Search results for "PHARMACOPHORE"

showing 10 items of 71 documents

Pharmacophore Models Derived from Molecular Dynamics Simulations of Protein-Ligand Complexes: A Case Study

2018

A single, merged pharmacophore hypothesis is derived combining 2000 pharmacophore models obtained during a 20 ns molecular dynamics simulation of a protein-ligand complex with one pharmacophore model derived from the initial PDB structure. This merged pharmacophore model contains all features that are present during the simulation and statistical information about the dynamics of the pharmacophore features. Based on the dynamics of the pharmacophore features we derive two distinctive feature patterns resulting in two different pharmacophore models for the analyzed system – the first model consists of features that are obtained from the PDB structure and the second uses two features that ca…

Models Molecular0301 basic medicineChemistry PharmaceuticalPlant ScienceMolecular Dynamics SimulationLigands01 natural sciencesStructure-Activity Relationship03 medical and health sciencesMolecular dynamicsComputational chemistry0103 physical sciencesDrug DiscoveryData MiningComputer SimulationPharmacology010304 chemical physicsChemistryProteinsHydrogen BondingGeneral Medicine030104 developmental biologyComplementary and alternative medicinePharmacophoreDatabases Nucleic AcidProtein ligandNatural Product Communications
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From Five- to Six-Membered Rings:  3,4-Diarylquinolinone as Lead for Novel p38MAP Kinase Inhibitors

2007

In this study we describe the design, synthesis, and biological evaluation of 3-(4-fluorophenyl)-4-pyridin-4-ylquinoline-2(1H)-one (5) as a new inhibitor of MAPK with a p38alphaMAPK IC50 of 1.8 muM. By keeping the common vicinal pyridine/4-F-phenyl pharmacophore, such as in prototypical imidazole 20 or isoxazole 13 but in 5 connected to the six-membered quinoline core, we were particularly interested in comparing biological activity, details of molecular geometry, and different binding modes of these compounds. Compounds 20 and 13 were active both in the p38alpha- and JNK3-assay, whereas 5 was selective for p38alpha, with no JNK3 inhibition. By comparing the X-ray structures of the compound…

Models MolecularBinding SitesMolecular modelStereochemistryQuinolineBiological activityQuinolonesCrystallography X-RayHeterocyclic Compounds 4 or More Ringsp38 Mitogen-Activated Protein KinasesStructure-Activity Relationshipchemistry.chemical_compoundchemistryMitogen-Activated Protein Kinase 10Drug DiscoveryPyridineMolecular MedicineImidazoleMoietyIsoxazolePharmacophoreJournal of Medicinal Chemistry
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Homology models of melatonin receptors: challenges and recent advances

2013

Melatonin exerts many of its actions through the activation of two G protein-coupled receptors (GPCRs), named MT1 and MT2. So far, a number of different MT1 and MT2 receptor homology models, built either from the prototypic structure of rhodopsin or from recently solved X-ray structures of druggable GPCRs, have been proposed. These receptor models differ in the binding modes hypothesized for melatonin and melatonergic ligands, with distinct patterns of ligand-receptor interactions and putative bioactive conformations of ligands. The receptor models will be described, and they will be discussed in light of the available information from mutagenesis experiments and ligand-based pharmacophore …

Models MolecularProtein Conformationhomology modelingMolecular Sequence DataDruggabilityReviewComputational biologyLigandsBioinformaticsCatalysisInorganic Chemistrylcsh:ChemistryStructure-Activity Relationshipmelatonin receptorsAnimalsHumansAmino Acid SequenceHomology modelingmelatonin receptors; MT1; MT2; homology modeling; structure-activity relationships; docking; molecular dynamics simulationsPhysical and Theoretical ChemistryReceptorMolecular Biologylcsh:QH301-705.5SpectroscopyMelatoninG protein-coupled receptorBinding SitesSequence Homology Amino AcidbiologyReceptor Melatonin MT2Receptor Melatonin MT1MT1Organic ChemistryMT2structure-activity relationshipsGeneral Medicinemolecular dynamics simulationsComputer Science ApplicationsMelatonergiclcsh:Biology (General)lcsh:QD1-999Structural Homology ProteinDocking (molecular)RhodopsindockingMutagenesis Site-Directedbiology.proteinPharmacophore
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Receptor-guided 3D-QSAR approach for the discovery of c-kit tyrosine kinase inhibitors

2012

Studies of the the three-dimensional quantitative structure–activity relationships for ninety-five c-kit tyrosine kinase inhibitors were performed. Based on a co-crystallized compound (1 T46), known inhibitors were aligned with c-kit by induced-fit docking, and multiple training/test set splitting was performed to validate the selected pharmacophore model. The best pharmacophore model consisted of five features: one hydrogen-bond donor and four aromatic rings. Reliable statistics were obtained (R 2 = 0.95, R pred 2  = 0.75), and the model was validated by using it to select c-kit inhibitors from a database; 82.1% of the hits it retrieved were active. Accordingly, our model can be reliably u…

Models MolecularQuantitative structure–activity relationshipChemistryStereochemistryOrganic ChemistryQuantitative Structure-Activity RelationshipC-kit . 3D-QSAR . Kohonen maps . Induced-fit dockingSettore CHIM/08 - Chimica FarmaceuticaCatalysisComputer Science ApplicationsInorganic ChemistryProto-Oncogene Proteins c-kitComputational Theory and MathematicsDocking (molecular)Drug DiscoveryPhysical and Theoretical ChemistryPharmacophoreReceptorTyrosine kinaseProtein Kinase Inhibitors
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A3 adenosine receptor: Homology modeling and 3D-QSAR studies

2012

Adenosine receptors (AR) belong to the superfamily of G-protein-coupled receptors (GPCRs). They are divided into four subtypes (A1, A2A, A2B, and A3) [1], and can be distinguished on the basis of their distinct molecular structures, distinct tissues distribution, and selectivity for adenosine analogs [2,3]. The hA3R, the most recently identified adenosine receptor, is involved in a variety of intracellular signaling pathways and physiological functions [4]. Expression of A3R was reported to be elevated in cancerous tissues [5], and A3 antagonists have been proposed for therapeutic treatments of cancer. The recent literature availability of crystal structure of hA2A adenosine receptor (PDB c…

Models MolecularQuantitative structure–activity relationshipReceptor Adenosine A2AAdenosine A3 Receptor AntagonistsQuantitative Structure-Activity RelationshipComputational biologyBiologyPharmacologyDrug DiscoveryMolecular dynamics simulationMaterials ChemistrymedicineHumansAmino Acid SequenceHomology modelingPhysical and Theoretical ChemistryReceptorA3 INHIBITORS HOMOLOGY MODELING 3D-QSARSpectroscopyG protein-coupled receptorA3 ReceptorBinding SitesTriazinesReceptor Adenosine A3Intracellular Signaling Peptides and ProteinsTriazolesA3 ADENOSINE RECEPTORComputer Graphics and Computer-Aided DesignAdenosine receptorAdenosineSettore CHIM/08 - Chimica FarmaceuticaPharmacophoresHomology modellingPharmacophoreProtein Bindingmedicine.drug
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IKK-β inhibitors: An analysis of drug–receptor interaction by using Molecular Docking and Pharmacophore 3D-QSAR approaches

2010

Abstract The IKK kinases family represents a thrilling area of research because of its importance in regulating the activity of NF-kB transcription factors. The discovery of the central role played by IKK-β in the activation of transcription in response to apoptotic or inflammatory stimuli allowed to considerate its modulation as a promising tool for the treatment of chronic inflammation and cancer. To date, several IKK-β inhibitors have been discovered and tested. In this work, an analysis of the interactions between different classes of inhibitors and their biological target was performed, through the application of Molecular Docking and Pharmacophore/3D-QSAR approaches to a set of 141 in…

Models MolecularQuantitative structure–activity relationshipReceptors DrugMolecular Sequence DataQuantitative Structure-Activity RelationshipIκB kinaseComputational biologyPharmacologyBiologyMaterials ChemistryHumansAmino Acid SequenceNF-kBHomology modelingPhysical and Theoretical ChemistryProtein Kinase InhibitorsTranscription factorSpectroscopyIKK-betaIKK-beta inhibitors Molecular Docking Pharmacophore 3D-QSAR approachesBinding SitesPharmacophoreKinaseHomology modelingSettore CHIM/08 - Chimica FarmaceuticaComputer Graphics and Computer-Aided DesignI-kappa B KinaseMolecular DockingStructural Homology ProteinBiological targetDrug receptorPharmacophoreJournal of Molecular Graphics and Modelling
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BANΔIT: B’‐factor Analysis for Drug Design and Structural Biology

2020

The analysis of B‐factor profiles from X‐ray protein structures can be utilized for structure‐based drug design since protein mobility changes have been associated with the quality of protein‐ligand interactions. With the BANΔIT (B’‐factor analysis and ΔB’ interpretation toolkit), we have developed a JavaScript‐based browser application that provides a graphical user interface for the normalization and analysis of B’‐factor profiles. To emphasize the usability for rational drug design applications, we have analyzed a selection of crystallographic protein‐ligand complexes and have given exemplary conclusions for further drug optimization including the development of a B’‐factor‐supported pha…

Normalization (statistics)Source codeComputer scienceBioinformaticsmedia_common.quotation_subjectDrug designB-factorMolecular modelingWeb BrowserJavaScriptcomputer.software_genre01 natural sciences03 medical and health sciencesStructural BiologyFactor (programming language)Drug DiscoveryApplication NoteHumansProtein flexibilityProtease Inhibitors030304 developmental biologycomputer.programming_languagemedia_commonGraphical user interface0303 health sciencesbusiness.industrySARS-CoV-2Organic ChemistryComputational BiologyUsabilityAdenosine Monophosphate0104 chemical sciencesComputer Science ApplicationsCOVID-19 Drug Treatment010404 medicinal & biomolecular chemistryDrug DesignMolecular MedicineData miningPharmacophorebusinesscomputerMolecular Informatics
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Pharmacophore modelling as useful tool in the lead compounds identification and optimization

2012

The goal of computer-aided molecular design methods in modern medicinal chemistry is to reduce the overall cost and time associated to the discovery and development of a new drug by identifying the most promising candidates to focus the experimental efforts on. Very often, many drug discovery projects have reached already a well-advanced stage before detailed structural data on the protein target have become available. A possible consequence is that often, medicinal chemists develop novel compounds for a target using preliminary structure–activity information, together with the theoretical models of interactions. Only responses that are consistent with the working hypothesis contribute to a…

PHARMACOPHORE MODELLING LEAD IDENTIFICATION AND OPTIMIZATIONSettore CHIM/08 - Chimica Farmaceutica
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3D-QSAR pharmacophore modeling and in silico screening of new Bcl-xl inhibitors.

2010

Bcl-2 proteins family members play several roles in tumoral proliferation: they inhibit proapoptotic activity during oncogenesis, support tumor cells survival, induce chemoresistance. The discovery of new small inhibitors of Bcl-xl represents a new frontier for cancer treatment. In this study, a 3D-QSAR pharmacophore model was developed, based on 42 biarylacylsulfonamides, and used to understand the structural factors affecting the inhibitory potency of these derivatives. Aromatic, negative charge, and hydrogen bond acceptor effects contribute to the inhibitory activity. The model was then employed as 3D search query to screen ZINC drug-like database in order to select new scaffolds. Finall…

PharmacologyModels MolecularVirtual screeningQuantitative structure–activity relationshipTertiary amineMolecular modelChemistryIn silicoOrganic ChemistryMolecular Conformationbcl-X ProteinQuantitative Structure-Activity RelationshipGeneral MedicineSettore CHIM/08 - Chimica FarmaceuticaBiochemistryIn vivoDocking (molecular)Drug Discovery3D-QSAR Pharmacophore Modeling In Silico Screening Bcl-xl InhibitorsPharmacophoreEuropean journal of medicinal chemistry
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Fragment- and negative image-based screening of phosphodiesterase 10A inhibitors.

2019

A novel virtual screening methodology called fragment- and negative image-based (F-NiB) screening is introduced and tested experimentally using phosphodiesterase 10A (PDE10A) as a case study. Potent PDE10A-specific small-molecule inhibitors are actively sought after for their antipsychotic and neuroprotective effects. The F-NiB combines features from both fragment-based drug discovery and negative image-based (NIB) screening methodologies to facilitate rational drug discovery. The selected structural parts of protein-bound ligand(s) are seamlessly combined with the negative image of the target's ligand-binding cavity. This cavity- and fragment-based hybrid model, namely its shape and electr…

PharmacologyVirtual screening010405 organic chemistryDrug discoveryChemistryPhosphodiesterase InhibitorsPhosphoric Diester HydrolasesOrganic ChemistryFragment-based lead discoveryAb initioDrug Evaluation PreclinicalPhosphodiesteraseComputational biology01 natural sciencesBiochemistrySmall molecule0104 chemical sciencesMolecular Docking Simulation010404 medicinal & biomolecular chemistryDocking (molecular)Drug DiscoveryMolecular MedicineHumansPharmacophoreChemical biologydrug designREFERENCES
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