Search results for "complexity"

showing 10 items of 1094 documents

The Role of Low Complexity Regions in Protein Interaction Modes: An Illustration in Huntingtin

2021

Low complexity regions (LCRs) are very frequent in protein sequences, generally having a lower propensity to form structured domains and tending to be much less evolutionarily conserved than globular domains. Their higher abundance in eukaryotes and in species with more cellular types agrees with a growing number of reports on their function in protein interactions regulated by post-translational modifications. LCRs facilitate the increase of regulatory and network complexity required with the emergence of organisms with more complex tissue distribution and development. Although the low conservation and structural flexibility of LCRs complicate their study, evolutionary studies of proteins …

Protein Conformation alpha-Helical0301 basic medicineNetwork complexityHuntingtinintrinsically disordered regionsAmino Acid MotifsComputational biologyBiologyprotein interactionsArticlecompositionally biased regionsCatalysisProtein–protein interactionlcsh:ChemistryEvolution MolecularInorganic ChemistryLow complexity03 medical and health sciencesProtein DomainsProtein Interaction MappingAnimalsHumansp300-CBP Transcription FactorsAmino Acid SequenceProtein Interaction MapsHuntingtinTissue distributionPhysical and Theoretical Chemistrylcsh:QH301-705.5Molecular BiologySpectroscopyHuntingtin Protein030102 biochemistry & molecular biologyOrganic ChemistryNuclear Proteinsp120 GTPase Activating ProteinGeneral MedicineMultiple modesSynapsinslow complexity regionsComputer Science ApplicationshomorepeatsMicroscopy Electron030104 developmental biologylcsh:Biology (General)lcsh:QD1-999Sequence AlignmentFunction (biology)Protein BindingInternational Journal of Molecular Sciences
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Disentangling the complexity of low complexity proteins

2020

Abstract There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichot…

Protein ConformationComputer scienceReview ArticleComputational biologyMeasure (mathematics)Evolution MolecularLow complexity03 medical and health sciencesProtein DomainsAmino Acid Sequencestructure[SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry Molecular Biology/Biochemistry [q-bio.BM]Databases ProteinMolecular Biology030304 developmental biologyStructure (mathematical logic)0303 health sciencesSequence[SCCO.NEUR]Cognitive science/Neurosciencecomposition bias030302 biochemistry & molecular biologyProteinsdisorderlow complexity regionsStructure and function[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]AlgorithmsInformation SystemsBriefings in Bioinformatics
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Efficient computation of root mean square deviations under rigid transformations

2013

The computation of root mean square deviations (RMSD) is an important step in many bioinformatics applications. If approached naively, each RMSD computation takes time linear in the number of atoms. In addition, a careful implementation is required to achieve numerical stability, which further increases runtimes. In practice, the structural variations under consideration are often induced by rigid transformations of the protein, or are at least dominated by a rigid component. In this work, we show how RMSD values resulting from rigid transformations can be computed in constant time from the protein's covariance matrix, which can be precomputed in linear time. As a typical application scenar…

Protein ConformationCovariance matrixComputationComputational BiologyProteinsGeometryGeneral ChemistryRoot mean squareComputational MathematicsComputer SimulationStatistical physicsCluster analysisConstant (mathematics)Time complexityRigid transformationMathematicsNumerical stabilityJournal of Computational Chemistry
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A reduction of protein specific motions in co-ligated myoglobin embedded in a trehalose glass

2000

Protein DenaturationProtein FoldingMyoglobinProtein ConformationChemistryTemperatureBiophysicsMembrane biologyTrehaloseGeneral MedicineTrehaloseReduction (complexity)Spectroscopy Mossbauerchemistry.chemical_compoundBiochemistryMyoglobinAnimalsGlassHorsesLeast-Squares AnalysisEuropean Biophysics Journal
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A Stevedore's protein knot.

2009

Protein knots, mostly regarded as intriguing oddities, are gradually being recognized as significant structural motifs. Seven distinctly knotted folds have already been identified. It is by and large unclear how these exceptional structures actually fold, and only recently, experiments and simulations have begun to shed some light on this issue. In checking the new protein structures submitted to the Protein Data Bank, we encountered the most complex and the smallest knots to date: A recently uncovered α-haloacid dehalogenase structure contains a knot with six crossings, a so-called Stevedore knot, in a projection onto a plane. The smallest protein knot is present in an as yet unclassified …

Protein FoldingHydrolasesProtein ConformationComputational Biology/Macromolecular Structure Analysis02 engineering and technologyBiologyMolecular Dynamics SimulationComputational Biology/Molecular DynamicsCombinatorics03 medical and health sciencesCellular and Molecular NeuroscienceKnot (unit)Protein structureGeneticsStructural motifDatabases ProteinMolecular Biologylcsh:QH301-705.5Ecology Evolution Behavior and Systematics030304 developmental biology0303 health sciencesTopological complexityQuantitative Biology::BiomoleculesEcologycomputer.file_format021001 nanoscience & nanotechnologyProtein Data BankMathematics::Geometric TopologyComputational Theory and MathematicsBiochemistrylcsh:Biology (General)Modeling and SimulationProtein foldingStevedore knot0210 nano-technologySingle loopcomputerResearch ArticlePLoS Computational Biology
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RepeatsDB

2015

Database of annotated tandem repeat protein structures.

Protein structure analysisSequence composition complexity and repeats
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Assessing the low complexity of protein sequences via the low complexity triangle.

2020

Background Proteins with low complexity regions (LCRs) have atypical sequence and structural features. Their amino acid composition varies from the expected, determined proteome-wise, and they do not follow the rules of structural folding that prevail in globular regions. One way to characterize these regions is by assessing the repeatability of a sequence, that is, calculating the local propensity of a region to be part of a repeat. Results We combine two local measures of low complexity, repeatability (using the RES algorithm) and fraction of the most frequent amino acid, to evaluate different proteomes, datasets of protein regions with specific features, and individual cases of proteins…

ProteomeProteomesComputer scienceProtein SequencingBiochemistryDatabase and Informatics MethodsSequence Analysis ProteinProtein methodsPeptide sequencechemistry.chemical_classification0303 health sciencesSequenceMultidisciplinary030302 biochemistry & molecular biologyQRGenomicsAmino acidTandem RepeatsProteomeAmino Acid AnalysisMedicineSequence AnalysisResearch ArticleRepetitive Sequences Amino AcidBioinformaticsSequence analysisScienceResearch and Analysis MethodsGenome Complexity03 medical and health sciencesProtein DomainsAmino Acid Sequence AnalysisTandem repeatGeneticsHumansFraction (mathematics)Repeated SequencesAmino Acid SequenceMolecular Biology TechniquesSequencing TechniquesRepresentation (mathematics)Molecular Biology030304 developmental biologyMolecular Biology Assays and Analysis Techniquesbusiness.industryBiology and Life SciencesProteinsComputational BiologyPattern recognitionchemistryGlobular ProteinsArtificial intelligencebusinessPLoS ONE
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The Conservation of Low Complexity Regions in Bacterial Proteins Depends on the Pathogenicity of the Strain and Subcellular Location of the Protein

2021

Low complexity regions (LCRs) in proteins are characterized by amino acid frequencies that differ from the average. These regions evolve faster and tend to be less conserved between homologs than globular domains. They are not common in bacteria, as compared to their prevalence in eukaryotes. Studying their conservation could help provide hypotheses about their function. To obtain the appropriate evolutionary focus for this rapidly evolving feature, here we study the conservation of LCRs in bacterial strains and compare their high variability to the closeness of the strains. For this, we selected 20 taxonomically diverse bacterial species and obtained the completely sequenced proteomes of t…

Proteomics0301 basic medicinelcsh:QH426-470030106 microbiologyBiologyArticlecompositionally biased regionsEvolution MolecularLow complexity03 medical and health sciencesBacterial ProteinsSequence Analysis ProteinGeneticsExtracellularGenetics (clinical)chemistry.chemical_classificationBacteriaVirulenceStrain (chemistry)Computational Biologybiology.organism_classificationlow complexity regionsAmino acidhomorepeatslcsh:Genetics030104 developmental biologychemistryEvolutionary biologybacterial strainsProteomeorthologyBacterial outer membraneBacteriaFunction (biology)host–pathogen interactionsGenes
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REP2

2021

REP2 is a web server to detect common tandem repeats in protein sequences.

Proteomicseducationinformation scienceProteinsnatural sciencesSequence composition complexity and repeats
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A Dynamic Distributed Algorithm for Multicast Path Setup

2005

In the past few years, there has been a considerable work on multicast route selection techniques, with the aim to design scalable protocols which can guarantee an efficient use of network resources. Steiner tree-based multicast algorithms produce optimal trees, but they are prohibitively expensive. For this reason, heuristic methods are generally employed. Conventional centralized Steiner heuristics provide effective solutions, but they are unpractical for large networks, since they require a complete knowledge of the network topology. In this paper, we propose a new distributed approach that is efficient and suitable for real network adoption. Performance evaluation indicates that it outp…

Protocol Independent MulticastMulticastComputer scienceDistributed computingDistance Vector Multicast Routing ProtocolNetwork topologySteiner tree problemsymbols.namesakeSource-specific multicastDistributed algorithmReliable multicastConvergence (routing)symbolsMulticast transmission Steiner Tree Routing protocolXcastCommunication complexityPragmatic General Multicast
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