Search results for "QSAR"

showing 10 items of 48 documents

Dry selection and wet evaluation for the rational discovery of new anthelmintics

2017

Helminths infections remain a major problem in medical and public health. In this report, atom-based 2D bilinear indices, a TOMOCOMD-CARDD (QuBiLs-MAS module) molecular descriptor family and linear discriminant analysis (LDA) were used to find models that differentiate among anthelmintic and non-anthelmintic compounds. Two classification models obtained by using non-stochastic and stochastic 2D bilinear indices, classified correctly 86.64% and 84.66%, respectively, in the training set. Equation 1(2) correctly classified 141(135) out of 165 [85.45%(81.82%)] compounds in external validation set. Another LDA models were performed in order to get the most likely mechanism of action of anthelmin…

0301 basic medicineBiophysicsNon-stochastic and stochastic atom-based bilinear indicesBilinear interpolationLDA-based QSAR modelQuBiLs-MAS module01 natural sciencesSet (abstract data type)03 medical and health sciencesMolecular descriptorStatisticsPhysical and Theoretical ChemistryMolecular BiologySelection (genetic algorithm)MathematicsFree and open source softwareTraining setTOMOCOMD-CARDD softwareExternal validationAnthelmintic activityAtom (order theory)Computational creeningCondensed Matter PhysicsLinear discriminant analysis0104 chemical sciencesIndazole010404 medicinal & biomolecular chemistry030104 developmental biologyLead generationMolecular Physics
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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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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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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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QuBiLS-MAS, open source multi-platform software for atom- and bond-based topological (2D) and chiral (2.5D) algebraic molecular descriptors computati…

2017

Background In previous reports, Marrero-Ponce et al. proposed algebraic formalisms for characterizing topological (2D) and chiral (2.5D) molecular features through atom- and bond-based ToMoCoMD-CARDD (acronym for Topological Molecular Computational Design-Computer Aided Rational Drug Design) molecular descriptors. These MDs codify molecular information based on the bilinear, quadratic and linear algebraic forms and the graph-theoretical electronic-density and edge-adjacency matrices in order to consider atom- and bond-based relations, respectively. These MDs have been successfully applied in the screening of chemical compounds of different therapeutic applications ranging from antimalarials…

0301 basic medicineTheoretical computer scienceComputer scienceBilinear interpolationLibrary and Information SciencesTopologyLinear01 natural scienceslcsh:ChemistryToMoCoMD-CARDDDouble stochastic03 medical and health sciencesMatrix (mathematics)SoftwareQuadratic equationMolecular descriptorAtom/bond-based molecular descriptorPhysical and Theoretical ChemistryAlgebraic numberSimple stochasticFree and open source softwarelcsh:T58.5-58.64lcsh:Information technologybusiness.industryQSARMutual probability matricesComputer Graphics and Computer-Aided DesignRotation formalisms in three dimensions0104 chemical sciencesComputer Science Applications010404 medicinal & biomolecular chemistry030104 developmental biologylcsh:QD1-999CheminformaticsBilinear and quadratic indicesbusinessNon-stochasticSoftwareQuBiLS-MASJournal of cheminformatics
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Diseño por Topología molecular y ensayos farmacológicos de nuevos inhibidores frente a WNT/β-CATENINA Y PI3K/Akt/mTOR

2015

El cáncer colorrectal y el de próstata causan una elevadísima tasa de muerte a nivel mundial. Por lo que, cualquier estrategia para detener o al menos reducir su desarrollo y progresión sería una importante contribución en la investigación actual. Por todo ello, el objetivo principal de la presente Tesis es la identificación de nuevos agentes quimiopreventivos frente al cáncer, que actúen modulando dos de las vías más implicadas en su desarrollo: PI3K/Akt/mTOR y Wnt/β-catenina. Hoy en día, existen diferentes enfoques para el descubrimiento de nuevos hits and leads, pero esta Tesis se centra en la metodología de la Topología Molecular, que ya ha demostrado su extraordinaria eficacia en este …

239001Cáncer de próstataQSARAktTopología molecularCáncer colorrectalDiseño de fármacos320990beta-catenina
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QuBiLs-MAS method in early drug discovery and rational drug identification of antifungal agents

2015

The QuBiLs-MAS approach is used for the in silico modelling of the antifungal activity of organic molecules. To this effect, non-stochastic (NS) and simple-stochastic (SS) atom-based quadratic indices are used to codify chemical information for a comprehensive dataset of 2478 compounds having a great structural variability, with 1087 of them being antifungal agents, covering the broadest antifungal mechanisms of action known so far. The NS and SS index-based antifungal activity classification models obtained using linear discriminant analysis (LDA) yield correct classification percentages of 90.73% and 92.47%, respectively, for the training set. Additionally, these models are able to correc…

AntifungalQuantitative structure–activity relationshipAntifungal AgentsLinear discriminant analysismedicine.drug_classIn silicoAtom-based quadratic indicesQSAR modelQuantitative Structure-Activity RelationshipBioengineeringDrug developmentComputational biologyQuantitative structure activity relationVrtual screening antifungal agentDrug DiscoverymedicineComputer SimulationDrug identificationChemistryDrug discoveryLinear modelDiscriminant AnalysisGeneral MedicineLinear discriminant analysisCombinatorial chemistryChemistryTest setLinear ModelsMolecular MedicineQuBiLs-MAS softwareStatistical modelAntifungal agent
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Aplicación de la topología molecular para la predicción de biodegradación anaerobia de clorofenoles

2013

Se ha aplicado la topología molecular y el análisis de regresión multilineal en la búsqueda de un modelo de relación cuantitativa estructura-actividad (QSAR) capaz de predecir la capacidad de biodegradación anaerobia de un grupo de clorofenoles. Tomando el valor de la constante de velocidad de desaparición del derivado clorofenolico, log k, como variable dependiente y los descriptores topológicos como variables independientes, se obtuvo una ecuación con tres variables y coeficientes de correlación y de predicción , R2=0.9291 y Q2=0.870. El modelo fue validado a través de una validación interna y un test de aleatoriedad. Los resultados obtenidos muestran una alta capacidad de predicción para…

Anàlisi de regressióBiodegradación; clorofenoles; análisis QSAR; análisis de regresión multilineal; topología molecular.Química
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