Search results for "Quantitative Structure-Activity Relationship"

showing 10 items of 113 documents

Alzheimer: A Decade of Drug Design. Why Molecular Topology can be an Extra Edge?

2017

Background The last decade was characterized by a growing awareness about the severity of dementia in the field of age-related and no age-related diseases and about the importance to invest resources in the research of new, effective treatments. Among the dementias, Alzheimer's plays a substantial role because of its extremely high incidence and fatality. Several pharmacological strategies have been tried but still now, Alzheimer keeps being an untreatable disease. In literature, the number of QSAR related drug design attempts about new treatments for Alzheimer is huge, but only few results can be considered noteworthy. Providing a detailed analysis of the actual situation and reporting the…

Models Molecular0301 basic medicineDrugQuantitative structure–activity relationshiptopologyComputer sciencemedia_common.quotation_subjectdesignQuantitative Structure-Activity RelationshipHistory 21st CenturyArticle03 medical and health sciencesAlzheimer DiseasemedicineHumansDementiaPharmacology (medical)molecularTopology (chemistry)media_commonPharmacologyQSARdrugGeneral Medicinemedicine.diseaseDatabases BibliographicPsychiatry and Mental healthIdentification (information)030104 developmental biologyNeurologyRisk analysis (engineering)Drug DesignAlzheimerNeurology (clinical)Enhanced Data Rates for GSM EvolutionHigh incidenceMolecular topologyAntipsychotic AgentsCurrent Neuropharmacology
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State of the Art Review and Report of New Tool for Drug Discovery

2017

BACKGROUND There are a great number of tools that can be used in QSAR/QSPR studies; they are implemented in several programs that are reviewed in this report. The usefulness of new tools can be proved through comparison, with previously published approaches. In order to perform the comparison, the most usual is the use of several benchmark datasets such as DRAGON and Sutherland's datasets. METHODS Here, an exploratory study of Atomic Weighted Vectors (AWVs), a new tool useful for drug discovery using different datasets, is presented. In order to evaluate the performance of the new tool, several statistics and QSAR/QSPR experiments are performed. Variability analyses are used to quantify the…

Models Molecular0301 basic medicineQuantitative structure–activity relationshipMolecular StructureOrthogonality (programming)Computer scienceQuantitative Structure-Activity RelationshipGeneral MedicineState of the art reviewInformation theorycomputer.software_genreStructure-Activity Relationship03 medical and health sciences030104 developmental biologyDrug DiscoveryLinear regressionPrincipal component analysisGenetic algorithmBenchmark (computing)Data miningcomputerSoftwareCurrent Topics in Medicinal Chemistry
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What place does molecular topology have in today’s drug discovery?

2020

Introduction: Most methods in molecular and drug design are currently based on physicochemical descriptors. However, molecular topology, which relies on topological descriptors, has also shown value for molecular design even if it does not take into account the physical or chemical properties of ligands and receptors, including the ligand-receptor interaction itself. Areas covered: Herein, the authors provide new insights into the importance of molecular topology according to some of the latest discoveries in physics and chemistry. Furthermore, the authors report on the most significant achievements in drug design using molecular topology over the last 5 years and give their expert perspect…

Models Molecular0303 health sciencesQuantitative structure–activity relationshipTheoretical computer scienceComputer scienceDrug discoveryQuantitative Structure-Activity RelationshipModels TheoreticalLigands03 medical and health sciences0302 clinical medicineDrug Design030220 oncology & carcinogenesisDrug DiscoveryAnimalsHumansMolecular topologyValue (mathematics)030304 developmental biologyExpert Opinion on Drug Discovery
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Design, synthesis, and SAR analysis of cytotoxic sinapyl alcohol derivatives.

2005

Five series totalling 51 of sinapyl alcohol derivatives were designed and synthesized. Their cytotoxicity analyses were performed oil six human tumor cell lines Such as PC-3. CNE, KB, A549, BEL-7404, and HeLa. Certain sinapyl alcohol derivatives showed significant cytotoxic activities. Compound 14d exhibited especially potent cytotoxicity against the BEL-7404 cell line with an IC50 value of 0.7 mu M, which showed more cytotoxic activity than the positive control, cisplatin. The structure-cytotoxicity relationships were discussed and the CoMFA analysis was performed using the cytotoxic data against HeLa cells as a template. (c) 2005 Elsevier Ltd. All rights reserved.

Models MolecularClinical BiochemistryPharmaceutical ScienceQuantitative Structure-Activity RelationshipAntineoplastic AgentsBiochemistryChemical synthesisHeLachemistry.chemical_compoundInhibitory Concentration 50Cell Line TumorDrug DiscoveryElectrochemistryCytotoxic T cellHumansCytotoxicityMolecular BiologyIC50biologyPhenylpropionatesOrganic Chemistrybiology.organism_classificationIn vitroSinapyl alcoholchemistryBiochemistryCell cultureDrug DesignMolecular MedicineDrug Screening Assays AntitumorHeLa CellsBioorganicmedicinal chemistry
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DesMol2, an Effective Tool for the Construction of Molecular Libraries and Its Application to QSAR Using Molecular Topology

2019

A web application, DesMol2, which offers two main functionalities, is presented: the construction of molecular libraries and the calculation of topological indices. These functionalities are explained through a practical example of research of active molecules to the formylpeptide receptor (FPR), a receptor associated with chronic inflammation in systemic amyloidosis and Alzheimer&rsquo

Models MolecularMultilinear mapQuantitative structure–activity relationshiplinear discriminant analysisComputer scienceQuantitative Structure-Activity RelationshipPharmaceutical ScienceComputational biology01 natural sciencesArticleAnalytical ChemistrySmall Molecule Librarieslcsh:QD241-44103 medical and health scienceslcsh:Organic chemistryDrug DiscoveryPhysical and Theoretical ChemistryPiperazineDesMol2030304 developmental biology0303 health sciencesMolecular Structure010405 organic chemistryOrganic Chemistrymolecular librariesBase (topology)Linear discriminant analysisReceptors Formyl PeptideSystemic amyloidosis0104 chemical sciencestopology descriptorsmultilinear regression analysisDiscriminantChemistry (miscellaneous)Molecular MedicineMultiple linear regression analysisMolecular topologyAlzheimer’s diseaseDatabases ChemicalSoftwareProtein BindingMolecules
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DNA minor groove binders: an overview on molecular modeling and QSAR approaches

2007

Molecular recognition of DNA by small molecules and proteins is a fundamental problem in structural biology and drug design. Understanding of recognition in both sequence-selective and sequence neutral ways at the level of successful prediction of binding modes and site selectivity will be instrumental for improvements in the design and synthesis of new molecules as potent and selective gene-regulatory drugs. Minor groove is the target of a large number of non-covalent binding agents. DNA binding with specific sequences, mostly AT, takes place by means of a combination of directed hydrogen bonding to base pair edges, van der Waals interactions with the minor groove walls and generalized ele…

Models MolecularPharmacologyDNA minor groove binders (mGBs) in silico techniques molecular modeling ab initio methods docking molecular dynamics simulations (MDS) QSAR QSPR.Molecular modelBase pairStereochemistryChemistryIn silicoOrganic ChemistryQuantitative Structure-Activity RelationshipDNAComputational biologyBiochemistrySmall moleculechemistry.chemical_compoundMolecular recognitionPharmaceutical PreparationsStructural biologyDocking (molecular)Drug DesignDrug DiscoveryNucleic Acid ConformationMolecular MedicineDNA
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Novel 3D bio-macromolecular bilinear descriptors for protein science: Predicting protein structural classes

2015

In the present study, we introduce novel 3D protein descriptors based on the bilinear algebraic form in the ℝn space on the coulombic matrix. For the calculation of these descriptors, macromolecular vectors belonging to ℝn space, whose components represent certain amino acid side-chain properties, were used as weighting schemes. Generalization approaches for the calculation of inter-amino acidic residue spatial distances based on Minkowski metrics are proposed. The simple- and double-stochastic schemes were defined as approaches to normalize the coulombic matrix. The local-fragment indices for both amino acid-types and amino acid-groups are presented in order to permit characterizing fragme…

Models MolecularProtein structural classesMathematical parametersProtein functionQuantitative Structure-Activity RelationshipBilinear interpolationQuantitative structure activity relation3D protein descriptorBilinear formProceduresChemical structureStatistical parametersMinkowski spaceProtein analysisAmino AcidsPriority journalMathematicsInterpretabilityQuantitative Biology::BiomoleculesApplied MathematicsStatistical parameterValidation studyGeneral MedicineComputer simulationDiscriminant analysisReproducibilityAmino acidAlgorithmChemistryProtein conformationModeling and SimulationStatistical modelGeneral Agricultural and Biological SciencesBiological systemAmino acid analysisAlgorithmsNonbiological modelStatistics and ProbabilityCorrelation coefficientLDAMacromolecular SubstancesMarkov chainMacromoleculeStructure analysisModels BiologicalArticleGeneral Biochemistry Genetics and Molecular BiologyCombinatoricsStochastic processesBilinear formBiologyMatrixGeneral Immunology and MicrobiologyProteinCoulombic matrixComputational BiologyProteinsReproducibility of ResultsLinear discriminant analysisWeightingCorrelation coefficientProtein structureBiological modelLinear ModelsThree-dimensional modelingJournal of Theoretical Biology
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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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