The images generated in modern IC laboratories are created with high-quality standard (1,024 × 1,024 pixels and 10–12 bits/pixel) enabling cardiologists to perform interventions in the best conditions. But these images are in most of the cases archived in a basic quality standard (512 × 512 pixels and 8 bits/pixel). The purpose of this work is to complete the research developed in a previous paper and analyze the influence of the matrix size and the bit depth reduction on the image quality acquired on a polymethylmethacrylate (PMMA) phantom with a test object. The variation in contrast-to-noise ratio (CNR) and high contrast spatial resolution (HCSR) were investigated when the matrix size and the bit depth were independently modified for different phantom thicknesses. These two image quality parameters did not suffer noticeable alterations under bits depth reduction from 10 to 8 bits. Such a result seems to imply that bits depth reduction could be used to reduce file sizes with a suitable algorithm and without losing perceptible image quality information. But when the matrix size was reduced from 1,024 × 1,024 to 512 × 512 pixels, a reduction from 17% to 25% in HCSR was noticed when changing phantom thickness, and an increase of 27% in CNR was observed. These findings should be taken into account and it would be wise to conduct further investigations in the field of clinical images.
Image quality; Test object; Matrix size; Bits depth; Image metrics; Cardiology
Motivation: Computational characterization of ligand-binding sites in proteins provides preliminary information for functional annotation, protein design and ligand optimization. SiteComp implements binding site analysis for comparison of binding sites, evaluation of residue contribution to binding sites and identification of sub-sites with distinct molecular interaction properties.
Availability and implementation: The SiteComp server and tutorials are freely available at http://sitecomp.sanchezlab.org
Supplementary data are available at Bioinformatics online.
Structural genomics projects have revealed structures for a large number of proteins of unknown function. Understanding the interactions between these proteins and their ligands would provide an initial step in their functional characterization. Binding site identification methods are a fast and cost-effective way to facilitate the characterization of functionally important protein regions. In this review we describe our recently developed methods for binding site identification in the context of existing methods. The advantage of energy-based approaches is emphasized, since they provide flexibility in the identification and characterization of different types of binding sites.
Binding site; Function; Interaction; Ligand; Prediction; Structure
PHD (plant homeodomain) zinc fingers are structurally conserved modules found in proteins that modify chromatin as well as mediate molecular interactions in gene transcription. The original discovery of their role in gene transcription is attributed to the recognition of lysine-methylated histone H3. Recent studies show that PHD fingers have a sophisticated histone sequence reading capacity that is modulated by the interplay between different histone modifications. These studies underscore the functional versatility of PHD fingers as epigenome readers that control gene expression through molecular recruitment of multi-protein complexes of chromatin regulators and transcription factors. Moreover, they reinforce the concept that evolutionary changes in amino acids surrounding ligand binding sites on a conserved structural fold impart great functional diversity upon this family of proteins.
In the absence of experimental structures, comparative modeling continues to be the chosen method for retrieving structural information of target proteins. However, models lack the accuracy of experimental structures. Alignment error and structural divergence (between target and template) influence model accuracy the most. Here, we examine the potential additional impact of backbone geometry, as our previous studies have suggested that the structural class (all-α, αβ, all-β) of proteins may influence the accuracy of their models. In the twilight zone (sequence identity ≤ 30%) and at a similar level of target-template divergence, model accuracy of proteins does indeed follow the trend all-α > αβ > all-β. This is mainly a result of the alignment accuracy following the same trend (all-α > αβ > all-β) with backbone geometry playing only a minor role. Differences in the diversity of sequences belonging to different structural classes leads to the observed accuracy differences thus enabling a priori accuracy estimates of alignments/models in a class-dependent manner. This study provides a systematic description and quantification of structural class-dependent effect in comparative modeling. The study also suggests datasets for large-scale sequence/structure analyses should have equal representation of different structural classes to avoid class-dependent bias.
Homology Modeling; Model Accuracy; Sequence Alignment; Alignment Accuracy; Information Content; Secondary Structure
Summary: SiteHound uses Molecular Interaction Fields (MIFs) produced by EasyMIFs to identify protein structure regions that show a high propensity for interaction with ligands. The type of binding site identified depends on the probe atom used in the MIF calculation. The input to EasyMIFs is a PDB file of a protein structure; the output MIF serves as input to SiteHound, which in turn produces a list of putative binding sites. Extensive testing of SiteHound for the detection of binding sites for drug-like molecules and phosphorylated ligands has been carried out.
Availability: EasyMIFs and SiteHound executables for Linux, Mac OS X, and MS Windows operating systems are freely available for download from http://sitehound.sanchezlab.org/download.html.
Contact: firstname.lastname@example.org or email@example.com
Supplementary information: Supplementary data are available at Bioinformatics online.
Urinary tract infection (UTI) remains one of the main complications after kidney transplantation and it has serious consequences.
Fifty-two patients with kidney transplantation were evaluated for UTI at 3-145 days (mean 40.0 days) after surgery.. Forty-two received a graft from a live donor and 10 from a deceased donor. There were 22 female and 30 male patients, aged 11-47 years. Microscopic examinations, leukocyte esterase stick, and urinary culture were performed every third day and weekly after hospitalization. A positive culture was consider when patients presented bacterial counts up to 105 counts.
UTI developed in 19/52 (37%) patients at 3-75 days (mean 19.5 days after transplantation. Recurrent infection was observed in 7/52 (13.4%) patients at days 17-65. UTI was more frequent in patients who received deceased grafts compared with live grafts (7/10, 70% vs. 12/42, 28%; p < 0.007). Female patients were more susceptible than male (11/22, 50% vs. 8/22, 36.35%; p < 0.042). Five-year survival rate was 94.5% (49/52 patients). Kidney Graft exit update is 47/52 (90.2%), and there were no significant differences between graft rejection and UTI (p = 0.2518). Isolated bacteria were Escherichia coli (31.5%), Candida albicans (21.0%) and Enterococcus spp. (10.5%), followed by Pseudomonas aeruginosa, Klebsiella pneumoniae, Morganella morganii, Enterobacter cloacae and Micrococcus spp. Secondary infections were produced by (7/19, 36.8%). Enterococcus spp. (57%), E. coli (28%) and Micrococcus spp. (14.2%). Antibiotic resistance was 22% for ciprofloxacin and 33% for ampicillin. Therapeutic alternatives were aztreonam, trimethoprim-sulfamethoxazole, netilmicin and fosfomycin.
Surveillance of UTI for the first 3 months is a good option for improving quality of life of kidney transplantation patients and the exit of graft function especially for female patients and those receiving deceased grafts. Antibiograms provided a good therapeutic alternative to patients who presented with UTIs after receiving a kidney allograft.
The acetylation of histone lysine is central to providing the dynamic regulation of chromatin-based gene transcription. The bromodomain (BRD), which is the conserved structural module in chromatin-associated proteins and histone acetyltranferases, is the sole protein domain known to recognize acetyl-lysine residues on proteins. Structural analyses of the recognition of lysine-acetylated peptides derived from histones and cellular proteins by BRDs have provided new insights into the differences between and unifying features of the selectivity that BRDs exhibit in binding biological ligands. Recent research has highlighted the importance of BRD/acetyl-lysine binding in orchestrating molecular interactions in chromatin biology and regulating gene transcription. These studies suggest that modulating BRD/acetyl-lysine interactions with small molecules may provide new opportunities for the control of gene expression in human health and disease.
Acetyl-lysine recognition; bromodomain; gene transcription; lysine acetylation
The recent availability in the literature of new crystal structures of inactive G-protein coupled receptors (GPCRs) prompted us to study the extent to which these crystal structures constitute an advantage over the former prototypic rhodopsin template for homology modeling of the transmembrane (TM) region of human class A GPCRs. Our results suggest that better templates than those currently available are required by the majority of these GPCRs to generate homology models that are accurate enough for simple virtual screening aimed at computer-aided drug discovery. Thus, we investigated: 1) which class A GPCRs would have the highest impact as potential templates for homology modeling of other GPCRs, if their structures were solved; and 2) the extent to which multiple-template homology modeling (using all currently available GPCR crystal structures) provides an improvement over single-template homology modeling, as evaluated by the accuracy of rigid protein-flexible ligand docking on these models.
The use of predicted binding sites (binding sites calculated from the protein structure alone) is evaluated here as a tool to focus the docking of small molecule ligands into protein structures, simulating cases where the real binding sites are unknown. The resulting approach consists of a few independent docking runs carried out on small boxes, centered on the predicted binding sites, as opposed to one larger blind docking run that covers the complete protein structure. The focused and blind approaches were compared using a set of 77 known protein-ligand complexes and 19 ligand-free structures. The focused approach is shown to: (1) identify the correct binding site more frequently than blind docking; (2) produce more accurate docking poses for the ligand; (3) require less computational time. Additionally, the results show that very few real binding sites are missed in spite of focusing on only 3 predicted binding sites per target protein. Overall the results indicate that, by improving the sampling in regions that are likely to correspond to binding sites, the focused docking approach increases accuracy and efficiency of protein ligand docking for those cases where the ligand-binding site is unknown. This is especially relevant in applications such as reverse virtual screening and structure-based functional annotation of proteins.
docking protocol; binding site discovery; reverse virtual screening; AutoDock; Astex Diverse Set
It has been shown that molecular interactions between site-specific chemical modifications such as acetylation and methylation on DNA-packing histones and conserved structural modules present in transcriptional proteins are closely associated with chromatin structural changes and gene activation. Unlike methyl-lysine that can interact with different protein modules including chromodomains, Tudor and MBT domains, as well as PHD fingers, acetyl-lysine (Kac) is known thus far to be recognized only by bromodomains. While histone lysine acetylation plays a crucial role in regulation of chromatin-mediated gene transcription, a high degree of sequence variation of the acetyl-lysine binding site in the bromodomains has limited our understanding of histone binding selectivity of the bromodomain family. Here, we report a systematic family-wide analysis of 14 yeast bromodomains binding to 32 lysine-acetylated peptides derived from known major acetylation sites in four core histones that are conserved in eukaryotes.
The histone binding selectivity of purified recombinant yeast bromodomains was assessed by using the native core histones in an overlay assay, as well as N-terminally biotinylated lysine-acetylated histone peptides spotted on streptavidin-coated nitrocellulose membrane in a dot blot assay. NMR binding analysis further validated the interactions between histones and selected bromodomain. Structural models of all yeast bromodomains were built using comparative modeling to provide insights into the molecular basis of their histone binding selectivity.
Our study reveals that while not all members of the bromodomain family are privileged to interact with acetylated-lysine, identifiable sequence features from those that bind histone emerge. These include an asparagine residue at the C-terminus of the third helix in the 4-helix bundle, negatively charged residues around the ZA loop, and preponderance of aromatic amino acid residues in the binding pocket. Further, while bromodomains exhibit selectivity for different sites in histones, individual interactions are of modest affinity. Finally, electrostatic interactions appear to be a primary determining factor that guides productive association between a bromodomain and a lysine-acetylated histone.
We describe the proceedings and conclusions from a “Workshop on Applications of Protein Models in Biomedical Research” that was held at University of California at San Francisco on 11 and 12 July, 2008. At the workshop, international scientists involved with structure modeling explored (i) how models are currently used in biomedical research, (ii) what the requirements and challenges for different applications are, and (iii) how the interaction between the computational and experimental research communities could be strengthened to advance the field.
SITEHOUND-web (http://sitehound.sanchezlab.org) is a binding-site identification server powered by the SITEHOUND program. Given a protein structure in PDB format SITEHOUND-web will identify regions of the protein characterized by favorable interactions with a probe molecule. These regions correspond to putative ligand binding sites. Depending on the probe used in the calculation, sites with preference for different ligands will be identified. Currently, a carbon probe for identification of binding sites for drug-like molecules, and a phosphate probe for phosphorylated ligands (ATP, phoshopeptides, etc.) have been implemented. SITEHOUND-web will display the results in HTML pages including an interactive 3D representation of the protein structure and the putative sites using the Jmol java applet. Various downloadable data files are also provided for offline data analysis.
Although multiple templates are frequently used in comparative modeling, the effect of inclusion of additional template(s) on model accuracy (when compared to that of corresponding single-template based models) is not clear. To address this, we systematically analyze two-template models, the simplest case of multiple-template modeling. For an existing target-template pair (single-template modeling), a two-template based model of the target sequence is constructed by including an additional template without changing the original alignment to measure the effect of the second template on model accuracy.
Even though in a large number of cases a two-template model showed higher accuracy than the corresponding one-template model, over the entire dataset only a marginal improvement was observed on average, as there were many cases where no change or the reverse change was observed. The increase in accuracy due to the structural complementarity of the templates increases at higher alignment accuracies. The combination of templates showing the highest potential for improvement is that where both templates share similar and low (less than 30%) sequence identity with the target, as well as low sequence identity with each other. The structural similarity between the templates also helps in identifying template combinations having a higher chance of resulting in an improved model.
Inclusion of additional template(s) does not necessarily improve model quality, but there are distinct combinations of the two templates, which can be selected a priori, that tend to show improvement in model quality over the single template model. The benefit derived from the structural complementarity is dependent on the accuracy of the modeling alignment. The study helps to explain the observation that a careful selection of templates together with an accurate target:template alignment are necessary to the benefit from using multiple templates in comparative modeling and provides guidelines to maximize the benefit from using multiple templates. This enables formulation of simple template selection rules to rank targets of a protein family in the context of structural genomics.
The accuracy of comparative models of proteins is addressed here. A set of 12 732 single-template models of sequences of known high-resolution structures was built by an automated procedure. Accuracy of several structure-derived properties, such as surface area, residue accessibility, presence of pockets, electrostatic potential and others, was determined as a function of template:target sequence identity by comparing models with their corresponding experimental structures. As expected, the average accuracy of structure-derived properties always increases with higher template:target sequence identity, but the exact shape of this relationship can differ from one property to another. A comparison of structure-derived properties measured from NMR and X-ray structures of the same protein shows that for most properties, the NMR/X-ray difference is of the same order as the error in models based on ∼40% template:target sequence identity. The exact sequence identity at which properties reach that accuracy varies between 25 and 50%, depending on the property being analyzed. A general characteristic of simple comparative models is that their surface has increased area as a consequence of being more rugged than that of experimental structures. This suggests that including solvent effects during model building or refinement could significantly improve the accuracy of surface properties in comparative models.
Reactive oxygen species (ROS) are key intermediates in cellular signal transduction pathways whose function may be counterbalanced by antioxidants. Acting as an antioxidant, ascorbic acid (AA) donates two electrons and becomes oxidized to dehydroascorbic acid (DHA). We discovered that DHA directly inhibits IκBα kinase β (IKKβ) and IKKα enzymatic activity in vitro, whereas AA did not have this effect. When cells were loaded with AA and induced to generate DHA by oxidative stress in cells expressing a constitutive active IKKβ, NF-κB activation was inhibited. Our results identify a dual molecular action of vitamin C in signal transduction and provide a direct linkage between the redox state of vitamin C and NF-κB signaling events. AA quenches ROS intermediates involved in the activation of NF-κB and is oxidized to DHA, which directly inhibits IKKβ and IKKα enzymatic activity. These findings define a function for vitamin C in signal transduction other than as an antioxidant and mechanistically illuminate how vitamin C down-modulates NF-κB signaling.
In a continuing effort to identify ribonucleases that may be involved in mRNA decay in Bacillus subtilis, fractionation of a protein extract from a triple-mutant strain that was missing three previously characterized 3′-to-5′ exoribonucleases (polynucleotide phosphorylase [PNPase], RNase R, and YhaM) was undertaken. These experiments revealed the presence of a high-molecular-weight nuclease encoded by the yhcR gene that was active in the presence of Ca2+ and Mn2+. YhcR is a sugar-nonspecific nuclease that cleaves endonucleolytically to yield nucleotide 3′-monophosphate products, similar to the well-characterized micrococcal nuclease of Staphylococcus aureus. YhcR appears to be located principally in the cell wall and is likely to be a substrate for a B. subtilis sortase. Zymogram analysis suggests that YhcR is the major Ca2+-activated nuclease of B. subtilis. In addition to having a unique overall domain structure, YhcR contains a hitherto unknown structural domain that we have named “NYD,” for “new YhcR domain.”
A strain of Bacillus subtilis lacking two 3′-to-5′ exoribonucleases, polynucleotide phosphorylase (PNPase) and RNase R, was used to purify another 3′-to-5′ exoribonuclease, which is encoded by the yhaM gene. YhaM was active in the presence of Mn2+ (or Co2+), was inactive in the presence of Mg2+, and could also degrade single-stranded DNA. The half-life of bulk mRNA in a mutant lacking PNPase, RNase R, and YhaM was not significantly different from that of the wild type, suggesting the existence of additional activities that can participate in mRNA turnover. Sequence homologues of YhaM were found only in gram-positive organisms. The Staphylococcus aureus homologue, CBF1, which had been characterized as a double-stranded DNA binding protein involved in plasmid replication, was also shown to be an Mn2+-dependent exoribonuclease. YhaM protein has a C-terminal “HD domain,” found in metal-dependent phosphohydrolases. By structure modeling, it was shown that YhaM also contains an N-terminal “OB-fold,” present in many oligosaccharide- and oligonucleotide-binding proteins. The combination of these two domains is unique. Thus, YhaM and 10 related proteins from gram-positive organisms constitute a new exonuclease family.