Search results for "Quantitative Structure-Activity Relationship"

showing 10 items of 113 documents

Thorough evaluation of OECD principles in modelling of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine derivatives using QSARINS.

2020

The human immunodeficiency virus is a lethal pathology considered as a worldwide problem. The search for new strategies for the treatment of this disease continues to be a great challenge in the scientific community. In this study, a series of 107 derivatives of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine, previously evaluated experimentally against HIV-I reverse transcriptase, was used to model antiretroviral activity. A model of linear regression, implemented in the QSARINS software, was developed with a genetic algorithm for variable selection. The fit of its parameters was good and exhaustive validation, according to the OECD regulatory principles, was performed. Also, the applica…

010405 organic chemistryChemistryHuman immunodeficiency virus (HIV)Quantitative Structure-Activity RelationshipBioengineeringGeneral Medicinemedicine.disease_cause01 natural sciencesVirologyReverse transcriptase0104 chemical sciences010404 medicinal & biomolecular chemistryAnti-Retroviral AgentsModels ChemicalDrug DiscoverymedicineMolecular Medicine1-((2-hydroxyethoxy)methyl)-6-(phenylthio)thymineOrganisation for Economic Co-Operation and DevelopmentThymineSAR and QSAR in environmental research
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An Integrated Pharmacophore/Docking/3D-QSAR Approach to Screening a Large Library of Products in Search of Future Botulinum Neurotoxin A Inhibitors

2020

Botulinum toxins are neurotoxins produced by Clostridium botulinum. This toxin can be lethal for humans as a cause of botulism

0301 basic medicineModels MolecularBotulinum ToxinsDatabases FactualNeuromuscular transmissionQuantitative Structure-Activity RelationshipPharmacologymedicine.disease_cause01 natural sciencesType Alcsh:ChemistryModelsClostridium botulinumbotulinum neurotoxin ABotulismBotulinum Toxins Type Alcsh:QH301-705.5Spectroscopyfood and beveragesGeneral MedicineBotulinum neurotoxinComputer Science ApplicationsdockingPharmacophoreQuantitative structure–activity relationshipStatic ElectricityChemicalbotulinum neurotoxin A virtual screening docking 3D-QSAR molecular dynamicsMolecular Dynamics SimulationArticleCatalysisInorganic ChemistrySmall Molecule Libraries03 medical and health sciencesDatabasesmedicinePhysical and Theoretical ChemistryMolecular BiologyFactual3D-QSARVirtual screening010405 organic chemistrybusiness.industryfungiOrganic ChemistryMolecularHydrogen Bondingmedicine.diseasevirtual screeningmolecular dynamics0104 chemical sciences030104 developmental biologyModels Chemicallcsh:Biology (General)lcsh:QD1-999Docking (molecular)Clostridium botulinumbusinessInternational Journal of Molecular Sciences
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Identification of estrogen receptor α ligands with virtual screening techniques.

2016

Utilization of computer-aided molecular discovery methods in virtual screening (VS) is a cost-effective approach to identify novel bioactive small molecules. Unfortunately, no universal VS strategy can guarantee high hit rates for all biological targets, but each target requires distinct, fine-tuned solutions. Here, we have studied in retrospective manner the effectiveness and usefulness of common pharmacophore hypothesis, molecular docking and negative image-based screening as potential VS tools for a widely applied drug discovery target, estrogen receptor α (ERα). The comparison of the methods helps to demonstrate the differences in their ability to identify active molecules. For example,…

0301 basic medicineModels MolecularQuantitative structure–activity relationshipMolecular ConformationQuantitative Structure-Activity RelationshipComputational biologyMolecular Dynamics Simulationta3111BioinformaticsLigands01 natural sciencesMolecular Docking SimulationSmall Molecule Libraries03 medical and health sciencesestrogen receptor alphaDrug DiscoveryMaterials ChemistryHumansComputer SimulationPhysical and Theoretical ChemistrySpectroscopy3D-QSARVirtual screeningDrug discoveryChemistryta1182Estrogen Receptor alphaSmall Molecule LibrariesReproducibility of Resultsmolecular dockingvirtual screeningComputer Graphics and Computer-Aided DesignSmall molecule0104 chemical sciencesMolecular Docking Simulation010404 medicinal & biomolecular chemistry030104 developmental biologyArea Under Curvepharmacophore modelingligand discoverynegative imagePharmacophoreEstrogen receptor alphaJournal of molecular graphicsmodelling
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Investigation on Quantitative Structure-Activity Relationships of 1,3,4-Oxadiazole Derivatives as Potential Telomerase Inhibitors.

2020

Background:Telomerase, a reverse transcriptase, maintains telomere and chromosomes integrity of dividing cells, while it is inactivated in most somatic cells. In tumor cells, telomerase is highly activated, and works in order to maintain the length of telomeres causing immortality, hence it could be considered as a potential marker to tumorigenesis.A series of 1,3,4-oxadiazole derivatives showed significant broad-spectrum anticancer activity against different cell lines, and demonstrated telomerase inhibition.Methods:This series of 24 N-benzylidene-2-((5-(pyridine-4-yl)-1,3,4-oxadiazol-2yl)thio)acetohydrazide derivatives as telomerase inhibitors has been considered to carry out QSAR studies…

0301 basic medicineModels MolecularTelomeraseQuantitative structure–activity relationship2D descriptorsDatasets as TopicQuantitative Structure-Activity RelationshipAntineoplastic Agents010402 general chemistry01 natural sciencesModels BiologicalAnticancer activityMLR03 medical and health sciencesInhibitory Concentration 50Drug DiscoveryLeast-Squares AnalysisTelomerase134-oxadiazolesOxadiazolesMolecular StructureDrug discoveryChemistryQSARQuantitative structureCombinatorial chemistry0104 chemical sciencesTelomerase inhibitors030104 developmental biology1 3 4 oxadiazole derivativesDrug Screening Assays AntitumorCurrent drug discovery technologies
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A Simple Method to Predict Blood-Brain Barrier Permeability of Drug- Like Compounds Using Classification Trees

2017

Background: To know the ability of a compound to penetrate the blood-brain barrier (BBB) is a challenging task; despite the numerous efforts realized to predict/measure BBB passage, they still have several drawbacks. Methods: The prediction of the permeability through the BBB is carried out using classification trees. A large data set of 497 compounds (recently published) is selected to develop the tree model. Results: The best model shows an accuracy higher than 87.6% for training set; the model was also validated using 10-fold cross-validation procedure and through a test set achieving accuracy values of 86.1% and 87.9%, correspondingly. We give a brief explanation, in structural terms, o…

0301 basic medicineQuantitative structure–activity relationshipComputer scienceDatasets as TopicQuantitative Structure-Activity Relationshipcomputer.software_genre01 natural sciencesPermeability03 medical and health sciencesMolecular descriptorDrug DiscoveryInternational literatureComputer SimulationTraining setDecision tree learningDecision Trees0104 chemical sciences010404 medicinal & biomolecular chemistry030104 developmental biologyPharmaceutical PreparationsBlood-Brain BarrierTest setData miningBlood brain barrier permeabilitycomputerAlgorithmsDecision tree modelMedicinal Chemistry
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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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LEGO-based generalized set of two linear algebraic 3D bio-macro-molecular descriptors: Theory and validation by QSARs

2019

Abstract Novel 3D protein descriptors based on bilinear, quadratic and linear algebraic maps in R n are proposed. The latter employs the kth 2-tuple (dis) similarity matrix to codify information related to covalent and non-covalent interactions in these biopolymers. The calculation of the inter-amino acid distances is generalized by using several dis-similarity coefficients, where normalization procedures based on the simple stochastic and mutual probability schemes are applied. A new local-fragment approach based on amino acid-types and amino acid-groups is proposed to characterize regions of interest in proteins. Topological and geometric macromolecular cutoffs are defined using local and…

0301 basic medicineStatistics and ProbabilityNormalization (statistics)GeneralizationQuantitative Structure-Activity RelationshipGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciences0302 clinical medicineLinear regressionAmino AcidsMathematicsGeneral Immunology and MicrobiologyApplied MathematicsStatistical parameterProteinsGeneral MedicineCollinearityStructural Classification of Proteins databaseSupport vector machine030104 developmental biologyModeling and SimulationTest setLinear ModelsGeneral Agricultural and Biological SciencesAlgorithmSoftware030217 neurology & neurosurgeryJournal of Theoretical Biology
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Search of Chemical Scaffolds for Novel Antituberculosis Agents

2005

3 A method to identify chemical scaffolds potentially active against Mycobacterium tuberculosis is presented. The molecular features of a set of structurally heterogeneous antituberculosis drugs were coded by means of structural invariants. Three tech- niques were used to obtain equations able to model the antituberculosis activity: linear discriminant analysis, multilinear re- gression, and shrinkage estimation-ridge regression. The model obtained was statistically validated through leave-n-out test, and an external set and was applied to a database for the search of new active agents. The selected compounds were assayed in vitro, and among those identified as active stand reserpine, N,N,N…

0301 basic medicineStereochemistryAntitubercular AgentsQuantitative Structure-Activity RelationshipComputational biology01 natural sciencesBiochemistryAnalytical ChemistryMycobacterium tuberculosis03 medical and health sciencesmedicineComputer SimulationMycobacterium avium complexEthambutolVirtual screeningMolecular StructurebiologyChemistrybiology.organism_classificationLinear discriminant analysis0104 chemical sciences010404 medicinal & biomolecular chemistry030104 developmental biologyModels ChemicalDrug DesignRegression AnalysisMolecular MedicineMultiple linear regression analysisBiotechnologyPentamidinemedicine.drugSLAS Discovery
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Estimation of ADME Properties in Drug Discovery: Predicting Caco-2 Cell Permeability Using Atom-Based Stochastic and Non-stochastic Linear Indices

2007

The in vitro determination of the permeability through cultured Caco-2 cells is the most often-used in vitro model for drug absorption. In this report, we use the largest data set of measured P(Caco-2), consisting of 157 structurally diverse compounds. Linear discriminant analysis (LDA) was used to obtain quantitative models that discriminate higher absorption compounds from those with moderate-poorer absorption. The best LDA model has an accuracy of 90.58% and 84.21% for training and test set. The percentage of good correlation, in the virtual screening of 241 drugs with the reported values of the percentage of human intestinal absorption (HIA), was greater than 81%. In addition, multiple …

Absorption (pharmacology)Stochastic ProcessesVirtual screeningQuantitative structure–activity relationshipDrug discoveryStereochemistryLinear modelQuantitative Structure-Activity RelationshipPharmaceutical ScienceLinear discriminant analysisPermeabilityData setROC CurveDrug DesignTest setLinear regressionLinear ModelsHumansPharmacokineticsCaco-2 CellsBiological systemADMEMathematicsJournal of Pharmaceutical Sciences
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Preparation and Promotion of Fruit Growth in Kiwifruit of Fluorinated N-Phenyl-N‘-1,2,3-thiadiazol-5-yl Ureas

2004

Seventeen phenyl-fluorinated analogues of thidiazuron [N-phenyl-N'-(1,2,3-thiadiazol-5-yl)urea, TDZ] have been prepared and characterized. The effects of each fluorinated urea on growth and quality of kiwifruits (Actinidia deliciosa) were evaluated by comparison with untreated (control) and TDZ-treated fruits. The results obtained showed a clear dependence of the growth-promoting activity of these fluorinated ureas on the pattern and degree of fluorine substitution in the phenyl ring. The most effective for promoting fruit growth was N-(2,3,5,6-tetrafluorophenyl)-N'-(1',2',3'-thiadiazol-5'-yl)urea at 25 ppm (at harvest, treated fruits were 58% heavier than untreated ones) followed by N-(3,5…

Actinidia deliciosaGrowth promotingbiologyChemistryPhenylurea CompoundsActinidiaFluorine CompoundsQuantitative Structure-Activity RelationshipTitratable acidGeneral Chemistrybiology.organism_classificationchemistry.chemical_compoundSoluble solidsFruitThidiazuronThiadiazolesBotanyUreaDry matterGeneral Agricultural and Biological SciencesNuclear chemistryJournal of Agricultural and Food Chemistry
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