Here we introduce EVAcon, an automated web service that evaluates the performance of contact prediction servers. Currently, EVAcon is monitoring nine servers, four of which are specialized in contact prediction and five are general structure prediction servers. Results are compared for all newly determined experimental structures deposited into PDB (∼5–50 per week). EVAcon allows for a precise comparison of the results based on a system of common protein subsets and the commonly accepted evaluation criteria that are also used in the corresponding category of the CASP assessment. EVAcon is a new service added to the functionality of the EVA system for the continuous evaluation of protein structure prediction servers. The new service is accesible from any of the three EVA mirrors: PDG (CNB-CSIC, Madrid) (); CUBIC (Columbia University, NYC) (); and Sali Lab (UCSF, San Francisco) ().
The META-PP server (http://cubic.bioc.columbia.edu/meta/) simplifies access to a battery of public protein structure and function prediction servers by providing a common and stable web-based interface. The goal is to make these powerful and increasingly essential methods more readily available to nonexpert users and the bioinformatics community at large. At present META-PP provides access to a selected set of high-quality servers in the areas of comparative modelling, threading/fold recognition, secondary structure prediction and more specialized fields like contact and function prediction.
PredictProtein (PP, http://cubic.bioc.columbia.edu/pp/) is an internet service for sequence analysis and the prediction of aspects of protein structure and function. Users submit protein sequence or alignments; the server returns a multiple sequence alignment, PROSITE sequence motifs, low-complexity regions (SEG), ProDom domain assignments, nuclear localisation signals, regions lacking regular structure and predictions of secondary structure, solvent accessibility, globular regions, transmembrane helices, coiled-coil regions, structural switch regions and disulfide-bonds. Upon request, fold recognition by prediction-based threading is available. For all services, users can submit their query either by electronic mail or interactively from World Wide Web.
Prediction of trans-membrane helices continues to be a difficult task with a few prediction methods clearly taking the lead; none of these is clearly best on all accounts. Recently, we have carefully set up protocols for benchmarking the most relevant aspects of prediction accuracy and have applied it to >30 prediction methods. Here, we present the extension of that analysis to the level of an automatic web server evaluating new methods (http://cubic.bioc.columbia.edu/services/tmh_benchmark/). The most important achievements of the tool are: (i) any new method is compared to the battery of well-established tools; (ii) the battery of measures explored allows spotting strengths in methods that may not be ‘best’ overall. In particular, we report per-residue and per-segment scores for accuracy and the error-rates for confusing membrane helices with globular proteins or signal peptides. An additional feature is that developers can directly investigate any hydrophobicity scale for its potential in predicting membrane helices.
LOC3D (http://cubic.bioc.columbia.edu/db/LOC3d/) is both a weekly-updated database and a web server for predictions of sub-cellular localization for eukaryotic proteins of known three-dimensional (3D) structure. Localization is predicted using four different methods: (i) PredictNLS, prediction of nuclear proteins through nuclear localization signals; (ii) LOChom, inferring localization through sequence homology; (iii) LOCkey, inferring localization through automatic text analysis of SWISS-PROT keywords; and (iv) LOC3Dini, ab initio prediction through a system of neural networks and vector support machines. The final prediction is based on the method that predicts localization with the highest confidence. The LOC3D database currently contains predictions for >8700 eukaryotic protein chains taken from the Protein Data Bank (PDB). The web server can be used to predict sub-cellular localization for proteins for which only a predicted structure is available from threading servers. This makes the resource of particular interest to structural genomics initiatives.
We describe Distill, a suite of servers for the prediction of protein structural features: secondary structure; relative solvent accessibility; contact density; backbone structural motifs; residue contact maps at 6, 8 and 12 Angstrom; coarse protein topology. The servers are based on large-scale ensembles of recursive neural networks and trained on large, up-to-date, non-redundant subsets of the Protein Data Bank. Together with structural feature predictions, Distill includes a server for prediction of Cα traces for short proteins (up to 200 amino acids).
The servers are state-of-the-art, with secondary structure predicted correctly for nearly 80% of residues (currently the top performance on EVA), 2-class solvent accessibility nearly 80% correct, and contact maps exceeding 50% precision on the top non-diagonal contacts. A preliminary implementation of the predictor of protein Cα traces featured among the top 20 Novel Fold predictors at the last CASP6 experiment as group Distill (ID 0348). The majority of the servers, including the Cα trace predictor, now take into account homology information from the PDB, when available, resulting in greatly improved reliability.
All predictions are freely available through a simple joint web interface and the results are returned by email. In a single submission the user can send protein sequences for a total of up to 32k residues to all or a selection of the servers. Distill is accessible at the address: .
ProFunc () is a web server for predicting the likely function of proteins whose 3D structure is known but whose function is not. Users submit the coordinates of their structure to the server in PDB format. ProFunc makes use of both existing and novel methods to analyse the protein's sequence and structure identifying functional motifs or close relationships to functionally characterized proteins. A summary of the analyses provides an at-a-glance view of what each of the different methods has found. More detailed results are available on separate pages. Often where one method has failed to find anything useful another may be more forthcoming. The server is likely to be of most use in structural genomics where a large proportion of the proteins whose structures are solved are of hypothetical proteins of unknown function. However, it may also find use in a comparative analysis of members of large protein families. It provides a convenient compendium of sequence and structural information that often hold vital functional clues to be followed up experimentally.
Identify correlations among SLC26A4 genotype, cochlear structural anomalies, and hearing loss associated with enlargement of the vestibular aqueduct (EVA).
Prospective cohort survey, National Institutes of Health, Clinical Center, a federal biomedical research facility.
83 individuals, 11 months to 59 years of age, with EVA in at least one ear. Correlations among pure-tone hearing thresholds, number of mutant SLC26A4 alleles, and the presence of cochlear anomalies detected by computed tomography or magnetic resonance imaging.
Linear mixed-effect model indicates significantly poorer hearing in ears with EVA from individuals with two mutant alleles of SLC26A4 than in those with EVA and a single mutant allele (p = .012) or no mutant alleles (p = .007) in this gene. There was no detectable relationship between degree of hearing loss and the presence of structural cochlear anomalies.
The number of mutant alleles of SLC26A4, but not the presence of cochlear anomalies, has a significant association with severity of hearing loss in ears with EVA. This information will be useful for prognostic counseling of patients and families with EVA.
enlarged vestibular aqueduct; SLC26A4; hearing
Objectives: To compare transmitted forces through ethylene vinyl acetate (EVA) mouthguard material and the same EVA material with gas inclusions in the form of a closed cell foam.
Method: EVA mouthguard materials with and without foam gas inclusions and 4 mm thick were impacted with a constant force from an impact pendulum. Various porosity levels in the foam materials were produced by 1%, 5%, and 10% by weight foaming agent. The forces transmitted through the EVA after energy absorption by the test materials were measured with a force sensor and compared.
Results: Only minor non-significant differences in transmitted forces through the EVA with and without foam were shown.
Conclusions: The inclusion of gas in the form of a closed cell foam in 4 mm thick EVA mouthguard materials did not improve the impact performance of the EVA mouthguard material.
Multiple sequence alignments are essential in computational sequence and structural analysis, with applications in homology detection, structure modeling, function prediction and phylogenetic analysis. We report PROMALS3D web server for constructing alignments for multiple protein sequences and/or structures using information from available 3D structures, database homologs and predicted secondary structures. PROMALS3D shows higher alignment accuracy than a number of other advanced methods. Input of PROMALS3D web server can be FASTA format protein sequences, PDB format protein structures and/or user-defined alignment constraints. The output page provides alignments with several formats, including a colored alignment augmented with useful information about sequence grouping, predicted secondary structures and consensus sequences. Intermediate results of sequence and structural database searches are also available. The PROMALS3D web server is available at: http://prodata.swmed.edu/promals3d/.
Conformational switches observed in the protein backbone play a key role in a variety of fundamental biological activities.
This paper describes a web-server that implements a pattern recognition algorithm trained on the examples from the Database
of Macromolecular Movements to predict residue positions involved in conformational switches. Prediction can be performed at
an adjustable false positive rate using a user-supplied protein sequence in FASTA format or a structure in a Protein Data
Bank (PDB) file. If a protein sequence is submitted, then the web-server uses sequence-derived information only (such as
evolutionary conservation of residue positions). If a PDB file is submitted, then the web-server uses sequence-derived
information and residue solvent accessibility calculated from this file.
FlexPred is publicly available at
conformational variability; support vector machine; protein flexibility; structural transition; prediction
Automatically extracting protein names from the literature and linking these names to the associated entries in sequence databases is becoming increasingly important for annotating biological databases. NLProt is a novel system that combines dictionary- and rule-based filtering with several support vector machines (SVMs) to tag protein names in PubMed abstracts. When considering partially tagged names as errors, NLProt still reached a precision of 75% at a recall of 76%. By many criteria our system outperformed other tagging methods significantly; in particular, it proved very reliable even for novel names. Names encountered particularly frequently in Drosophila, such as white, wing and bizarre, constitute an obvious limitation of NLProt. Our method is available both as an Internet server and as a program for download (http://cubic.bioc.columbia.edu/services/NLProt/). Input can be PubMed/MEDLINE identifiers, authors, titles and journals, as well as collections of abstracts, or entire papers.
Consensus is a server developed to produce high-quality alignments for comparative modeling, and to identify the alignment regions reliable for copying from a given template. This is accomplished even when target–template sequence identity is as low as 5%. Combining the output from five different alignment methods, the server produces a consensus alignment, with a reliability measure indicated for each position and a prediction of the regions suitable for modeling. Models built using the server predictions are typically within 3 Å rms deviations from the crystal structure. Users can upload a target protein sequence and specify a template (PDB code); if no template is given, the server will search for one. The method has been validated on a large set of homologous protein structure pairs. The Consensus server should prove useful for modelers for whom the structural reliability of the model is critical in their applications. It is currently available at http://structure.bu.edu/cgi-bin/consensus/consensus.cgi.
To evaluate the effect of pupillary dilation on electronic-ETDRS visual acuity (EVA) in diabetic subjects and to assess post-dilation EVA as a surrogate for pre-dilation visual acuity (VA).
Methods and Design
DRCR.net-protocol refraction and EVA were measured pre- and post-dilation in diabetic subjects by independent, masked examiners.
In 129 eyes of 66 subjects, median [25th, 75th percentiles] pre-dilation EVA score was 69 [54, 86] (Snellen-equivalent 20/40-1 [20/80-1, 20/20+1]). Pre-dilation VA was ≥20/20, 20/25-20/40, 20/50-20/80, and <20/80 in 29%, 19%, 26%, and 26% of eyes, respectively. Median EVA change post-dilation was -3 letters [-7, 0]. EVA change was ≥15 letters (≥ 3 ETDRS lines) in 9% of eyes and ≥10 letters (≥ 2 ETDRS lines) in 19% of eyes. Extent of change (range +12 to -25 letters) was associated with baseline VA. No relationship was identified between EVA change and gender, race, lens status, refractive error, DR severity, or primary cause of vision loss.
In an optimized clinical trial setting, there is a decline in best-corrected EVA after dilation in diabetic subjects. The large range and magnitude of VA change preclude using post-dilation EVA as a surrogate for undilated VA.
The SAM-T08 web server is a protein structure prediction server that provides several useful intermediate results in addition to the final predicted 3D structure: three multiple sequence alignments of putative homologs using different iterated search procedures, prediction of local structure features including various backbone and burial properties, calibrated E-values for the significance of template searches of PDB and residue–residue contact predictions. The server has been validated as part of the CASP8 assessment of structure prediction as having good performance across all classes of predictions. The SAM-T08 server is available at http://compbio.soe.ucsc.edu/SAM_T08/T08-query.html
An in-clinic assay for equine serum amyloid A (SAA) analysis, Equinostic EVA1, was evaluated for use in a clinical setting. Stability of SAA in serum samples was determined.
Intra- and inter- assay variation of the in-clinic method was determined. The in-clinic method (EVA1) results were compared to a reference method (Eiken LZ SAA) with 62 patient samples. For samples with SAA concentrations within the assay range of EVA1 (10-270 mg/L), differences between the methods were evaluated in a difference plot. Linearity under dilution was evaluated in two samples. Stability of SAA in three serum pools stored at 4°C and approximately 22°C was evaluated with the reference method day 0, 1, 2, 4, 7, 17 and analysed with a two-way ANOVA.
The imprecision (coefficient of variation, CV) for the in-clinic method was acceptable at higher SAA concentrations with CV values of 7,3-12%, but poor at low SAA concentrations with CV values of 27% and 37% for intra- and inter-assay variation respectively. Recovery after dilution was 50-138%. The in-clinic assay and the reference method identified equally well horses with low (<10 mg/L) and high (>270 mg/L) SAA concentrations. Within the assay range of the in-clinic method, 10-270 mg/L, the difference between the two methods was slightly higher than could be explained by the inherent imprecision of the assays. There were no significant changes of serum SAA concentrations during storage.
The in-clinic assay identified horses with SAA concentrations of <10 mg/L and >270 mg/L in a similar way as the reference method, and provided an estimate of the SAA concentration in the range of 10-270 mg/L. The imprecision of the in-clinic method was acceptable at high SAA concentrations but not at low concentrations. Dilution of samples gave inconsistent results. SAA was stable both at room temperature and refrigerated, and thus samples may be stored before analysis with the reference method.
ClusPro (http://nrc.bu.edu/cluster) represents the first fully automated, web-based program for the computational docking of protein structures. Users may upload the coordinate files of two protein structures through ClusPro's web interface, or enter the PDB codes of the respective structures, which ClusPro will then download from the PDB server (http://www.rcsb.org/pdb/). The docking algorithms evaluate billions of putative complexes, retaining a preset number with favorable surface complementarities. A filtering method is then applied to this set of structures, selecting those with good electrostatic and desolvation free energies for further clustering. The program output is a short list of putative complexes ranked according to their clustering properties, which is automatically sent back to the user via email.
The I-TASSER server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional atomic models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission numbers and Gene Ontology terms. An estimate of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of on-line server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhang.bioinformatics.ku.edu/I-TASSER.
I-TASSER; protein structure prediction; protein function prediction
The World Wide Web server of the PBIL (Pôle Bioinformatique Lyonnais) provides on-line access to sequence databanks and to many tools of nucleic acid and protein sequence analyses. This server allows to query nucleotide sequence banks in the EMBL and GenBank formats and protein sequence banks in the SWISS-PROT and PIR formats. The query engine on which our data bank access is based is the ACNUC system. It allows the possibility to build complex queries to access functional zones of biological interest and to retrieve large sequence sets. Of special interest are the unique features provided by this system to query the data banks of gene families developed at the PBIL. The server also provides access to a wide range of sequence analysis methods: similarity search programs, multiple alignments, protein structure prediction and multivariate statistics. An originality of this server is the integration of these two aspects: sequence retrieval and sequence analysis. Indeed, thanks to the introduction of re-usable lists, it is possible to perform treatments on large sets of data. The PBIL server can be reached at: http://pbil.univ-lyon1.fr.
Summary: Structure-based approaches complement ligand-based approaches for lead-discovery and cross-reactivity prediction. We present to the scientific community a web server for comparing the surface of a ligand bound site of a protein against a ligand bound site surface database of 106 796 sites. The web server implements the property encoded shape distributions (PESD) algorithm for surface comparison. A typical virtual screen takes 5 min to complete. The output provides a ranked list of sites (by site similarity), hyperlinked to the corresponding entries in the PDB and PDBeChem databases.
Availability: The server is freely accessible at http://reccr.chem.rpi.edu/Software/pesdserv/
Here, we describe two freely available web servers for molecular docking. The PatchDock method performs structure prediction of protein–protein and protein–small molecule complexes. The SymmDock method predicts the structure of a homomultimer with cyclic symmetry given the structure of the monomeric unit. The inputs to the servers are either protein PDB codes or uploaded protein structures. The services are available at . The methods behind the servers are very efficient, allowing large-scale docking experiments.
VADAR (Volume Area Dihedral Angle Reporter) is a comprehensive web server for quantitative protein structure evaluation. It accepts Protein Data Bank (PDB) formatted files or PDB accession numbers as input and calculates, identifies, graphs, reports and/or evaluates a large number (>30) of key structural parameters both for individual residues and for the entire protein. These include excluded volume, accessible surface area, backbone and side chain dihedral angles, secondary structure, hydrogen bonding partners, hydrogen bond energies, steric quality, solvation free energy as well as local and overall fold quality. These derived parameters can be used to rapidly identify both general and residue-specific problems within newly determined protein structures. The VADAR web server is freely accessible at http://redpoll.pharmacy.ualberta.ca/vadar.
Epithelial V-like antigen (EVA), a CD3-binding immunoglobulin-like protein, regulates embryonic thymic development. Here we demonstrate that EVA is expressed in choroid plexus from mature immune competent and lymphocyte deficient (RAG−/−) mice. Choroid plexus epithelial cells from RAG−/− mice demonstrated reduced junctional integrity and enhanced permeability that was associated with decreased expression of E-cadherin and EVA mRNA as compared to wild-type mice. Following iv infusion of an anti-CD3 antibody (145-2C11) that also binds EVA, expression of E-cadherin and EVA mRNA approached levels seen in wild type mice. Immuno-fluorescent staining for cadherin also revealed decreased expression in untreated RAG−/− mice that could be increased by 145-2C11 treatment. Expression of mouse EVA in HEK-293 cells followed by challenge with 145-2C11 resulted in increased cytosolic calcium that was not seen in control cells. These results suggest that EVA expressed in choroid plexus cells may regulate the permeability of the blood-CSF barrier.
Epithelial V-like antigen; choroid plexus; blood-CSF barrier; cadherin; F-actin; signal transduction; cytosolic calcium
Hearing loss with enlarged vestibular aqueduct (EVA) can be inherited as an autosomal recessive trait caused by bi-allelic mutations of SLC26A4. However, many EVA patients have non-diagnostic SLC26A4 genotypes with only one or no detectable mutant alleles.
Methods and results
In this study, the authors were unable to detect occult SLC26A4 mutations in EVA patients with non-diagnostic genotypes by custom comparative genomic hybridisation (CGH) microarray analysis or by sequence analysis of conserved non-coding regions. The authors sought to compare the segregation of EVA among 71 families with two (M2), one (M1) or no (M0) detectable mutant alleles of SLC26A4. The segregation ratios of EVA in the M1 and M2 groups were similar, but the segregation ratio for M1 was significantly higher than in the M0 group. Haplotype analyses of SLC26A4-linked STR markers in M0 and M1 families revealed discordant segregation of EVA with these markers in eight of 24 M0 families.
The results support the hypothesis of a second, undetected SLC26A4 mutation that accounts for EVA in the M1 patients, in contrast to non-genetic factors, complex inheritance, or aetiologic heterogeneity in the M0 group of patients. These results will be helpful for counselling EVA families with non-diagnostic SLC26A4 genotypes.
To compare visual acuity (VA) scores after autorefraction versus research protocol manual refraction in eyes of patients with diabetes and a wide range of VA.
Electronic Early Treatment Diabetic Retinopathy Study (E-ETDRS) VA Test© letter score (EVA) was measured after autorefraction (AR-EVA) and after Diabetic Retinopathy Clinical Research Network (DRCR.net) protocol manual refraction (MR-EVA). Testing order was randomized, study participants and VA examiners were masked to refraction source, and a second EVA utilizing an identical manual refraction (MR-EVAsupl) was performed to determine test-retest variability.
In 878 eyes of 456 study participants, median MR-EVA was 74 (Snellen equivalent approximately 20/32). Spherical equivalent was often similar for manual and autorefraction (median difference: 0.00, 5th and 95th percentiles −1.75 to +1.13 Diopters). However, on average, MR-EVA results were slightly better than AR-EVA results across the entire VA range. Furthermore, variability between AR-EVA and MR-EVA was substantially greater than the test-retest variability of MR-EVA (P<0.001). Variability of differences was highly dependent on autorefractor model.
Across a wide range of VA at multiple sites using a variety of autorefractors, VA measurements tend to be worse with autorefraction than manual refraction. Differences between individual autorefractor models were identified. However, even among autorefractor models comparing most favorably to manual refraction, VA variability between autorefraction and manual refraction is higher than the test-retest variability of manual refraction. The results suggest that with current instruments, autorefraction is not an acceptable substitute for manual refraction for most clinical trials with primary outcomes dependent on best-corrected VA.