Search results for "Protein structure prediction"

showing 9 items of 9 documents

Fasciola spp: Mapping of the MF6 epitope and antigenic analysis of the MF6p/HDM family of heme-binding proteins

2017

MF6p/FhHDM-1 is a small cationic heme-binding protein which is recognized by the monoclonal antibody (mAb) MF6, and abundantly present in parenchymal cells and secreted antigens of Fasciola hepatica. Orthologs of this protein (MF6p/HDMs) also exist in other causal agents of important foodborne trematodiasis, such as Clonorchis sinensis, Opisthorchis viverrini and Paragonimus westermani. Considering that MF6p/FhHDM-1 is relevant for heme homeostasis in Fasciola and was reported to have immunomodulatory properties, this protein is expected to be a useful target for vaccination. Thus, in this study we mapped the epitope recognized by mAb MF6 and evaluated its antigenicity in sheep. The sequenc…

0301 basic medicineParagonimus westermaniFasciola sppPhysiologyProtein ConformationFlatwormslcsh:MedicineProtein Structure PredictionBiochemistryEpitopeAntigenicEpitopes0302 clinical medicineAnimal CellsImmune PhysiologyMedicine and Health SciencesMacromolecular Structure AnalysisMF6p/HDMEnzyme-Linked Immunoassayslcsh:ScienceMammalsNeuronsImmune System ProteinsMultidisciplinaryFasciolabiologyVaccinationEukaryotaAntibodies MonoclonalRuminantsDendritic StructureVertebratesCellular TypesAntibodyResearch ArticleHemeproteinsProtein StructureAntigenicityFascioliasisHeme bindingImmunology030231 tropical medicineAntibodies HelminthEnzyme-Linked Immunosorbent AssayHemeResearch and Analysis MethodsTrematodesAntibodiesHeme-Binding Proteins03 medical and health sciencesHelminthsparasitic diseasesParasitic DiseasesFasciola hepaticaAnimalsImmunoassaysMolecular BiologySheeplcsh:ROrganismsBiology and Life SciencesProteinsCell BiologyDendritesNeuronal DendritesFasciola hepaticabiology.organism_classificationInvertebratesMolecular biologyFasciola030104 developmental biologyEpitope mappingCellular NeuroscienceAntigens HelminthAmniotesImmunologic Techniquesbiology.proteinlcsh:QCarrier ProteinsEpitope MappingNeuroscience
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Improving protein secondary structure predictions by prediction fusion

2009

Protein secondary structure prediction is still a challenging problem at today. Even if a number of prediction methods have been presented in the literature, the various prediction tools that are available on-line produce results whose quality is not always fully satisfactory. Therefore, a user has to know which predictor to use for a given protein to be analyzed. In this paper, we propose a server implementing a method to improve the accuracy in protein secondary structure prediction. The method is based on integrating the prediction results computed by some available on-line prediction tools to obtain a combined prediction of higher quality. Given an input protein p whose secondary struct…

CorrectnessComputer sciencemedia_common.quotation_subjectProtein structure predictioncomputer.software_genreSet (abstract data type)Global distance testHardware and ArchitectureSignal ProcessingQuality (business)Data miningBioinformatics Protein Secondary Structure Prediction ClassificationCASPProtein secondary structurecomputerSoftwareInformation Systemsmedia_commonData integrationInformation Fusion
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Finding optimal finite biological sequences over finite alphabets: the OptiFin toolbox

2017

International audience; In this paper, we present a toolbox for a specific optimization problem that frequently arises in bioinformatics or genomics. In this specific optimisation problem, the state space is a set of words of specified length over a finite alphabet. To each word is associated a score. The overall objective is to find the words which have the lowest possible score. This type of general optimization problem is encountered in e.g 3D conformation optimisation for protein structure prediction, or largest core genes subset discovery based on best supported phylogenetic tree for a set of species. In order to solve this problem, we propose a toolbox that can be easily launched usin…

FOS: Computer and information sciences0301 basic medicineTheoretical computer scienceOptimization problemComputer Science - Artificial IntelligenceComputer science[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]Quantitative Biology - Quantitative MethodsSet (abstract data type)[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing03 medical and health sciences[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]State spaceMetaheuristicQuantitative Methods (q-bio.QM)Protein structure prediction[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationToolboxCore (game theory)Artificial Intelligence (cs.AI)030104 developmental biology[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]FOS: Biological sciences[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Word (computer architecture)
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Exploration of Evolutionary Relations between Protein Structures

2008

We describe a new method for the exploration of evolutionary relations between protein structures.

GeneticsProtein structureChemistryProtein domainProtein designProtein function predictionProtein engineeringSupersecondary structureComputational biologyProtein structure predictionProtein tertiary structure
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Molecular basis of filamin a-filGAP interaction and its impairment in congenital disorders associated with filamin a mutations

2008

Background Mutations in filamin A (FLNa), an essential cytoskeletal protein with multiple binding partners, cause developmental anomalies in humans. Methodology/Principal Findings We determined the structure of the 23rd Ig repeat of FLNa (IgFLNa23) that interacts with FilGAP, a Rac-specific GTPase-activating protein and regulator of cell polarity and movement, and the effect of the three disease-related mutations on this interaction. A combination of NMR structural analysis and in silico modeling revealed the structural interface details between the C and D β-strands of the IgFLNa23 and the C-terminal 32 residues of FilGAP. Mutagenesis of the predicted key interface residues confirmed the b…

ImmunoprecipitationFilaminsMolecular Sequence Dataeducationlcsh:MedicineComputational Biology/Protein Structure PredictionBiologyFilaminCell Biology/Cell SignalingCongenital AbnormalitiesBiochemistry/Protein Folding03 medical and health sciences0302 clinical medicineProtein structureContractile ProteinsCell Biology/CytoskeletonFLNAHumansFLNBFLNCAmino Acid Sequencelcsh:Science030304 developmental biologyGenetics0303 health sciencesMultidisciplinaryBinding SitesMolecular StructureSequence Homology Amino AcidPoint mutationlcsh:RGTPase-Activating ProteinsMicrofilament Proteins3. Good healthBiochemistry/BioinformaticsMutationProtein foldinglcsh:Q118 Biological sciences030217 neurology & neurosurgeryResearch Article
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Protein structure prediction assisted with sparse NMR data in CASP13

2019

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein structure prediction. NOESY and 15 N-1 H residual dipolar coupling data, typical of that obtained for 15 N,13 C-enriched, perdeuterated proteins up to about 40 kDa, were simulated for 11 CASP13 targets ranging in size from 80 to 326 residues. For several targets, two prediction groups generated models that are more accurate than those produced using baseline methods. Real NMR data collected for a de novo designed protein were also provided to predictors, including one data set in which only backbone resonance assignments were available. Some NMR-assisted prediction groups also did very well with these data. CAS…

Models MolecularProtein FoldingMagnetic Resonance SpectroscopyProtein ConformationComputer scienceCrystallography X-RayBiochemistryArticle03 medical and health sciencesProtein structureStructural BiologyComputer SimulationCASPMolecular Biology030304 developmental biology0303 health sciences030302 biochemistry & molecular biologyProteinsReproducibility of ResultsRangingProtein structure predictionNmr dataData setResidual dipolar couplingTwo-dimensional nuclear magnetic resonance spectroscopyAlgorithmAlgorithmsProteins: Structure, Function, and Bioinformatics
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A computer system to perform structure comparison using TOPS representations of protein structure

2001

We describe the design and implementation of a fast topology-based method for protein structure comparison. The approach uses the TOPS topological representation of protein structure, aligning two structures using a common discovered pattern and generating measure of distance derived from an insert score. Heavy use is made of a constraint-based pattern-matching algorithm for TOPS diagrams that we have designed and described elsewhere (Bioinformatics 15(4) (1999) 317). The comparison system is maintained at the European Bioinformatics Institute and is available over the Web at tops.ebi.ac.uk/tops. Users submit a structure description in Protein Data Bank (PDB) format and can compare it with …

Protein structure databaseMeasure (data warehouse)Molecular StructureComputer scienceGeneral Chemical EngineeringProteinsSequence Homologycomputer.file_formatTOPSProtein structure predictioncomputer.software_genreProtein Data BankApplied Microbiology and BiotechnologyPattern Recognition AutomatedArtificial IntelligencePattern matchingData miningProtein topologyRepresentation (mathematics)computerAlgorithmsSoftwareBiotechnology
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Experimental Evaluation of Protein Secondary Structure Predictors

2009

Understanding protein biological function is a key issue in modern biology, which is largely determined by its 3D shape. Protein 3D shape, in its turn, is functionally implied by its amino acid sequence. Since the direct inspection of such 3D structures is rather expensive and time consuming, a number of software techniques have been developed in the last few years that predict a spatial model, either of the secondary or of the tertiary form, for a given target protein starting from its amino acid sequence. This paper offers a comparison of several available automatic secondary structure prediction tools. The comparison is of the experimental kind, where two relevant sets of proteins, a non…

Protein structure databasebusiness.industryProtein structure predictionBioinformaticsMachine learningcomputer.software_genreSet (abstract data type)Bioinformatics Protein PredictionTest caseGlobal distance testArtificial intelligenceCASPbusinessPeptide sequencecomputerProtein secondary structure
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New set of 2D/3D thermodynamic indices for proteins. A formalism based on "Molten Globule" theory

2010

Abstract We define eight new macromolecular indices, and several related descriptors for proteins. The coarse grained methodology used for its deduction ensures its fast execution and becomes a powerful potential tool to explore large databases of protein structures. The indices are intended for stability studies, predicting Φ -values, predicting folding rate constants, protein QSAR/QSPR as well as protein alignment studies. Also, these indices could be used as scoring function in protein-protein docking or 3D protein structure prediction algorithms and any others applications which need a numerical code for proteins and/or residues from 2D or 3D format.

Quantitative structure–activity relationshipComputer sciencePhysics and Astronomy(all)Protein structure predictionMolten globuleFolding degreeFormalism (philosophy of mathematics)Protein indicesProtein structureFPIDocking (molecular)Protein stabilityPhysical chemistryBiological systemStatistical potentialMacromoleculeProtein folding descriptor
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