Search results for "Target peptide"

showing 2 items of 2 documents

Structural Basis of the High Affinity Interaction between the Alphavirus Nonstructural Protein-3 (nsP3) and the SH3 Domain of Amphiphysin-2

2016

We show that a peptide from Chikungunya virus nsP3 protein spanning residues 1728–1744 binds the amphiphysin-2 (BIN1) Src homology-3 (SH3) domain with an unusually high affinity (Kd 24 nM). Our NMR solution complex structure together with isothermal titration calorimetry data on several related viral and cellular peptide ligands reveal that this exceptional affinity originates from interactions between multiple basic residues in the target peptide and the extensive negatively charged binding surface of amphiphysin-2 SH3. Remarkably, these arginines show no fixed conformation in the complex structure, indicating that a transient or fluctuating polyelectrostatic interaction accounts for this …

0301 basic medicinenuclear magnetic resonance (NMR)Amino Acid MotifsStatic ElectricityPeptideTarget peptidePlasma protein bindingViral Nonstructural ProteinsBiologyhost-pathogen interactionBiochemistrySH3 domainsrc Homology Domainsamphiphysin SH3Structure-Activity Relationship03 medical and health sciencesProtein structuredynaminHumansShort linear motifprotein structureNuclear Magnetic Resonance BiomolecularMolecular BiologySrc homology 3 domain (SH3 domain)Adaptor Proteins Signal Transducingchemistry.chemical_classificationTumor Suppressor Proteinsta1182Nuclear ProteinsIsothermal titration calorimetryCell Biologyintrinsically disordered protein030104 developmental biologychemistryBiochemistrynsP3Protein Structure and FoldingAmphiphysinBiophysicsPeptidesChikungunya virusProtein BindingJournal of Biological Chemistry
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Prediction of Specific TCR-Peptide Binding From Large Dictionaries of TCR-Peptide Pairs

2019

Abstract The T cell repertoire is composed of T cell receptors (TCR) selected by their cognate MHC-peptides and naive TCR that do not bind known peptides. While the task of distinguishing a peptide-binding TCR from a naive TCR unlikely to bind any peptide can be performed using sequence motifs, distinguishing between TCRs binding different peptides requires more advanced methods. Such a prediction is the key for using TCR repertoires as disease-specific biomarkers. We here used large scale TCR-peptide dictionaries with state-of-the-art natural language processing (NLP) methods to produce ERGO (pEptide tcR matchinG predictiOn), a highly specific classifier to predict which TCR binds to which…

lcsh:Immunologic diseases. AllergyComputer scienceevaluation methodsT-LymphocytesT cellImmunologyReceptors Antigen T-CellEpitopes T-LymphocyteTarget peptidePeptide bindingPeptidechemical and pharmacologic phenomenaComputational biologyLigandsSoftware implementationautoencoder (AE)AntigenEvaluation methodsmedicineImmunology and AllergyHumansProtein Interaction Domains and MotifsEpitope specificityAntigensDatabases ProteinOriginal Researchchemistry.chemical_classificationBinding SitesT cell repertoireChemistryRepertoirelong short-term memory (LSTM)T-cell receptorepitope specificitydeep learninghemic and immune systemsmedicine.anatomical_structuremachine learningPeptidesSequence motiflcsh:RC581-607SoftwareProtein BindingSignal TransductionTCR repertoire analysisFrontiers in Immunology
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