Search results for "molecular dynamics simulation"

showing 10 items of 260 documents

How Can Interleukin-1 Receptor Antagonist Modulate Distinct Cell Death Pathways?

2018

Multiple mechanisms of cell death exist (apoptosis, necroptosis, pyroptosis) and the subtle balance of several distinct proteins and inhibitors tightly regulates the cell fate toward one or the other pathway. Here, by combining coimmunoprecipitation, enzyme assays, and molecular simulations, we ascribe a new role, within this entangled regulatory network, to the interleukin-1 receptor antagonist (IL-1Ra). Our study enlightens that IL-1Ra, which usually inhibits the inflammatory effects of IL-1α/β by binding to IL-1 receptor, under advanced pathological states prevents apoptosis and/or necroptosis by noncompetitively inhibiting the activity of caspase-8 and -9. Consensus docking, followed by…

0301 basic medicineProgrammed cell deathProtein ConformationGeneral Chemical EngineeringNecroptosis-Library and Information SciencesMolecular Dynamics SimulationInhibitor of apoptosis01 natural sciencesArticle03 medical and health sciences0103 physical sciencesReceptorsmedicineCaspaseCaspase 8010304 chemical physicsbiologyCell DeathChemistryNeurodegenerationPyroptosisComputational BiologyReceptors Interleukin-1General Chemistrymedicine.diseaseCaspase 9Computer Science ApplicationsCell biologyXIAPEnzyme ActivationInterleukin 1 Receptor Antagonist Protein030104 developmental biologyApoptosisbiology.proteinThermodynamicsInterleukin-1
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Searching for Chymase Inhibitors among Chamomile Compounds Using a Computational-Based Approach

2018

Inhibitors of chymase have good potential to provide a novel therapeutic approach for the treatment of cardiovascular diseases. We used a computational approach based on pharmacophore modeling, docking, and molecular dynamics simulations to evaluate the potential ability of 13 natural compounds from chamomile extracts to bind chymase enzyme. The results indicated that some chamomile compounds can bind to the active site of human chymase. In particular, chlorogenic acid had a predicted binding energy comparable or even better than that of some known chymase inhibitors, interacted stably with key amino acids in the chymase active site, and appeared to be more selective for chymase than other …

0301 basic medicineProteaseschlorogenic acidlcsh:QR1-502030204 cardiovascular system & hematologyMolecular Dynamics SimulationCrystallography X-RayLigandsBiochemistrylcsh:MicrobiologyArticleSerine03 medical and health sciences0302 clinical medicineChymasesCatalytic DomainHumanschamomilecardiovascular diseases; chamomile; chlorogenic acid; chymase; docking; matricin; molecular dynamics simulations; pharmacophore; Biochemistry; Molecular BiologyEnzyme InhibitorsMolecular Biologychymasechemistry.chemical_classificationBinding SitesbiologypharmacophoreChymaseActive sitemolecular dynamics simulationsmatricinAmino acidcardiovascular diseasesMolecular Docking Simulation030104 developmental biologyEnzymechemistryBiochemistryDocking (molecular)dockingbiology.proteinPharmacophoreBiomolecules
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Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport

2017

Ion translocation across biological barriers is a fundamental requirement for life. In many cases, controlling this process-for example with neuroactive drugs-demands an understanding of rapid and reversible structural changes in membrane-embedded proteins, including ion channels and transporters. Classical approaches to electrophysiology and structural biology have provided valuable insights into several such proteins over macroscopic, often discontinuous scales of space and time. Integrating these observations into meaningful mechanistic models now relies increasingly on computational methods, particularly molecular dynamics simulations, while surfacing important challenges in data manage…

0301 basic medicineProtein ConformationComputer sciencemedia_common.quotation_subjectData managementBiophysicsContext (language use)Molecular Dynamics SimulationBiochemistryIon ChannelsArticleStructure-Activity Relationship03 medical and health sciencesAnimalsHumansFunction (engineering)Biological sciencesClassical structureIon transportermedia_commonIon Transportbusiness.industryMembrane Transport ProteinsCell BiologyData science030104 developmental biologyStructural biologybusinessIon Channel GatingProtein BindingBiochimica et Biophysica Acta (BBA) - Biomembranes
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Insights into the inhibited form of the redox-sensitive SufE-like sulfur acceptor CsdE

2017

17 p.-8 fig.

0301 basic medicineProtein ConformationDimerlcsh:MedicineMolecular DynamicsCrystallography X-RayPhysical ChemistryBiochemistryDEAD-box RNA HelicasesMolecular dynamicschemistry.chemical_compoundComputational ChemistryNucleophileBiochemical Simulationslcsh:ScienceMultidisciplinaryCrystallographyChemistryOrganic CompoundsPhysicsEscherichia coli ProteinsCondensed Matter Physics3. Good healthPhysical sciencesChemistryCarbon-Sulfur LyasesBiochemistryCrystal StructureResearch ArticleChemical ElementsProtein subunitChemical physicschemistry.chemical_elementOxidative phosphorylationMolecular Dynamics Simulation03 medical and health sciencesThiolsEscherichia coliSolid State PhysicsProtein Interaction Domains and MotifsChemical BondingOrganic Chemistrylcsh:RChemical CompoundsBiology and Life SciencesComputational BiologyDimers (Chemical physics)Hydrogen BondingCell BiologySulfurAcceptorRedox sensitiveOxidative Stress030104 developmental biologyBiophysicslcsh:QProtein MultimerizationSulfur
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Evaluating the stability of pharmacophore features using molecular dynamics simulations.

2016

Abstract Molecular dynamics simulations of twelve protein—ligand systems were used to derive a single, structure based pharmacophore model for each system. These merged models combine the information from the initial experimental structure and from all snapshots saved during the simulation. We compared the merged pharmacophore models with the corresponding PDB pharmacophore models, i.e., the static models generated from an experimental structure in the usual manner. The frequency of individual features, of feature types and the occurrence of features not present in the static model derived from the experimental structure were analyzed. We observed both pharmacophore features not visible in …

0301 basic medicineProtein FlexibilityProtein ConformationBiophysicsStability (learning theory)Molecular Dynamics SimulationLigands01 natural sciencesBiochemistryLigandScoutSet (abstract data type)03 medical and health sciencesMolecular dynamicsComputational chemistryFeature (machine learning)Pharmacophore ModelingSensitivity (control systems)Molecular BiologyBinding Sites010405 organic chemistryChemistryStructure-based Pharmacophore ModelingMolecular DynamicProteinsHydrogen BondingCell Biology0104 chemical sciences030104 developmental biologyRankingModels ChemicalDrug DesignPharmacophoreBiological systemProtein BindingBiochemical and biophysical research communications
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Recent advances on CDK inhibitors: An insight by means of in silico methods

2017

The cyclin dependent kinases (CDKs) are a small family of serine/threonine protein kinases that can act as a potential therapeutic target in several proliferative diseases, including cancer. This short review is a survey on the more recent research progresses in the field achieved by using in silico methods. All the "armamentarium" available to the medicinal chemists (docking protocols and molecular dynamics, fragment-based, de novo design, virtual screening, and QSAR) has been employed to the discovery of new, potent, and selective inhibitors of cyclin dependent kinases. The results cited herein can be useful to understand the nature of the inhibitor-target interactions, and furnish an ins…

0301 basic medicineQuantitative structure–activity relationshipMolecular dynamicIn silicoCDKQuantitative Structure-Activity RelationshipAntineoplastic AgentsComputational biologyMolecular Dynamics SimulationBioinformatics01 natural sciencesSerine03 medical and health sciencesCyclin-dependent kinaseNeoplasmsDrug DiscoveryAnimalsHumansProtein Kinase InhibitorsPharmacologyVirtual screeningHVTSbiologyChemistryKinaseQSARDrug Discovery3003 Pharmaceutical ScienceOrganic ChemistryGeneral MedicineCyclin-Dependent Kinases0104 chemical sciencesMolecular Docking Simulation010404 medicinal & biomolecular chemistry030104 developmental biologyDocking (molecular)Drug Designbiology.proteinComputer-Aided DesignIn silico methodMolecular modelling
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Assessment of in vivo organ-uptake and in silico prediction of CYP mediated metabolism of DA-Phen, a new dopaminergic agent

2017

Abstract The drug development process strives to predict metabolic fate of a drug candidate, together with its uptake in major organs, whether they act as target, deposit or metabolism sites, to the aim of establish a relationship between the pharmacodynamics and the pharmacokinetics and highlight the potential toxicity of the drug candidate. The present study was aimed at evaluating the in vivo uptake of 2-Amino-N-[2-(3,4-dihydroxy-phenyl)-ethyl]-3-phenyl-propionamide (DA-Phen) − a new dopaminergic neurotransmission modulator, in target and non-target organs of animal subjects and integrating these data with SMARTCyp results, an in silico method that predicts the sites of cytochrome P450-m…

0301 basic medicineSMARTCyp predictionIn silicoDopaminePhenylalanineDopamine AgentsPharmacologyBiologyMolecular Dynamics SimulationBiochemistry03 medical and health sciencesPharmacokineticsCytochrome P-450 Enzyme SystemStructural BiologyIn vivoDopaminein silico metabolism predictionmedicineDa-PhenAnimalsComputer SimulationRats WistarOrganic ChemistryDopaminergicBrain homogenate analysiProdrugRatsComputational Mathematics030104 developmental biologyDrug developmentSettore CHIM/09 - Farmaceutico Tecnologico ApplicativoPharmacodynamicsOrgan uptakeInjections Intraperitonealmedicine.drug
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Exploring Strategies for Labeling Viruses with Gold Nanoclusters through Non-equilibrium Molecular Dynamics Simulations.

2017

Biocompatible gold nanoclusters can be utilized as contrast agents in virus imaging. The labeling of viruses can be achieved noncovalently but site-specifically by linking the cluster to the hydrophobic pocket of a virus via a lipid-like pocket factor. We have estimated the binding affinities of three different pocket factors of echovirus 1 (EV1) in molecular dynamics simulations combined with non-equilibrium free-energy calculations. We have also studied the effects on binding affinities with a pocket factor linked to the Au102pMBA44 nanocluster in different protonation states. Although the absolute binding affinities are over-estimated for all the systems, the trend is in agreement with r…

0301 basic medicineStereochemistryBiomedical EngineeringPalmitic AcidPharmaceutical ScienceMetal NanoparticlesBioengineeringProtonationMolecular Dynamics SimulationLigandsAntiviral AgentsNanoclusters03 medical and health sciencesMolecular dynamicschemistry.chemical_compoundCapsidCluster (physics)Moleculeta116OxazolesBinding affinitiesEnterovirusPharmacologyOxadiazolesBinding Sitesta114labeling virusesChemistryOrganic ChemistryBiocompatible materialCrystallography030104 developmental biologyThermodynamicsnon-equilibrium molecular dynamicsGoldgold nanoclustersHydrophobic and Hydrophilic InteractionsDerivative (chemistry)BiotechnologyBioconjugate chemistry
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2-methoxyestradiol impacts on amino acids-mediated metabolic reprogramming in osteosarcoma cells by interaction with NMDA receptor

2017

Deregulation of serine and glycine metabolism, have been identified to function as metabolic regulators in supporting tumor cell growth. The role of serine and glycine in regulation of cancer cell proliferation is complicated, dependent on concentrations of amino acids and tissue-specific. D-serine and glycine are coagonists of N-methyl-D-aspartate receptor subunit GRIN1. Importantly, NMDA receptors are widely expressed in cancer cells and play an important role in regulation of cell death, proliferation and metabolism of numerous malignancies. The aim of the present work was to associate the metabolism of glycine and D-serine with the anticancer activity of 2-methoxyestradiol. 2-methoxyest…

0301 basic medicineTime Factors2-methoxyestradiol neuronal nitric oxide synthase D-serine glycine osteosarcomaPhysiologyClinical BiochemistryNitric Oxide Synthase Type ISerine0302 clinical medicineCell MovementSerinechemistry.chemical_classificationMembrane Potential MitochondrialOsteosarcomaEstradiolTubulin ModulatorsAmino acidMolecular Docking Simulation030220 oncology & carcinogenesisMCF-7 CellsNMDA receptorOsteosarcomaFemalemedicine.drugProtein BindingSignal TransductionProgrammed cell deathGlycineAntineoplastic AgentsBone NeoplasmsBreast NeoplasmsNerve Tissue ProteinsBiologyMolecular Dynamics SimulationReceptors N-Methyl-D-Aspartate03 medical and health sciencesStructure-Activity RelationshipProtein DomainsmedicineHumans2-MethoxyestradiolCell ProliferationBinding SitesDose-Response Relationship DrugCell BiologyMetabolismmedicine.disease2-Methoxyestradiol030104 developmental biologychemistryCancer cellCancer researchEnergy Metabolism
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Interaction of C 60 fullerenes with asymmetric and curved lipid membranes: a molecular dynamics study

2015

Interaction of fullerenes with asymmetric and curved DOPC/DOPS bicelles is studied by means of coarse-grained molecular dynamics simulations. The effects caused by asymmetric lipid composition of the membrane leaflets and the curvature of the membrane are analyzed. It is shown that the aggregates of fullerenes prefer to penetrate into the membrane in the regions of the moderately positive mean curvature. Upon penetration into the hydrophobic core of the membrane fullerenes avoid the regions of the extreme positive or the negative curvature. Fullerenes increase the ordering of lipid tails, which are in direct contact with them, but do not influence other lipids significantly. Our data sugges…

0301 basic medicine[ SDV.BBM.BP ] Life Sciences [q-bio]/Biochemistry Molecular Biology/BiophysicsFullereneLipid BilayersGeneral Physics and AstronomyPhosphatidylserinesModel lipid bilayerMolecular Dynamics SimulationCurvatureQuantitative Biology::Cell BehaviorQuantitative Biology::Subcellular Processes03 medical and health sciencesMolecular dynamicsPhysics::Atomic and Molecular ClustersOrganic chemistryPhysical and Theoretical ChemistryComputingMilieux_MISCELLANEOUSPhysics::Biological PhysicsMean curvatureChemistryPenetration (firestop)[SDV.BBM.BP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Biophysics030104 developmental biologyMembraneMembrane curvatureBiophysicsPhosphatidylcholineslipids (amino acids peptides and proteins)Fullerenes
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