Search results for "Quantitative structure–activity relationship"

showing 10 items of 158 documents

QSPR Prediction of Retention Times of Methylxanthines and Cotinine by Bioplastic Evolution

2018

High-performance liquid-chromatographic retention times of methylxanthines and cotinine in human plasma and urine are modelled by structure–property relationships. Bioplastic evolution is an evolutionary perspective conjugating the effect of acquired characters, and relations that emerge among the principles of evolutionary indeterminacy, morphological determination and natural selection. It is applied to design co-ordination index, which is used to characterize retentions of methylxanthines, etc. Parameters used to calculate co-ordination index are formation enthalpy, molecular weight and surface area. Morphological and co-ordination indices provide strong correlations. Effect of different…

0301 basic medicine03 medical and health scienceschemistry.chemical_compoundQuantitative structure–activity relationship030104 developmental biologyMaterials scienceChromatographychemistry02 engineering and technology021001 nanoscience & nanotechnology0210 nano-technologyCotinineBioplasticInternational Journal of Quantitative Structure-Property Relationships
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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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Molecular topology: A new strategy for antimicrobial resistance control

2017

The control of antimicrobial resistance (AMR) seems to have come to an impasse. The use and abuse of antibacterial drugs has had major consequences on the genetic mutability of both pathogenic and nonpathogenic microorganisms, leading to the development of new highly resistant strains. Because of the complexity of this situation, an in silico strategy based on QSAR molecular topology was devised to identify synthetic molecules as antimicrobial agents not susceptible to one or several mechanisms of resistance such as: biofilms formation (BF), ionophore (IA) activity, epimerase (EI) activity or SOS system (RecA inhibition). After selecting a group of 19 compounds, five of them showed signific…

0301 basic medicineQuantitative structure–activity relationshipStaphylococcusIn silico030106 microbiologyMicrobial Sensitivity Testsmedicine.disease_causeMicrobiologyStructure-Activity Relationship03 medical and health sciencesAntibiotic resistanceDrug Resistance BacterialDrug DiscoveryEnterococcus faecalisEscherichia colimedicineEscherichia coliPharmacologyVirtual screeningDose-Response Relationship DrugMolecular StructureChemistryOrganic ChemistryBiofilmGeneral MedicineAntimicrobialAnti-Bacterial Agents030104 developmental biologyBiofilmsRegression AnalysisStaphylococcusEuropean Journal of Medicinal Chemistry
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Mode of Action Analyses of Neferine, a Bisbenzylisoquinoline Alkaloid of Lotus (Nelumbo nucifera) against Multidrug-Resistant Tumor Cells

2017

Neferine, a bisbenzylisoquinoline alkaloid isolated from the green seed embryos of Lotus (Nelumbo nucifera Gaertn), has been previously shown to have various anti-cancer effects. In the present study, we evaluated the effect of neferine in terms of P-glycoprotein (P-gp) inhibition via in vitro cytotoxicity assays, R123 uptake assays in drug-resistant cancer cells, in silico molecular docking analysis on human P-gp and in silico absorption, distribution, metabolism, and excretion (ADME), quantitative structure activity relationships (QSAR) and toxicity analyses. Lipinski rule of five were mainly considered for the ADME evaluation and the preset descriptors including number of hydrogen bond d…

0301 basic medicineQuantitative structure–activity relationshipnatural productsIn silicohERGPharmacologyP-glycoproteinchemotherapy03 medical and health sciences0302 clinical medicinecancerPharmacology (medical)Mode of actionIC50P-glycoproteinADMEOriginal ResearchPharmacologydrug resistancebiologylcsh:RM1-950030104 developmental biologylcsh:Therapeutics. Pharmacology030220 oncology & carcinogenesisbiology.proteinLipinski's rule of fiveneferineFrontiers in Pharmacology
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Innovative Strategies to Develop Chemical Categories Using a Combination of Structural and Toxicological Properties.

2016

Interest is increasing in the development of non-animal methods for toxicological evaluations. These methods are however, particularly challenging for complex toxicological endpoints such as repeated dose toxicity. European Legislation, e.g., the European Union's Cosmetic Directive and REACH, demands the use of alternative methods. Frameworks, such as the Read-across Assessment Framework or the Adverse Outcome Pathway Knowledge Base, support the development of these methods. The aim of the project presented in this publication was to develop substance categories for a read-across with complex endpoints of toxicity based on existing databases. The basic conceptual approach was to combine str…

0301 basic medicineQuantitative structure–activity relationshipread acrossPredictive Clustering Tree (PCT) methodComputer science610010501 environmental sciencescomputer.software_genre600 Technik Medizin angewandte Wissenschaften::610 Medizin und Gesundheit01 natural sciences03 medical and health sciencesPharmacology (medical)Cluster analysis0105 earth and related environmental sciencesOriginal ResearchAlternative methodsPharmacologytoxicological and structural similaritybusiness.industryQSARlcsh:RM1-950non-animal methods; QSAR; readacross; Predictive Clustering Tree (PCT) method; toxicological and structural similarityIdentification (information)Tree (data structure)030104 developmental biologyConceptual approachlcsh:Therapeutics. PharmacologyKnowledge basenon-animal methodsData miningWeb servicebusinesscomputerFrontiers in pharmacology
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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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