The ConSurf-DB: pre-calculated evolutionary conservation profiles of protein structures

ConSurf-DB is a repository for evolutionary conservation analysis of the proteins of known structures in the Protein Data Bank (PDB). Sequence homologues of each of the PDB entries were collected and aligned using standard methods. The evolutionary conservation of each amino acid position in the alignment was calculated using the Rate4Site algorithm, implemented in the ConSurf web server. The algorithm takes into account the phylogenetic relations between the aligned proteins and the stochastic nature of the evolutionary process explicitly. Rate4Site assigns a conservation level for each position in the multiple sequence alignment using an empirical Bayesian inference. Visual inspection of the conservation patterns on the 3D structure often enables the identification of key residues that comprise the functionally important regions of the protein. The repository is updated with the latest PDB entries on a monthly basis and will be rebuilt annually. ConSurf-DB is available online at http://consurfdb.tau.ac.il

The effect of baseline metabolic rate on pulmonary O₂ uptake kinetics during very heavy intensity exercise in boys and men

addresses: Children's Health and Exercise Research Centre, College of Life and Environmental Sciences, University of Exeter, UK.Copyright © 2012 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Respiratory Physiology and Neurobiology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Respiratory Physiology and Neurobiology, 2012, 180 (2-3), pp. 223 – 229 DOI: 10.1016/j.resp.2011.11.013This study tested the hypothesis that pulmonary VO₂ kinetics would be slowed during 'work-to-work' exercise in adults but not in children. Eight boys (mean age=12.5 ± 0.5 years) and nine men completed very heavy step transitions initiated from either 'unloaded' pedalling (U→VH) or unloaded-to-moderate cycling (i.e. U→M to M→VH). The phase II τ was significantly (p<0.05) lengthened in M→VH compared to U→M and U→VH in boys (30 ± 5 vs. 19 ± 5 vs. 21 ± 5 s) and men (49 ± 14 vs. 30 ± 5 vs. 34 ± 8 s). In U→VH, a greater relative VO₂ slow component temporally coincided with an increased linear iEMG slope in men compared boys (VO₂ slow component: 16 ± 3 vs. 11 ± 4%; iEMG slope: 0.19 ± 0.24 vs. -0.06 ± 0.14%, p<0.05). These results suggest that an age-linked modulation of VO₂ kinetics might be influenced by alterations in muscle fibre recruitment following the onset of exercise

Oral rehydration versus intravenous therapy for treating dehydration due to gastroenteritis in children: a meta-analysis of randomised controlled trials

BACKGROUND: Despite treatment recommendations from various organizations, oral rehydration therapy (ORT) continues to be underused, particularly by physicians in high-income countries. We conducted a systematic review of randomised controlled trials (RCTs) to compare ORT and intravenous therapy (IVT) for the treatment of dehydration secondary to acute gastroenteritis in children. METHODS: RCTs were identified through MEDLINE, EMBASE, CENTRAL, authors and references of included trials, pharmaceutical companies, and relevant organizations. Screening and inclusion were performed independently by two reviewers in order to identify randomised or quasi-randomised controlled trials comparing ORT and IVT in children with acute diarrhea and dehydration. Two reviewers independently assessed study quality using the Jadad scale and allocation concealment. Data were extracted by one reviewer and checked by a second. The primary outcome measure was failure of rehydration. We analyzed data using standard meta-analytic techniques. RESULTS: The quality of the 14 included trials ranged from 0 to 3 (Jadad score); allocation concealment was unclear in all but one study. Using a random effects model, there was no significant difference in treatment failures (risk difference [RD] 3%; 95% confidence intervals [CI]: 0, 6). The Mantel-Haenzsel fixed effects model gave a significant difference between treatment groups (RD 4%; 95% CI: 2, 5) favoring IVT. Based on the four studies that reported deaths, there were six in the IVT groups and two in ORT. There were no significant differences in total fluid intake at six and 24 hours, weight gain, duration of diarrhea, or hypo/hypernatremia. Length of stay was significantly shorter for the ORT group (weighted mean difference [WMD] -1.2 days; 95% CI: -2.4,-0.02). Phlebitis occurred significantly more often with IVT (number needed to treat [NNT] 33; 95% CI: 25,100); paralytic ileus occurred more often with ORT (NNT 33; 95% CI: 20,100). These results may not be generalizable to children with persistent vomiting. CONCLUSION: There were no clinically important differences between ORT and IVT in terms of efficacy and safety. For every 25 children (95% CI: 20, 50) treated with ORT, one would fail and require IVT. The results support existing practice guidelines recommending ORT as the first course of treatment in appropriate children with dehydration secondary to gastroenteritis

Quantitative analysis of the binding affinity of poly(ADP-ribose) to specific binding proteins as a function of chain length

Poly(ADP-ribose) (PAR) is synthesized by poly(ADP-ribose) polymerases in response to genotoxic stress and interacts non-covalently with DNA damage checkpoint and repair proteins. Here, we present a variety of techniques to analyze this interaction in terms of selectivity and affinity. In vitro synthesized PAR was end-labeled using a carbonyl-reactive biotin analog. Binding of HPLC-fractionated PAR chains to the tumor suppressor protein p53 and to the nucleotide excision repair protein XPA was assessed using a novel electrophoretic mobility shift assay (EMSA). Long ADP-ribose chains (55-mer) promoted the formation of three specific complexes with p53. Short PAR chains (16-mer) were also able to bind p53, yet forming only one defined complex. In contrast, XPA did not interact with short polymer, but produced a single complex with long PAR chains (55-mer). In addition, we performed surface plasmon resonance with immobilized PAR chains, which allowed establishing binding constants and confirmed the results obtained by EMSA. Taken together, we developed several new protocols permitting the quantitative characterization of PAR–protein binding. Furthermore, we demonstrated that the affinity of the non-covalent PAR interactions with specific binding proteins (XPA, p53) can be very high (nanomolar range) and depends both on the PAR chain length and on the binding protein

ERK1/2 MAP kinases promote cell cycle entry by rapid, kinase-independent disruption of retinoblastoma–lamin A complexes

When in the nucleus, ERK1/2 dislodges the retinoblastoma protein from lamin A, facilitating its rapid phosphorylation

Joint Evolutionary Trees: A Large-Scale Method To Predict Protein Interfaces Based on Sequence Sampling

The Joint Evolutionary Trees (JET) method detects protein interfaces, the core residues involved in the folding process, and residues susceptible to site-directed mutagenesis and relevant to molecular recognition. The approach, based on the Evolutionary Trace (ET) method, introduces a novel way to treat evolutionary information. Families of homologous sequences are analyzed through a Gibbs-like sampling of distance trees to reduce effects of erroneous multiple alignment and impacts of weakly homologous sequences on distance tree construction. The sampling method makes sequence analysis more sensitive to functional and structural importance of individual residues by avoiding effects of the overrepresentation of highly homologous sequences and improves computational efficiency. A carefully designed clustering method is parametrized on the target structure to detect and extend patches on protein surfaces into predicted interaction sites. Clustering takes into account residues' physical-chemical properties as well as conservation. Large-scale application of JET requires the system to be adjustable for different datasets and to guarantee predictions even if the signal is low. Flexibility was achieved by a careful treatment of the number of retrieved sequences, the amino acid distance between sequences, and the selective thresholds for cluster identification. An iterative version of JET (iJET) that guarantees finding the most likely interface residues is proposed as the appropriate tool for large-scale predictions. Tests are carried out on the Huang database of 62 heterodimer, homodimer, and transient complexes and on 265 interfaces belonging to signal transduction proteins, enzymes, inhibitors, antibodies, antigens, and others. A specific set of proteins chosen for their special functional and structural properties illustrate JET behavior on a large variety of interactions covering proteins, ligands, DNA, and RNA. JET is compared at a large scale to ET and to Consurf, Rate4Site, siteFiNDER|3D, and SCORECONS on specific structures. A significant improvement in performance and computational efficiency is shown

HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information

<p>Abstract</p> <p>Background</p> <p>Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues.</p> <p>Results</p> <p>Here we introduced an efficient algorithm HemeBIND for predicting heme binding residues by integrating structural and sequence information. We systematically investigated the characteristics of binding interfaces based on a non-redundant dataset of heme-protein complexes. It was found that several sequence and structural attributes such as evolutionary conservation, solvent accessibility, depth and protrusion clearly illustrate the differences between heme binding and non-binding residues. These features can then be separately used or combined to build the structure-based classifiers using support vector machine (SVM). The results showed that the information contained in these features is largely complementary and their combination achieved the best performance. To further improve the performance, an attempt has been made to develop a post-processing procedure to reduce the number of false positives. In addition, we built a sequence-based classifier based on SVM and sequence profile as an alternative when only sequence information can be used. Finally, we employed a voting method to combine the outputs of structure-based and sequence-based classifiers, which demonstrated remarkably better performance than the individual classifier alone.</p> <p>Conclusions</p> <p>HemeBIND is the first specialized algorithm used to predict binding residues in protein structures for heme ligands. Extensive experiments indicated that both the structure-based and sequence-based methods have effectively identified heme binding residues while the complementary relationship between them can result in a significant improvement in prediction performance. The value of our method is highlighted through the development of HemeBIND web server that is freely accessible at <url>http://mleg.cse.sc.edu/hemeBIND/</url>.</p

How accurate and statistically robust are catalytic site predictions based on closeness centrality?

<p>Abstract</p> <p>Background</p> <p>We examine the accuracy of enzyme catalytic residue predictions from a network representation of protein structure. In this model, amino acid α-carbons specify vertices within a graph and edges connect vertices that are proximal in structure. Closeness centrality, which has shown promise in previous investigations, is used to identify important positions within the network. Closeness centrality, a global measure of network centrality, is calculated as the reciprocal of the average distance between vertex <it>i </it>and all other vertices.</p> <p>Results</p> <p>We benchmark the approach against 283 structurally unique proteins within the Catalytic Site Atlas. Our results, which are inline with previous investigations of smaller datasets, indicate closeness centrality predictions are statistically significant. However, unlike previous approaches, we specifically focus on residues with the very best scores. Over the top five closeness centrality scores, we observe an average true to false positive rate ratio of 6.8 to 1. As demonstrated previously, adding a solvent accessibility filter significantly improves predictive power; the average ratio is increased to 15.3 to 1. We also demonstrate (for the first time) that filtering the predictions by residue identity improves the results even more than accessibility filtering. Here, we simply eliminate residues with physiochemical properties unlikely to be compatible with catalytic requirements from consideration. Residue identity filtering improves the average true to false positive rate ratio to 26.3 to 1. Combining the two filters together has little affect on the results. Calculated p-values for the three prediction schemes range from 2.7E-9 to less than 8.8E-134. Finally, the sensitivity of the predictions to structure choice and slight perturbations is examined.</p> <p>Conclusion</p> <p>Our results resolutely confirm that closeness centrality is a viable prediction scheme whose predictions are statistically significant. Simple filtering schemes substantially improve the method's predicted power. Moreover, no clear effect on performance is observed when comparing ligated and unligated structures. Similarly, the CC prediction results are robust to slight structural perturbations from molecular dynamics simulation.</p

Burnout and Depression: Two Entities or One

Objectives: The purpose of this study was to examine the overlap in burnout and depression. Method: The sample comprised 1,386 schoolteachers (mean age = 43; mean years taught = 15; 77% women) from 18 different U.S. states. We assessed burnout, using the Shirom-Melamed Burnout Measure, and depression, using the depression module of the Patient Health Questionnaire. Results: Treated dimensionally, burnout and depressive symptoms were strongly correlated (.77; disattenuated correlation, .84). Burnout and depressive symptoms were similarly correlated with each of 3 stress-related factors, stressful life events, job adversity, and workplace support. In categorical analyses, 86% of the teachers identified as burned out met criteria for a provisional diagnosis of depression. Exploratory analyses revealed a link between burnout and anxiety. Conclusions: This study provides evidence that past research has underestimated burnout–depression overlap. The state of burnout is likely to be a form of depression. Given the magnitude of burnout–depression overlap, treatments for depression may help workers identified as burned out. Copyright 2015 Wiley Periodicals, Inc. J. Clin. Psychol. 72:22–37, 2016

Audit of therapeutic interventions in inpatient children using two scores: are they evidence-based in developing countries?

BACKGROUND: The evidence base of clinical interventions in paediatric hospitals of developing countries has not been formally assessed. We performed this study to determine the proportion of evidence-based therapeutic interventions in a paediatric referral hospital of a developing country METHODS: The medical records of 167 patients admitted in one-month period were revised. Primary diagnosis and primary therapeutic interventions were determined for each patient. A systematic search was performed to assess the level of evidence for each intervention. Therapeutic interventions were classified using the Ellis score and the Oxford Centre for Evidence Based Medicine Levels of Evidence RESULTS: Any dehydration due to diarrhoea (59 cases) and pneumonia (42 cases) were the most frequent diagnoses. Based on Ellis score, level I evidence supported the primary therapeutic intervention in 21%, level II in 73% and level III in 6% cases. Using the Oxford classification 16%, 8%, 1% and 75% therapeutic interventions corresponded to grades A, B, C, and D recommendations, respectively. Overall, according to Ellis score, 94% interventions were evidence based. However, out of the total, 75% interventions were based on expert opinion or basic sciences. Most children with mild to moderate dehydration (52 cases) were inappropriately treated with slow intravenous fluids, and most children with non-complicated community acquired pneumonia (42 cases) received intravenous antibiotics CONCLUSIONS: Most interventions were inappropriate, despite the availability of effective therapy for several of them. Diarrhoeal dehydration and community acquired pneumonia were the most common diagnoses and were inappropriately managed. Existing effective interventions for dehydration and pneumonia need to be put into practice at referral hospitals of developing countries. For the remaining problems, there is the need to conduct appropriate clinical studies. Caution must be taken when assigning the level of evidence supporting therapeutic interventions, as commonly used classifications may be misleadin