
Project description:Zinc is one of the essential transition metals in cells. Excess or lack of zinc is detrimental, and cells exploit highly sensitive zinc-binding regulators to achieve homeostasis. In this article, we present a crystal structure of active Zur from Streptomyces coelicolor with three zinc-binding sites (C-, M-, and D-sites). Mutations of the three sites differentially affected sporulation and transcription of target genes, such that C- and M-site mutations inhibited sporulation and derepressed all target genes examined, whereas D-site mutations did not affect sporulation and derepressed only a sensitive gene. Biochemical and spectroscopic analyses of representative metal site mutants revealed that the C-site serves a structural role, whereas the M- and D-sites regulate DNA-binding activity as an on-off switch and a fine-tuner, respectively. Consistent with differential effect of mutations on target genes, zinc chelation by TPEN derepressed some genes (znuA, rpmF2) more sensitively than others (rpmG2, SCO7682) in vivo. Similar pattern of TPEN-sensitivity was observed for Zur-DNA complexes formed on different promoters in vitro. The sensitive promoters bound Zur with lower affinity than the less sensitive ones. EDTA-treated apo-Zur gained its DNA binding activity at different concentrations of added zinc for the two promoter groups, corresponding to free zinc concentrations of 4.5×10(-16) M and 7.9×10(-16) M for the less sensitive and sensitive promoters, respectively. The graded expression of target genes is a clever outcome of subtly modulating Zur-DNA binding affinities in response to zinc availability. It enables bacteria to detect metal depletion with improved sensitivity and optimize gene-expression pattern.
| S-EPMC3064357 | biostudies-literature
Project description:Metal ions are essential for the folding of RNA into stable tertiary structures and for the catalytic activity of some RNA enzymes. To aid in the study of the roles of metal ions in RNA structural biology, we have created MeRNA (Metals in RNA), a comprehensive compilation of all metal binding sites identified in RNA 3D structures available from the PDB and Nucleic Acid Database. Currently, our database contains information relating to binding of 9764 metal ions corresponding to 23 distinct elements, in 256 RNA structures. The metal ion locations were confirmed and ligands characterized using original literature references. MeRNA includes eight manually identified metal-ion binding motifs, which are described in the literature. MeRNA is searchable by PDB identifier, metal ion, method of structure determination, resolution and R-values for X-ray structure and distance from metal to any RNA atom or to water. New structures with their respective binding motifs will be added to the database as they become available. The MeRNA database will further our understanding of the roles of metal ions in RNA folding and catalysis and have applications in structural and functional analysis, RNA design and engineering. The MeRNA database is accessible at http://merna.lbl.gov.
| S-EPMC1347421 | biostudies-literature
Project description:The nitric oxide synthase (NOS) dimer is stabilized by a Zn(2+) ion coordinated to four symmetry-related Cys residues exactly along the dimer 2-fold axis. Each of the two essential tetrahydrobiopterin (H4B) molecules in the dimer interacts directly with the heme, and each H4B molecule is ~15 Å from the Zn(2+). We have determined the crystal structures of the bovine endothelial NOS dimer oxygenase domain bound to three different pterin analogues, which reveal an intimate structural communication between the H4B and Zn(2+) sites. The binding of one of these compounds, 6-acetyl-2-amino-7,7-dimethyl-7,8-dihydro-4(3H)-pteridinone (1), to the pterin site and Zn(2+) binding are mutually exclusive. Compound 1 both directly and indirectly disrupts hydrogen bonding between key residues in the Zn(2+) binding motif, resulting in destabilization of the dimer and a complete disruption of the Zn(2+) site. Addition of excess Zn(2+) stabilizes the Zn(2+) site at the expense of weakened binding of 1. The unique structural features of 1 that disrupt the dimer interface are extra methyl groups that extend into the dimer interface and force a slight opening of the dimer, thus resulting in disruption of the Zn(2+) site. These results illustrate a very delicate balance of forces and structure at the dimer interface that must be maintained to properly form the Zn(2+), pterin, and substrate binding sites.
| S-EPMC4082377 | biostudies-literature
Project description:The geometrical properties of zinc binding sites in a dataset of high quality protein crystal structures deposited in the Protein Data Bank have been examined to identify important differences between zinc sites that are directly involved in catalysis and those that play a structural role. Coordination angles in the zinc primary coordination sphere are compared with ideal values for each coordination geometry, and zinc coordination distances are compared with those in small zinc complexes from the Cambridge Structural Database as a guide of expected trends. We find that distances and angles in the primary coordination sphere are in general close to the expected (or ideal) values. Deviations occur primarily for oxygen coordinating atoms and are found to be mainly due to H-bonding of the oxygen coordinating ligand to protein residues, bidentate binding arrangements, and multi-zinc sites. We find that H-bonding of oxygen containing residues (or water) to zinc bound histidines is almost universal in our dataset and defines the elec-His-Zn motif. Analysis of the stereochemistry shows that carboxyl elec-His-Zn motifs are geometrically rigid, while water elec-His-Zn motifs show the most geometrical variation. As catalytic motifs have a higher proportion of carboxyl elec atoms than structural motifs, they provide a more rigid framework for zinc binding. This is understood biologically, as a small distortion in the zinc position in an enzyme can have serious consequences on the enzymatic reaction. We also analyze the sequence pattern of the zinc ligands and residues that provide elecs, and identify conserved hydrophobic residues in the endopeptidases that also appear to contribute to stabilizing the catalytic zinc site. A zinc binding template in protein crystal structures is derived from these observations.
| S-EPMC2144076 | biostudies-other
Project description:The sc-PDB database (available at http://bioinfo-pharma.u-strasbg.fr/scPDB/) is a comprehensive and up-to-date selection of ligandable binding sites of the Protein Data Bank. Sites are defined from complexes between a protein and a pharmacological ligand. The database provides the all-atom description of the protein, its ligand, their binding site and their binding mode. Currently, the sc-PDB archive registers 9283 binding sites from 3678 unique proteins and 5608 unique ligands. The sc-PDB database was publicly launched in 2004 with the aim of providing structure files suitable for computational approaches to drug design, such as docking. During the last 10 years we have improved and standardized the processes for (i) identifying binding sites, (ii) correcting structures, (iii) annotating protein function and ligand properties and (iv) characterizing their binding mode. This paper presents the latest enhancements in the database, specifically pertaining to the representation of molecular interaction and to the similarity between ligand/protein binding patterns. The new website puts emphasis in pictorial analysis of data.
| S-EPMC4384012 | biostudies-literature
Project description:The influx of high-throughput data and the need for complex models to describe the interaction of prokaryotic transcription factors (TF) with their target sites pose new challenges for TF-binding site databases. CollecTF (http://collectf.umbc.edu) compiles data on experimentally validated, naturally occurring TF-binding sites across the Bacteria domain, placing a strong emphasis on the transparency of the curation process, the quality and availability of the stored data and fully customizable access to its records. CollecTF integrates multiple sources of data automatically and openly, allowing users to dynamically redefine binding motifs and their experimental support base. Data quality and currency are fostered in CollecTF by adopting a sustainable model that encourages direct author submissions in combination with in-house validation and curation of published literature. CollecTF entries are periodically submitted to NCBI for integration into RefSeq complete genome records as link-out features, maximizing the visibility of the data and enriching the annotation of RefSeq files with regulatory information. Seeking to facilitate comparative genomics and machine-learning analyses of regulatory interactions, in its initial release CollecTF provides domain-wide coverage of two TF families (LexA and Fur), as well as extensive representation for a clinically important bacterial family, the Vibrionaceae.
| S-EPMC3965012 | biostudies-literature
Project description:Location and properties of ligand binding sites provide important information to uncover protein functions and to direct structure-based drug design approaches. However, as binding site detection depends on the three-dimensional (3D) structural data of proteins, functional analysis based on protein ligand binding sites is formidable for proteins without structural information. Recent developments in protein structure prediction and the 3D structures built by AlphaFold provide an unprecedented opportunity for analyzing ligand binding sites in human proteins. Here, we constructed the CavitySpace database, the first pocket library for all the proteins in the human proteome, using a widely-applied ligand binding site detection program CAVITY. Our analysis showed that known ligand binding sites could be well recovered. We grouped the predicted binding sites according to their similarity which can be used in protein function prediction and drug repurposing studies. Novel binding sites in highly reliable predicted structure regions provide new opportunities for drug discovery. Our CavitySpace is freely available and provides a valuable tool for drug discovery and protein function studies.
| S-EPMC9312471 | biostudies-literature