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1.  EVAcon: a protein contact prediction evaluation service 
Nucleic Acids Research  2005;33(Web Server issue):W347-W351.
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) ().
PMCID: PMC1160172  PMID: 15980486
2.  LOC3D: annotate sub-cellular localization for protein structures 
Nucleic Acids Research  2003;31(13):3337-3340.
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.
PMCID: PMC168921  PMID: 12824321
3.  META-PP: single interface to crucial prediction servers 
Nucleic Acids Research  2003;31(13):3308-3310.
The META-PP server ( 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.
PMCID: PMC168978  PMID: 12824314
4.  Improving protein secondary structure prediction based on short subsequences with local structure similarity 
BMC Genomics  2010;11(Suppl 4):S4.
When characterizing the structural topology of proteins, protein secondary structure (PSS) plays an important role in analyzing and modeling protein structures because it represents the local conformation of amino acids into regular structures. Although PSS prediction has been studied for decades, the prediction accuracy reaches a bottleneck at around 80%, and further improvement is very difficult.
In this paper, we present an improved dictionary-based PSS prediction method called SymPred, and a meta-predictor called SymPsiPred. We adopt the concept behind natural language processing techniques and propose synonymous words to capture local sequence similarities in a group of similar proteins. A synonymous word is an n-gram pattern of amino acids that reflects the sequence variation in a protein’s evolution. We generate a protein-dependent synonymous dictionary from a set of protein sequences for PSS prediction.
On a large non-redundant dataset of 8,297 protein chains (DsspNr-25), the average Q3 of SymPred and SymPsiPred are 81.0% and 83.9% respectively. On the two latest independent test sets (EVA Set_1 and EVA_Set2), the average Q3 of SymPred is 78.8% and 79.2% respectively. SymPred outperforms other existing methods by 1.4% to 5.4%. We study two factors that may affect the performance of SymPred and find that it is very sensitive to the number of proteins of both known and unknown structures. This finding implies that SymPred and SymPsiPred have the potential to achieve higher accuracy as the number of protein sequences in the NCBInr and PDB databases increases.
Our experiment results show that local similarities in protein sequences typically exhibit conserved structures, which can be used to improve the accuracy of secondary structure prediction. For the application of synonymous words, we demonstrate an example of a sequence alignment which is generated by the distribution of shared synonymous words of a pair of protein sequences. We can align the two sequences nearly perfectly which are very dissimilar at the sequence level but very similar at the structural level. The SymPred and SymPsiPred prediction servers are available at
PMCID: PMC3005913  PMID: 21143813
5.  Distill: a suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins 
BMC Bioinformatics  2006;7:402.
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: .
PMCID: PMC1574355  PMID: 16953874
6.  SWISS-MODEL: an automated protein homology-modeling server 
Nucleic Acids Research  2003;31(13):3381-3385.
SWISS-MODEL ( is a server for automated comparative modeling of three-dimensional (3D) protein structures. It pioneered the field of automated modeling starting in 1993 and is the most widely-used free web-based automated modeling facility today. In 2002 the server computed 120 000 user requests for 3D protein models. SWISS-MODEL provides several levels of user interaction through its World Wide Web interface: in the ‘first approach mode’ only an amino acid sequence of a protein is submitted to build a 3D model. Template selection, alignment and model building are done completely automated by the server. In the ‘alignment mode’, the modeling process is based on a user-defined target-template alignment. Complex modeling tasks can be handled with the ‘project mode’ using DeepView (Swiss-PdbViewer), an integrated sequence-to-structure workbench. All models are sent back via email with a detailed modeling report. WhatCheck analyses and ANOLEA evaluations are provided optionally. The reliability of SWISS-MODEL is continuously evaluated in the EVA-CM project. The SWISS-MODEL server is under constant development to improve the successful implementation of expert knowledge into an easy-to-use server.
PMCID: PMC168927  PMID: 12824332
7.  Improving the accuracy of protein secondary structure prediction using structural alignment 
BMC Bioinformatics  2006;7:301.
The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3) of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence) database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences), the probability of a newly identified sequence having a structural homologue is actually quite high.
We have developed a method that performs structure-based sequence alignments as part of the secondary structure prediction process. By mapping the structure of a known homologue (sequence ID >25%) onto the query protein's sequence, it is possible to predict at least a portion of that query protein's secondary structure. By integrating this structural alignment approach with conventional (sequence-based) secondary structure methods and then combining it with a "jury-of-experts" system to generate a consensus result, it is possible to attain very high prediction accuracy. Using a sequence-unique test set of 1644 proteins from EVA, this new method achieves an average Q3 score of 81.3%. Extensive testing indicates this is approximately 4–5% better than any other method currently available. Assessments using non sequence-unique test sets (typical of those used in proteome annotation or structural genomics) indicate that this new method can achieve a Q3 score approaching 88%.
By using both sequence and structure databases and by exploiting the latest techniques in machine learning it is possible to routinely predict protein secondary structure with an accuracy well above 80%. A program and web server, called PROTEUS, that performs these secondary structure predictions is accessible at . For high throughput or batch sequence analyses, the PROTEUS programs, databases (and server) can be downloaded and run locally.
PMCID: PMC1550433  PMID: 16774686
8.  Visual Acuity Testing Using Autorefraction or Pinhole Occluder as Compared with a Manual Protocol Refraction in Individuals with Diabetes 
Ophthalmology  2010;118(3):537-542.
To compare visual acuity (VA) scores obtained after autorefraction or using a pinhole occluder to scores obtained after refraction according to a standard clinical research protocol.
Prospective, comparative case series
One hundred and ten study participants (209 eyes) with diabetes mellitus and a broad range of diabetic retinopathy severity and visual acuity (VA).
VA was measured after autorefraction by a Topcon KR-8000 autorefractor as well as after a Diabetic Retinopathy Clinical Research Network ( protocol manual refraction. The order of testing was randomized and examiners were masked to the source of each refraction. A second VA measurement, utilizing an identical manual refraction, was made in a subset of eyes (N = 144, 69%) in order to establish test-retest variability for comparison purposes. All eyes underwent VA testing using a pinhole occluder.
Main Outcome Measures
Best corrected VA as measured by the Electronic Early Treatment Diabetic Retinopathy Study Visual Acuity Test© (E-ETDRS).
In all eyes, the median E-ETDRS VA letter score (EVA) obtained after manual refraction (MR-EVA) was 69 (Snellen equivalent 20/40), ranging from 4 to 93 (20/800 to 20/16). The median MR-EVA was slightly better than the median EVA obtained after autorefraction (AR-EVA), with a median difference (AR-EVA – MR-EVA) of −1 letter (25th, 75th percentiles: −4, 2 letters). The absolute difference between AR-EVA and MR-EVA was similar to the test-retest variability of MR-EVA alone. In contrast, MR-EVA was better than EVA obtained using a pinhole occluder (PH-EVA), (median PH-EVA – MR-EVA: −4 letters [−9, 0]), and had significantly less test-retest variability (P<0.001). Generally, the spherical equivalent of autorefraction was slightly more hyperopic (or less myopic) than the spherical equivalent of manual refraction (median difference: +0.25 Diopters [0, +0.63 Diopters]).
Given the substantial time and effort required for training and certification of study protocol refractionists, and the similarity between AR-EVA and MR-EVA, further evaluation of autorefraction, but not pinhole occluder testing, as an alternative to the current clinical research gold standard of ETDRS protocol manual refraction in study participants with diabetic retinopathy is warranted.
PMCID: PMC3057328  PMID: 20947171
9.  Static benchmarking of membrane helix predictions 
Nucleic Acids Research  2003;31(13):3642-3644.
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 ( 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.
PMCID: PMC168939  PMID: 12824384
10.  Cluster-based exposure variation analysis 
Static posture, repetitive movements and lack of physical variation are known risk factors for work-related musculoskeletal disorders, and thus needs to be properly assessed in occupational studies. The aims of this study were (i) to investigate the effectiveness of a conventional exposure variation analysis (EVA) in discriminating exposure time lines and (ii) to compare it with a new cluster-based method for analysis of exposure variation.
For this purpose, we simulated a repeated cyclic exposure varying within each cycle between “low” and “high” exposure levels in a “near” or “far” range, and with “low” or “high” velocities (exposure change rates). The duration of each cycle was also manipulated by selecting a “small” or “large” standard deviation of the cycle time. Theses parameters reflected three dimensions of exposure variation, i.e. range, frequency and temporal similarity.
Each simulation trace included two realizations of 100 concatenated cycles with either low (ρ = 0.1), medium (ρ = 0.5) or high (ρ = 0.9) correlation between the realizations. These traces were analyzed by conventional EVA, and a novel cluster-based EVA (C-EVA). Principal component analysis (PCA) was applied on the marginal distributions of 1) the EVA of each of the realizations (univariate approach), 2) a combination of the EVA of both realizations (multivariate approach) and 3) C-EVA. The least number of principal components describing more than 90% of variability in each case was selected and the projection of marginal distributions along the selected principal component was calculated. A linear classifier was then applied to these projections to discriminate between the simulated exposure patterns, and the accuracy of classified realizations was determined.
C-EVA classified exposures more correctly than univariate and multivariate EVA approaches; classification accuracy was 49%, 47% and 52% for EVA (univariate and multivariate), and C-EVA, respectively (p < 0.001). All three methods performed poorly in discriminating exposure patterns differing with respect to the variability in cycle time duration.
While C-EVA had a higher accuracy than conventional EVA, both failed to detect differences in temporal similarity. The data-driven optimality of data reduction and the capability of handling multiple exposure time lines in a single analysis are the advantages of the C-EVA.
PMCID: PMC3623884  PMID: 23557439
Ergonomics; Physical work load; Linear discriminant analysis; Work-related musculoskeletal disorders; Principle component analysis
11.  The PredictProtein server 
Nucleic Acids Research  2003;31(13):3300-3304.
PredictProtein (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.
PMCID: PMC168915  PMID: 12824312
12.  The effect of customised and sham foot orthoses on plantar pressures 
The effectiveness of foot orthoses has been evaluated in many clinical trials with sham foot orthoses used as the control intervention in at least 10 clinical trials. However, the mechanical effects and credibility of sham orthoses has been rarely quantified. This study aimed to: (i) compare the effects on plantar pressures of three sham foot orthoses to a customised foot orthosis, and (ii) establish the perceived credibility and the expected benefit of each orthotic condition.
Thirty adults aged between 18 and 51 participated in this study. At 0 and 4 weeks, plantar pressure data were collected for the heel, midfoot and forefoot using the pedar®-X in-shoe system for the following five randomly assigned conditions: (i) shoe alone, (ii) customised foot orthosis, (iii) contoured polyethylene sham foot orthosis, (iv) contoured EVA sham foot orthosis, and (v) flat EVA sham foot orthosis. At the initial data collection session, each participant completed a Credibility/Expectancy Questionnaire (CEQ) to determine the credibility and expected benefit of each orthotic condition.
Compared to the shoe alone at week 0, the contoured polyethylene sham orthosis was the only condition to not significantly effect peak pressure at any region of the foot. In contrast, the contoured EVA sham orthosis, the flat EVA sham orthosis and the customised orthosis significantly reduced peak pressure at the heel. At the medial midfoot, all sham orthoses provided the same effect as the shoe alone, which corresponded to effects that were significantly different to the customised orthosis. There were no differences in peak pressure between conditions at the other mask regions, the lateral midfoot and forefoot. When the conditions were compared at week 4, the differences between the conditions were generally similar to the findings observed at week 0. With respect to credibility and expected benefit, all orthotic conditions were considered the same with the exception of the contoured polyethylene sham orthosis, which was perceived as being less credible and less likely to provide benefits.
The findings of this study indicate that all of the sham orthoses tested provided the same effect on plantar pressures at the midfoot and forefoot as a shoe alone. However, the contoured EVA sham orthosis and the flat EVA sham orthosis significantly reduced peak pressure under the heel, which was similar to the customised orthosis. In contrast, the contoured polyethylene sham orthosis had no significant effect on plantar pressure and was comparable to the shoe alone at all regions of the foot. Hence, lower plantar pressures were found under the heel with some sham orthoses, but not with others. Importantly, participants perceived the polyethylene sham orthosis – the sham that had no effect on plantar pressure – to be the least credible orthosis and the least likely to provide benefits. This may be critical for the design of future clinical trials as it may introduce confounding effects that produce inaccurate results. These findings provide some evidence for the mechanical effects, treatment credibility and expected benefit of sham foot orthoses, which should be considered when they are used as a control intervention in a clinical trial.
PMCID: PMC3663766  PMID: 23680496
Orthoses; Orthotic devices; Sham treatment; Kinetics
13.  Effects of Dilation on Electronic-ETDRS Visual Acuity (EVA) in Diabetic Patients 
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 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.
PMCID: PMC2762194  PMID: 18936147
14.  A benchmark server using high resolution protein structure data, and benchmark results for membrane helix predictions 
BMC Bioinformatics  2013;14:111.
Helical membrane proteins are vital for the interaction of cells with their environment. Predicting the location of membrane helices in protein amino acid sequences provides substantial understanding of their structure and function and identifies membrane proteins in sequenced genomes. Currently there is no comprehensive benchmark tool for evaluating prediction methods, and there is no publication comparing all available prediction tools. Current benchmark literature is outdated, as recently determined membrane protein structures are not included. Current literature is also limited to global assessments, as specialised benchmarks for predicting specific classes of membrane proteins were not previously carried out.
We present a benchmark server at that uses recent high resolution protein structural data to provide a comprehensive assessment of the accuracy of existing membrane helix prediction methods. The server further allows a user to compare uploaded predictions generated by novel methods, permitting the comparison of these novel methods against all existing methods compared by the server. Benchmark metrics include sensitivity and specificity of predictions for membrane helix location and orientation, and many others. The server allows for customised evaluations such as assessing prediction method performances for specific helical membrane protein subtypes.
We report results for custom benchmarks which illustrate how the server may be used for specialised benchmarks. Which prediction method is the best performing method depends on which measure is being benchmarked. The OCTOPUS membrane helix prediction method is consistently one of the highest performing methods across all measures in the benchmarks that we performed.
The benchmark server allows general and specialised assessment of existing and novel membrane helix prediction methods. Users can employ this benchmark server to determine the most suitable method for the type of prediction the user needs to perform, be it general whole-genome annotation or the prediction of specific types of helical membrane protein. Creators of novel prediction methods can use this benchmark server to evaluate the performance of their new methods. The benchmark server will be a valuable tool for researchers seeking to extract more sophisticated information from the large and growing protein sequence databases.
PMCID: PMC3620685  PMID: 23530628
Helical membrane proteins; Transmembrane helix prediction; Benchmark
15.  Oxidative Lung Damage Resulting from Repeated Exposure to Radiation and Hyperoxia Associated with Space Exploration 
Spaceflight missions may require crewmembers to conduct Extravehicular Activities (EVA) for repair, maintenance or scientific purposes. Pre-breathe protocols in preparation for an EVA entail 100% hyperoxia exposure that may last for a few hours (5-8 hours), and may be repeated 2-3 times weekly. Each EVA is associated with additional challenges such as low levels of total body cosmic/galactic radiation exposure that may present a threat to crewmember health and therefore, pose a threat to the success of the mission. We have developed a murine model of combined, hyperoxia and radiation exposure (double-hit) in the context of evaluating countermeasures to oxidative lung damage associated with space flight. In the current study, our objective was to characterize the early and chronic effects of repeated single and double-hit challenge on lung tissue using a novel murine model of repeated exposure to low-level total body radiation and hyperoxia. This is the first study of its kind evaluating lung damage relevant to space exploration in a rodent model.
Mouse cohorts (n=5-15/group) were exposed to repeated: a) normoxia; b) >95% O2 (O2); c) 0.25Gy single fraction gamma radiation (IR); or d) a combination of O2 and IR (O2+IR) given 3 times per week for 4 weeks. Lungs were evaluated for oxidative damage, active TGFβ1 levels, cell apoptosis, inflammation, injury, and fibrosis at 1, 2, 4, 8, 12, 16, and 20 weeks post-initiation of exposure.
Mouse cohorts exposed to all challenge conditions displayed decreased bodyweight compared to untreated controls at 4 and 8 weeks post-challenge initiation. Chronic oxidative lung damage to lipids (malondialdehyde levels), DNA (TUNEL, cleaved Caspase 3, cleaved PARP positivity) leading to apoptotic cell death and to proteins (nitrotyrosine levels) was elevated all treatment groups. Importantly, significant systemic oxidative stress was also noted at the late phase in mouse plasma, BAL fluid, and urine. Importantly, however, late oxidative damage across all parameters that we measured was significantly higher than controls in all cohorts but was exacerbated by the combined exposure to O2 and IR. Additionally, impaired levels of arterial blood oxygenation were noted in all exposure cohorts. Significant but transient elevation of lung tissue fibrosis (p<0.05), determined by lung hydroxyproline content, was detected as early as 2 week in mice exposed to challenge conditions and persisted for 4-8 weeks only. Interestingly, active TGFβ1 levels in +BAL fluid was also transiently elevated during the exposure time only (1-4 weeks). Inflammation and lung edema/lung injury was also significantly elevated in all groups at both early and late time points, especially the double-hit group.
We have characterized significant, early and chronic lung changes consistent with oxidative tissue damage in our murine model of repeated radiation and hyperoxia exposure relevant to space travel. Lung tissue changes, detectable several months after the original exposure, include significant oxidative lung damage (lipid peroxidation, DNA damage and protein nitrosative stress) and increased pulmonary fibrosis. These findings, along with increased oxidative stress in diverse body fluids and the observed decreases in blood oxygenation levels in all challenge conditions (whether single or in combination), lead us to conclude that in our model of repeated exposure to oxidative stressors, chronic tissue changes are detected that persist even months after the exposure to the stressor has ended. This data will provide useful information in the design of countermeasures to tissue oxidative damage associated with space exploration.
PMCID: PMC3866035  PMID: 24358450
Apoptosis; Bronchoalveolar lavage; Caspase 3; Double-hit; Extravehicular activity; Hyperoxia; Inflammation; Lung fibrosis; Lung injury; Mouse model; Nitrotyrosine; Oxidative stress; PARP; Radiation pneumonopathy; Space exploration; TGF-β1; Total body irradiation; TUNEL
16.  Phenotypic and genotypic variations among three allopatric populations of Lutzomyia umbratilis, main vector of Leishmania guyanensis 
Parasites & Vectors  2015;8:448.
In South America, Lutzomyia umbratilis is the main vector of Leishmania guyanensis, one of the species involved in the transmission of American tegumentary leishmaniasis. In Brazil, L. umbratilis has been recorded in the Amazon region, and in the state of Pernambuco, Northeastern region, where an isolated population has been identified. This study assessed the phylogeographic structure and size and shape differences of the wing of three Brazilian populations.
Samples of L. umbratilis were collected from Rio Preto da Eva (north of the Amazon River, Amazonas), from Manacapuru (south of the Amazon River), and from the isolated population in Recife, Pernambuco state. These samples were processed to obtain sequences of the Cytochrome Oxidase I mitochondrial gene. Geometrics morphometry analysis of the right wing shape of the three populations was made using discriminate canonical analysis.
Phylogenetic analysis revealed the presence of two distinct monophyletic clades: one clade comprised of the Recife and Rio Preto da Eva samples, and the other clade comprised of the Manacapuru samples. Comparing the Manacapuru population with the Recife and Rio Preto da Eva populations generated high indices of interpopulational divergence. Geometric morphometry analysis indicated two distinct groups between the studied populations. Canonical variate analysis of wing shape indicated that Rio Preto da Eva population is significantly closer to Recife population, and both populations were genetically distant from Manacapuru.
The polymorphic sites and geometric morphometry analysis indicate that the distance, lack of continuity and environmental differences have not modified the ancestral relationship between Recife and Rio Preto da Eva populations. The genetic and morphological similarities shared by the Recife and Rio Preto da Eva populations suggest that these populations are more closely related evolutionarily. These results confirm the existence of an L. umbratilis species complex in the North and Northeast regions.
PMCID: PMC4559179  PMID: 26338469
Lutzomyia umbratilis; Species complex; Phylogenetic analysis; Geometric morphometry
17.  Jenner-predict server: prediction of protein vaccine candidates (PVCs) in bacteria based on host-pathogen interactions 
BMC Bioinformatics  2013;14:211.
Subunit vaccines based on recombinant proteins have been effective in preventing infectious diseases and are expected to meet the demands of future vaccine development. Computational approach, especially reverse vaccinology (RV) method has enormous potential for identification of protein vaccine candidates (PVCs) from a proteome. The existing protective antigen prediction software and web servers have low prediction accuracy leading to limited applications for vaccine development. Besides machine learning techniques, those software and web servers have considered only protein’s adhesin-likeliness as criterion for identification of PVCs. Several non-adhesin functional classes of proteins involved in host-pathogen interactions and pathogenesis are known to provide protection against bacterial infections. Therefore, knowledge of bacterial pathogenesis has potential to identify PVCs.
A web server, Jenner-Predict, has been developed for prediction of PVCs from proteomes of bacterial pathogens. The web server targets host-pathogen interactions and pathogenesis by considering known functional domains from protein classes such as adhesin, virulence, invasin, porin, flagellin, colonization, toxin, choline-binding, penicillin-binding, transferring-binding, fibronectin-binding and solute-binding. It predicts non-cytosolic proteins containing above domains as PVCs. It also provides vaccine potential of PVCs in terms of their possible immunogenicity by comparing with experimentally known IEDB epitopes, absence of autoimmunity and conservation in different strains. Predicted PVCs are prioritized so that only few prospective PVCs could be validated experimentally. The performance of web server was evaluated against known protective antigens from diverse classes of bacteria reported in Protegen database and datasets used for VaxiJen server development. The web server efficiently predicted known vaccine candidates reported from Streptococcus pneumoniae and Escherichia coli proteomes. The Jenner-Predict server outperformed NERVE, Vaxign and VaxiJen methods. It has sensitivity of 0.774 and 0.711 for Protegen and VaxiJen dataset, respectively while specificity of 0.940 has been obtained for the latter dataset.
Better prediction accuracy of Jenner-Predict web server signifies that domains involved in host-pathogen interactions and pathogenesis are better criteria for prediction of PVCs. The web server has successfully predicted maximum known PVCs belonging to different functional classes. Jenner-Predict server is freely accessible at
PMCID: PMC3701604  PMID: 23815072
Protein vaccine candidates (PVCs); Host-pathogen interactions; Domain; Antigen; Reverse vaccinology; Virulence
18.  Evaluation of Visual Acuity Measurements after Autorefraction versus Manual Refraction in Eyes with and without Diabetic Macular Edema 
Archives of ophthalmology  2011;130(4):470-479.
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 ( 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.
PMCID: PMC3489033  PMID: 22159173
19.  KoBaMIN: a knowledge-based minimization web server for protein structure refinement 
Nucleic Acids Research  2012;40(Web Server issue):W323-W328.
The KoBaMIN web server provides an online interface to a simple, consistent and computationally efficient protein structure refinement protocol based on minimization of a knowledge-based potential of mean force. The server can be used to refine either a single protein structure or an ensemble of proteins starting from their unrefined coordinates in PDB format. The refinement method is particularly fast and accurate due to the underlying knowledge-based potential derived from structures deposited in the PDB; as such, the energy function implicitly includes the effects of solvent and the crystal environment. Our server allows for an optional but recommended step that optimizes stereochemistry using the MESHI software. The KoBaMIN server also allows comparison of the refined structures with a provided reference structure to assess the changes brought about by the refinement protocol. The performance of KoBaMIN has been benchmarked widely on a large set of decoys, all models generated at the seventh worldwide experiments on critical assessment of techniques for protein structure prediction (CASP7) and it was also shown to produce top-ranking predictions in the refinement category at both CASP8 and CASP9, yielding consistently good results across a broad range of model quality values. The web server is fully functional and freely available at
PMCID: PMC3394243  PMID: 22564897
20.  FFAS03: a server for profile–profile sequence alignments 
Nucleic Acids Research  2005;33(Web Server issue):W284-W288.
The FFAS03 server provides a web interface to the third generation of the profile–profile alignment and fold-recognition algorithm of fold and function assignment system (FFAS) [L. Rychlewski, L. Jaroszewski, W. Li and A. Godzik (2000), Protein Sci., 9, 232–241]. Profile–profile algorithms use information present in sequences of homologous proteins to amplify the patterns defining the family. As a result, they enable detection of remote homologies beyond the reach of other methods. FFAS, initially developed in 2000, is consistently one of the best ranked fold prediction methods in the CAFASP and LiveBench competitions. It is also used by several fold-recognition consensus methods and meta-servers. The FFAS03 server accepts a user supplied protein sequence and automatically generates a profile, which is then compared with several sets of sequence profiles of proteins from PDB, COG, PFAM and SCOP. The profile databases used by the server are automatically updated with the latest structural and sequence information. The server provides access to the alignment analysis, multiple alignment, and comparative modeling tools. Access to the server is open for both academic and commercial researchers. The FFAS03 server is available at .
PMCID: PMC1160179  PMID: 15980471
21.  EVA-1 Functions as an UNC-40 Co-receptor to Enhance Attraction to the MADD-4 Guidance Cue in Caenorhabditis elegans 
PLoS Genetics  2014;10(8):e1004521.
We recently discovered a secreted and diffusible midline cue called MADD-4 (an ADAMTSL) that guides migrations along the dorsoventral axis of the nematode Caenorhabditis elegans. We showed that the transmembrane receptor, UNC-40 (DCC), whose canonical ligand is the UNC-6 (netrin) guidance cue, is required for extension towards MADD-4. Here, we demonstrate that MADD-4 interacts with an EVA-1/UNC-40 co-receptor complex to attract cell extensions. EVA-1 is a conserved transmembrane protein with predicted galactose-binding lectin domains. EVA-1 functions in the same pathway as MADD-4, physically interacts with both MADD-4 and UNC-40, and enhances UNC-40's sensitivity to the MADD-4 cue. This enhancement is especially important in the presence of UNC-6. In EVA-1's absence, UNC-6 interferes with UNC-40's responsiveness to MADD-4; in UNC-6's absence, UNC-40's responsiveness to MADD-4 is less dependent on EVA-1. By enabling UNC-40 to respond to MADD-4 in the presence of UNC-6, EVA-1 may increase the precision by which UNC-40-directed processes can reach their MADD-4-expressing targets within a field of the UNC-6 guidance cue.
Author Summary
During animal development, cells and cell extensions migrate along stereotypical paths to their target destination by interacting with guidance cues in their environment. The guidance receptors on the surface of these cells can each interact with several different cues, and many of the cues can each interact with multiple receptors. How a migrating cell can reach its target amid this apparent receptor-cue promiscuity is poorly understood. Here, we extend our earlier investigation of how the UNC-40 receptor, which is known to interact with the UNC-6 guidance cue, mediates attraction towards the MADD-4 guidance cue. We show that another transmembrane protein called EVA-1 increases the sensitivity of UNC-40 to MADD-4. This increase in sensitivity allows UNC-40 to respond to MADD-4 in the presence of UNC-6. Without EVA-1, UNC-6 dominates UNC-40 function and restricts its response to MADD-4. Hence, the presence of EVA-1 acts like a switch to change UNC-40's sensitivity from UNC-6 to MADD-4, and in turn allows UNC-40-expressing cells to migrate towards the source of MADD-4 within a field of the UNC-6 guidance cue.
PMCID: PMC4133157  PMID: 25122090
22.  WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation 
BMC Genomics  2013;14(Suppl 3):S6.
SNPs&GO is a method for the prediction of deleterious Single Amino acid Polymorphisms (SAPs) using protein functional annotation. In this work, we present the web server implementation of SNPs&GO (WS-SNPs&GO). The server is based on Support Vector Machines (SVM) and for a given protein, its input comprises: the sequence and/or its three-dimensional structure (when available), a set of target variations and its functional Gene Ontology (GO) terms. The output of the server provides, for each protein variation, the probabilities to be associated to human diseases.
The server consists of two main components, including updated versions of the sequence-based SNPs&GO (recently scored as one of the best algorithms for predicting deleterious SAPs) and of the structure-based SNPs&GO3d programs. Sequence and structure based algorithms are extensively tested on a large set of annotated variations extracted from the SwissVar database. Selecting a balanced dataset with more than 38,000 SAPs, the sequence-based approach achieves 81% overall accuracy, 0.61 correlation coefficient and an Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve of 0.88. For the subset of ~6,600 variations mapped on protein structures available at the Protein Data Bank (PDB), the structure-based method scores with 84% overall accuracy, 0.68 correlation coefficient, and 0.91 AUC. When tested on a new blind set of variations, the results of the server are 79% and 83% overall accuracy for the sequence-based and structure-based inputs, respectively.
WS-SNPs&GO is a valuable tool that includes in a unique framework information derived from protein sequence, structure, evolutionary profile, and protein function. WS-SNPs&GO is freely available at
PMCID: PMC3665478  PMID: 23819482
23.  Flaxseed Mitigates Acute Oxidative Lung Damage in a Mouse Model of Repeated Radiation and Hyperoxia Exposure Associated with Space Exploration 
Spaceflight missions may require crewmembers to conduct extravehicular activities (EVA). Pre-breathe protocols in preparation for an EVA entail 100% hyperoxia exposure that may last for a few hours and be repeated 2-3 times weekly. Each EVA is associated with additional challenges such as low levels of total body cosmic/galactic radiation exposure that may present a threat to crewmember health. We have developed a mouse model of total body radiation and hyperoxia exposure and identified acute damage of lung tissues. In the current study we evaluated the usefulness of dietary flaxseed (FS) as a countermeasure agent for such double-hit exposures.
We evaluated lung tissue changes 2 weeks post-initiation of exposure challenges. Mouse cohorts (n=5/group) were pre-fed diets containing either 0% FS or 10% FS for 3 weeks and exposed to: a) normoxia (Untreated); b) >95% O2 (O2); c) 0.25Gy single fraction gamma radiation (IR); or d) a combination of O2 and IR (O2+IR) 3 times per week for 2 consecutive weeks, where 8-hour hyperoxia treatments were spanned by normoxic intervals.
At 2 weeks post challenge, while control-diet fed mice developed significant lung injury and inflammation across all challenges, FS protected lung tissues by decreasing bronchoalveolar lavage fluid (BALF) neutrophils (p<0.003) and protein levels, oxidative tissue damage, as determined by levels of malondialdehyde (MDA) (p<0.008) and nitrosative stress as determined by nitrite levels. Lung hydroxyproline levels, a measure of lung fibrosis, were significantly elevated in mice fed 0% FS (p<0.01) and exposed to hyperoxia/radiation or the combination treatment, but not in FS-fed mice. FS also decreased levels of a pro-inflammatory, pro-fibrogenic cytokine (TGF-β1) gene expression levels in lung.
Flaxseed mitigated adverse effects in lung of repeat exposures to radiation/hyperoxia. This data will provide useful information in the design of countermeasures to early tissue oxidative damage associated with space exploration.
PMCID: PMC4333641  PMID: 25705570
Bronchoalveolar lavage; Double-hit; extravehicular activity; Hyperoxia; Inflammation; Lung fibrosis; Acute lung injury; Mouse model; Nitrosative stress; Oxidative stress; Radiation pneumonopathy; Space exploration; TGF-β1; Total body irradiation
24.  Protemot: prediction of protein binding sites with automatically extracted geometrical templates 
Nucleic Acids Research  2006;34(Web Server issue):W303-W309.
Geometrical analysis of protein tertiary substructures has been an effective approach employed to predict protein binding sites. This article presents the Protemot web server that carries out prediction of protein binding sites based on the structural templates automatically extracted from the crystal structures of protein–ligand complexes in the PDB (Protein Data Bank). The automatic extraction mechanism is essential for creating and maintaining a comprehensive template library that timely accommodates to the new release of PDB as the number of entries continues to grow rapidly. The design of Protemot is also distinctive by the mechanism employed to expedite the analysis process that matches the tertiary substructures on the contour of the query protein with the templates in the library. This expediting mechanism is essential for providing reasonable response time to the user as the number of entries in the template library continues to grow rapidly due to rapid growth of the number of entries in PDB. This article also reports the experiments conducted to evaluate the prediction power delivered by the Protemot web server. Experimental results show that Protemot can deliver a superior prediction power than a web server based on a manually curated template library with insufficient quantity of entries. Availability: .
PMCID: PMC1538868  PMID: 16845015
25.  IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences 
Nucleic Acids Research  2015;43(Web Server issue):W169-W173.
IntFOLD is an independent web server that integrates our leading methods for structure and function prediction. The server provides a simple unified interface that aims to make complex protein modelling data more accessible to life scientists. The server web interface is designed to be intuitive and integrates a complex set of quantitative data, so that 3D modelling results can be viewed on a single page and interpreted by non-expert modellers at a glance. The only required input to the server is an amino acid sequence for the target protein. Here we describe major performance and user interface updates to the server, which comprises an integrated pipeline of methods for: tertiary structure prediction, global and local 3D model quality assessment, disorder prediction, structural domain prediction, function prediction and modelling of protein-ligand interactions. The server has been independently validated during numerous CASP (Critical Assessment of Techniques for Protein Structure Prediction) experiments, as well as being continuously evaluated by the CAMEO (Continuous Automated Model Evaluation) project. The IntFOLD server is available at:
PMCID: PMC4489238  PMID: 25820431

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