Search results for "relationship"

showing 10 items of 3616 documents

3D-Chiral quadratic indices of the ‘molecular pseudograph’s atom adjacency matrix’ and their application to central chirality codification: classific…

2004

Quadratic indices of the 'molecular pseudograph's atom adjacency matrix' have been generalized to codify chemical structure information for chiral drugs. These 3D-chiral quadratic indices make use of a trigonometric 3D-chirality correction factor. These indices are nonsymmetric and reduced to classical (2D) descriptors when symmetry is not codified. By this reason, it is expected that they will be useful to predict symmetry-dependent properties. 3D-Chirality quadratic indices are real numbers and thus, can be easily calculated in TOMOCOMD-CARDD software. These descriptors circumvent the inability of conventional 2D quadratic indices (Molecules 2003, 8, 687-726. http://www.mdpi.org) and othe…

Models MolecularQuantitative structure–activity relationshipChemistryStereochemistryOrganic ChemistryClinical BiochemistryStability (learning theory)Computational BiologyQuantitative Structure-Activity RelationshipPharmaceutical ScienceAngiotensin-Converting Enzyme InhibitorsStereoisomerismLinear discriminant analysisBiochemistryCross-validationQuadratic equationTest setDrug DiscoveryLinear regressionReceptors sigmaMolecular MedicineApplied mathematicsAdjacency matrixMolecular BiologyBioorganic & Medicinal Chemistry
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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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QSPR prediction of retention times of phenylurea herbicides by biological plastic evolution.

2012

A simple/sensitive high-performance liquid chromatographic method, with ultraviolet (UV) detection, was developed for phenylurea-herbicide analysis, which involves preconcentration using solid-phase extraction. Mobile phase was acetonitrile/water at flow-rate of 1 mL.min-1 with direct UV absorbance detection at 210 nm. Analyte separation studied on a C18 column was applied successfully to herbicide analysis in soft drink's brands and tap water. Good linearity/repeatability was observed for all pesticides. Retention times increase as: metoxuron < monuron < diuron < matazachlor < linuron. They are modelled by structure-property relations. The effect of different types of features is analyzed:…

Models MolecularQuantitative structure–activity relationshipEnthalpyAnalytical chemistryQuantitative Structure-Activity RelationshipToxicologychemistry.chemical_compoundTap waterWater SupplyPhase (matter)Water Pollution ChemicalMedicinePharmacology (medical)AcetonitrileChromatography High Pressure LiquidPharmacologybusiness.industryHerbicidesPhenylurea CompoundsSolvationMoment (mathematics)DipolechemistryMultivariate AnalysisRegression AnalysisThermodynamicsbusinessCurrent drug safety
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Atom-based Stochastic and non-Stochastic 3D-Chiral Bilinear Indices and their Applications to Central Chirality Codification

2006

Abstract Non-stochastic and stochastic 2D bilinear indices have been generalized to codify chemical structure information for chiral drugs, making use of a trigonometric 3D-chirality correction factor. In order to evaluate the effectiveness of this novel approach in drug design we have modeled the angiotensin-converting enzyme inhibitory activity of perindoprilate's σ-stereoisomers combinatorial library. Two linear discriminant analysis models, using non-stochastic and stochastic linear indices, were obtained. The models had shown an accuracy of 95.65% for the training set and 100% for the external prediction set. Next the prediction of the σ-receptor antagonists of chiral 3-(3-hydroxypheny…

Models MolecularQuantitative structure–activity relationshipIndolesStereochemistryStatic ElectricityQuantitative Structure-Activity RelationshipBilinear interpolationAngiotensin-Converting Enzyme InhibitorsIn Vitro TechniquesSet (abstract data type)PiperidinesLinear regressionMaterials ChemistryReceptors sigmaOrder (group theory)Applied mathematicsComputer SimulationPhysical and Theoretical ChemistrySpectroscopyMathematicsTranscortinStochastic ProcessesChemistryAtom (order theory)StereoisomerismLinear discriminant analysisComputer Graphics and Computer-Aided DesignData setDrug DesignLinear ModelsSteroidsTrigonometryChirality (chemistry)Proceedings of The 10th International Electronic Conference on Synthetic Organic Chemistry
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Molecular basis of the interaction of novel tributyltin(IV) 2/4-[(E)-2-(aryl)-1-diazenyl] benzoates endowed with an improved cytotoxic profile: Synth…

2010

A series of tributyltin(IV) complexes based on 2/4-[(E)-2-(aryl)-1-diazenyl]benzoate ligands was synthesized, wherein the position of the carboxylate and aryl substituents (methyl, tert-butyl and hydroxyl) varies. The complexes, Bu(3)SnL(1-4)H (1-4), have been structurally characterized by elemental analysis and IR, NMR ((1)H, (13)C, and (119)Sn) and (119)Sn Mossbauer spectroscopy. All have a tetrahedral geometry in solution and a trigonal bipyramidal geometry in the solid-state, except for Bu(3)SnL(4)H (4) that was ascertained to have tetrahedral coordination by X-ray crystallography. Cytotoxicity studies were carried out on human tumor cell lines A498 (renal cancer), EVSA-T (mammary cance…

Models MolecularQuantitative structure–activity relationshipMagnetic Resonance SpectroscopyStereochemistryCell SurvivalANTITUMOR-ACTIVITYHydrophobicityQuantitative Structure-Activity RelationshipAntineoplastic AgentsCrystallography X-RayBiochemistryBenzoatesVALIDATIONInorganic Chemistrychemistry.chemical_compoundAnti-cancer drugCell Line TumorOrganotin CompoundsTRIORGANOTIN(IV) COMPLEXESHumansCRYSTAL-STRUCTURESCarboxylateOPTIMIZATIONArylazobenzoateSpectroscopyX-ray crystallographyMolecular StructureQSARArylTetrahedral molecular geometryNuclear magnetic resonance spectroscopyBenzoatesTributyltin(IV) compoundTrigonal bipyramidal molecular geometryMOSQUITO LARVAEchemistryCELL-DEATHDocking (molecular)Settore CHIM/03 - Chimica Generale E InorganicaDocking studies RIBONUCLEOTIDE REDUCTASE INHIBITORSEMIEMPIRICAL METHODSTrialkyltin CompoundsCell lineAEDES-AEGYPTI
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Identification of New Templates for the Synthesis of BEA, BEC, and ISV Zeolites Using Molecular Topology and Monte Carlo Techniques

2020

The presence of organic structure directing agents (templates) in the synthesis of zeolites allows the synthesis to be directed, in many cases, toward structures in which there is a large stabilization between the template and the zeolite micropore due to dispersion interactions. Although other factors are also important (temperature, pH, Si/Al ratio, etc.), systems with strong zeolite-template interactions are good candidates for an application of new computational algorithms, for instance those based in molecular topology (MT), that can be used in combination with large databases of organic molecules. Computational design of new templates allows the synthesis of existing and new zeolites …

Models MolecularQuantitative structure–activity relationshipMaterials science010304 chemical physicsGeneral Chemical EngineeringMonte Carlo methodGeneral ChemistryMicroporous materialLibrary and Information Sciences01 natural sciences0104 chemical sciencesComputer Science Applications010404 medicinal & biomolecular chemistryIdentification (information)Template0103 physical sciencesZeolitesMoleculeMinificationMolecular topologyBiological systemMonte Carlo MethodJournal of Chemical Information and Modeling
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Discrimination and selection of new potential antibacterial compounds using simple topological descriptors.

2003

Abstract The aim of the work was to discriminate between antibacterial and non-antibacterial drugs by topological methods and to select new potential antibacterial agents from among new structures. The method used for antibacterial activity selection was a linear discriminant analysis (LDA). It is possible to obtain a QSAR interpretation of the information contained in the discriminant function. We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and selection of new antibacterial agents.

Models MolecularQuantitative structure–activity relationshipMolecular StructureComputer sciencebusiness.industryDiscriminant AnalysisQuantitative Structure-Activity RelationshipPattern recognitionLinear discriminant analysisTopologyComputer Graphics and Computer-Aided DesignDiscriminant function analysisAnti-Infective AgentsSimple (abstract algebra)Drug DesignMaterials ChemistryComputer SimulationArtificial intelligencePhysical and Theoretical ChemistryAntibacterial activitybusinessSpectroscopySelection (genetic algorithm)SoftwareJournal of molecular graphicsmodelling
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TOMOCOMD-CARDD descriptors-based virtual screening of tyrosinase inhibitors: evaluation of different classification model combinations using bond-bas…

2006

Abstract A new set of bond-level molecular descriptors (bond-based linear indices) are used here in QSAR (quantitative structure–activity relationship) studies of tyrosinase inhibitors, for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones. A database of 246 compounds was collected for this study; all organic chemicals were reported as tyrosinase inhibitors; they had great structural diversity. This dataset can be considered as a helpful tool, not only for theoretical chemists but also for other researchers in this area. The set used as inactive has 412 drugs with other clinical uses. Twelve LDA-based QSAR models were obtained, the first six us…

Models MolecularQuantitative structure–activity relationshipMolecular modelStereochemistryTyrosinaseClinical BiochemistryPharmaceutical ScienceQuantitative Structure-Activity RelationshipBiochemistryModels BiologicalChemometricsMolecular descriptorDrug DiscoveryComputer SimulationMolecular BiologyVirtual screeningMolecular StructureChemistryMonophenol MonooxygenaseOrganic ChemistryDiscriminant AnalysisLinear discriminant analysisModels ChemicalTopological indexMolecular MedicineBiological systemAgaricalesPeptidesAlgorithmsBioorganicmedicinal chemistry
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Structural, chemical topological, electrotopological and electronic structure hypotheses.

2003

The first important hypothesis in the prediction of properties of synthesized molecules is the structural hypothesis. In the study of drug-receptor interactions, the case where the three-dimensional structure of the receptor is known allows the application of molecular simulation and energy calculations to estimate the binding affinity for a proposed series of compounds. The chemical topological hypothesis permits the description of molecular structures without using concepts such as force or energy. These notions would not be as dominant as supposed since they should be able to be deduced from topology. Although topological descriptors are able to describe specific physicochemical properti…

Models MolecularQuantitative structure–activity relationshipProperty (philosophy)Similarity (geometry)Series (mathematics)Molecular StructureComputer scienceOrganic ChemistryStructure (category theory)Quantitative Structure-Activity RelationshipElectronsGeneral MedicineElectronic structureTopologyComputer Science ApplicationsInterpretation (model theory)Drug DiscoveryTopology (chemistry)Combinatorial chemistryhigh throughput screening
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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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