Search results for "quantitative"

showing 10 items of 2409 documents

tomocomd-camps and protein bilinear indices - novel bio-macromolecular descriptors for protein research: I. Predicting protein stability effects of a…

2010

Descriptors calculated from a specific representation scheme encode only one part of the chemical information. For this reason, there is a need to construct novel graphical representations of proteins and novel protein descriptors that can provide new information about the structure of proteins. Here, a new set of protein descriptors based on computation of bilinear maps is presented. This novel approach to biomacromolecular design is relevant for QSPR studies on proteins. Protein bilinear indices are calculated from the kth power of nonstochastic and stochastic graph–theoretic electronic-contact matrices, and , respectively. That is to say, the kth nonstochastic and stochastic protein bili…

Quantitative structure–activity relationshipProtein structureLinear regressionStability (learning theory)Bilinear interpolationCell BiologySegmented regressionRepresentation (mathematics)Linear discriminant analysisBiological systemMolecular BiologyBiochemistryMathematicsFEBS Journal
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Atom-Based Quadratic Indices to Predict Aquatic Toxicity of Benzene Derivatives to <i>Tetrahymena pyriformis</i>

2009

The non-stochastic and stochastic atom-based quadratic indices are applied to develop quantitative structure-activity relationship (QSAR) models for the prediction of aquatic toxicity. The used dataset, consisting of 392 benzene derivatives for which toxicity data to the ciliate Tetrahymena pyriformis were available, is divided into training and test sets. The obtained multiple linear regression models are statistically significant (R2 = 0.787 and s = 0.347, R2 = 0.806 and s = 0.329, for non-stochastic and stochastic quadratic indices, respectively) and show rather good stability in a cross-validation experiment (q2 = 0.769 and scv = 0.357, q2 = 0.791 and scv = 0.337, correspondingly). In a…

Quantitative structure–activity relationshipQuadratic equationTest setToxicityLinear regressionTetrahymena pyriformisBiological systemStability (probability)MathematicsAquatic toxicologyProceedings of The 13th International Electronic Conference on Synthetic Organic Chemistry
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Modeling the chiral resolution ability of highly sulfated β-cyclodextrin for basic compounds in electrokinetic chromatography

2013

Abstract Despite the fact that extensive research in the field of enantioseparations by capillary electrophoresis has been carried out, it is difficult to predict whether a concrete chiral selector would be useful for the separation of a racemic compound. Hence, several experimental effort is necessary to test the abilities of individual chiral selectors, usually by trial and error procedures. Thus, the enantioseparation of a new racemate becomes a time- and money-consuming task. In this work, the ability of highly sulfated β-cyclodextrin (HS-β-CD) as chiral selector in electrokinetic chromatography (EKC) is modeled for the first time, using exclusively directly-available structural data of…

Quantitative structure–activity relationshipQuantitative Structure-Activity RelationshipBiochemistryAnalytical ChemistryPolar surface areaElectrokinetic phenomenaCapillary electrophoresisPartial least squares regressionLeast-Squares AnalysisChromatography Micellar Electrokinetic Capillarychemistry.chemical_classificationPrincipal Component AnalysisChromatographyCyclodextrinSulfatesChemistrybeta-CyclodextrinsOrganic ChemistryTemperatureStereoisomerismGeneral MedicineHydrogen-Ion ConcentrationBupivacaineChiral resolutionPartition coefficientModels ChemicalPharmaceutical PreparationsJournal of Chromatography A
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QSAR models for tyrosinase inhibitory activity description applying modern statistical classification techniques: A comparative study

2010

Abstract Cluster analysis (CA), Linear and Quadratic Discriminant Analysis (L(Q)DA), Binary Logistic Regression (BLR) and Classification Tree (CT) are applied on two datasets for description of tyrosinase inhibitory activity from molecular structures. The first set included 701 tyrosinase inhibitors (TI) that are used for performance of inhibitory and non-inhibitory activity and the second one is for potency estimation of active compounds. 2D TOMOCOMD-CARDD atom-based quadratic indices are computed as molecular descriptors. CA is used to “rational” design of training (TS) and prediction set (PS) but it shows of not being adequate as classification technique. On the first data, the overall a…

Quantitative structure–activity relationshipReceiver operating characteristicProcess Chemistry and TechnologyDecision tree learningPosterior probabilityQuadratic classifierComputer Science ApplicationsAnalytical ChemistrySet (abstract data type)Statistical classificationMolecular descriptorStatisticsSpectroscopySoftwareMathematicsChemometrics and Intelligent Laboratory Systems
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Prospective computational design and in vitro bio-analytical tests of new chemical entities as potential selective CYP17A1 lyase inhibitors

2019

[EN] The development and advancement of prostate cancer (PCa) into stage 4, where it metastasize, is a major problem mostly in elder males. The growth of PCa cells is stirred up by androgens and androgen receptor (AR). Therefore, therapeutic strategies such as blocking androgens synthesis and inhibiting AR binding have been explored in recent years. However, recently approved drugs (or in clinical phase) failed in improving the expected survival rates for this metastatic-castration resistant prostate cancer (mCRPC) patients. The selective CYP17A1 inhibition of 17,20-lyase route has emerged as a novel strategy. Such inhibition blocks the production of androgens everywhere they are found in t…

Quantitative structure–activity relationshipStereochemistry01 natural sciencesBiochemistryStructure-Activity Relationship3D-QSAR pharmacophore modelDrug DiscoveryCytochrome P-450 Enzyme InhibitorsHumansStructure–activity relationshipCYP17A1 InhibitorMolecular BiologyDensity Functional TheoryVirtual screeningDose-Response Relationship DrugMolecular Structure010405 organic chemistryChemistryOrganic ChemistryProspective computational designSteroid 17-alpha-Hydroxylasecomputer.file_format1720-lyase selective inhibitionProtein Data BankLyase0104 chemical sciencesMolecular Docking Simulation010404 medicinal & biomolecular chemistryDocking (molecular)CYP17A1 inhibitorsMetastatic-castration resistant prostate cancerPharmacophorecomputer
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New active drugs against liver stages of Plasmodium predicted by molecular topology.

2008

ABSTRACT We conducted a quantitative structure-activity relationship (QSAR) study based on a database of 127 compounds previously tested against the liver stage of Plasmodium yoelii in order to develop a model capable of predicting the in vitro antimalarial activities of new compounds. Topological indices were used as structural descriptors, and their relation to antimalarial activity was determined by using linear discriminant analysis. A topological model consisting of two discriminant functions was created. The first function discriminated between active and inactive compounds, and the second identified the most active among the active compounds. The model was then applied sequentially t…

Quantitative structure–activity relationshipStereochemistryAntiparasiticmedicine.drug_classModels BiologicalAuto-immunity transplantation and immunotherapy [N4i 4]AntimalarialsMiceStructure-Activity RelationshipParasitic Sensitivity Testsparasitic diseasesmedicineAnimalsHumansStructure–activity relationshipPharmacology (medical)PharmacologybiologyPoverty-related infectious diseases [N4i 3]Plasmodium falciparumPlasmodium yoeliibiology.organism_classificationIn vitroInfectious Diseasesmedicine.anatomical_structureLiverBiochemistrySusceptibilityHepatocyteHepatocytesMicrobial pathogenesis and host defense [UMCN 4.1]Infection and autoimmunity [NCMLS 1]Plasmodium yoeliiFunction (biology)Immunity infection and tissue repair [NCMLS 1]
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Bond-based bilinear indices for computational discovery of novel trypanosomicidal drug-like compounds through virtual screening

2014

Two-dimensional bond-based bilinear indices and linear discriminant analysis are used in this report to perform a quantitative structure-activity relationship study to identify new trypanosomicidal compounds. A data set of 440 organic chemicals, 143 with antitrypanosomal activity and 297 having other clinical uses, is used to develop the theoretical models. Two discriminant models, computed using bond-based bilinear indices, are developed and both show accuracies higher than 86% for training and test sets. The stochastic model correctly indentifies nine out of eleven compounds of a set of organic chemicals obtained from our synthetic collaborators. The in vitro antitrypanosomal activity of …

Quantitative structure–activity relationshipStereochemistryTrypanosoma cruziDrug Evaluation PreclinicalQuantitative Structure-Activity RelationshipBilinear interpolationSet (abstract data type)MiceDrug DiscoveryIc50 valuesmedicineAnimalsCells CulturedPharmacologyStochastic ProcessesVirtual screeningDose-Response Relationship DrugMolecular StructureChemistryMacrophagesOrganic ChemistryDiscriminant AnalysisGeneral MedicineLinear discriminant analysisTrypanocidal AgentsDiscriminantBenznidazoleBiological systemmedicine.drugEuropean Journal of Medicinal Chemistry
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Vanilloid Derivatives as Tyrosinase Inhibitors Driven by Virtual Screening-Based QSAR Models

2010

A number of vanilloids have been tested as tyrosinase inhibitors using Ligand-Based Virtual Screening (LBVS) driven by QSAR (Quantitative Structure-Activity Relationship) models as the multi-agent classification system. A total of 81 models were used to screen this family. Then, a preliminary cluster analysis of the selected chemicals was carried out based on their bioactivity to detect possible similar substructural features among these compounds and the active database used in the QSAR model construction. The compounds identified were tested in vitro to corroborate the results obtained in silico. Among them, two chemicals, isovanillin (K(M) (app) = 1.08 mM) near to kojic acid (reference d…

Quantitative structure–activity relationshipStereochemistryTyrosinaseIn silicoQuantitative Structure-Activity RelationshipPharmaceutical ScienceIsovanillinModels BiologicalSkin DiseasesVanilloidsAnalytical Chemistrychemistry.chemical_compoundCluster AnalysisHumansEnvironmental ChemistryComputer SimulationEnzyme InhibitorsSpectroscopyVirtual screeningMonophenol MonooxygenaseReference drugCombinatorial chemistrychemistryBenzaldehydesDrug DesignKojic acidAlgorithmsDrug Testing and Analysis
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Atom, atom-type, and total nonstochastic and stochastic quadratic fingerprints: a promising approach for modeling of antibacterial activity.

2005

The TOpological MOlecular COMputer Design (TOMOCOMD-CARDD) approach has been introduced for the classification and design of antimicrobial agents using computer-aided molecular design. For this propose, atom, atom-type, and total quadratic indices have been generalized to codify chemical structure information. In this sense, stochastic quadratic indices have been introduced for the description of the molecular structure. These stochastic fingerprints are based on a simple model for the intramolecular movement of all valence-bond electrons. In this work, a complete data set containing 1006 antimicrobial agents is collected and presented. Two structure-based antibacterial activity classificat…

Quantitative structure–activity relationshipStochastic ProcessesMolecular modelDatabases FactualChemistryOrganic ChemistryClinical BiochemistryMolecular ConformationPharmaceutical ScienceAtom (order theory)Quantitative Structure-Activity RelationshipModels TheoreticalLinear discriminant analysisBiochemistryAnti-Bacterial AgentsSet (abstract data type)Quadratic equationSimple (abstract algebra)Drug DiscoveryMolecular MedicineComputer SimulationBiological systemMolecular BiologyAntibacterial agentBioorganicmedicinal chemistry
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Harmonization of QSAR Best Practices and Molecular Docking Provides an Efficient Virtual Screening Tool for Discovering New G-Quadruplex Ligands

2015

Telomeres and telomerase are key players in tumorogenesis. Among the various strategies proposed for telomerase inhibition or telomere uncapping, the stabilization of telomeric G-quadruplex (G4) structures is a very promising one. Additionally, G4 stabilizing ligands also act over tumors mediated by the alternative elongation of telomeres. Accordingly, the discovery of novel compounds able to act on telomeres and/or inhibit the telomerase enzyme by stabilizing DNA telomeric G4 structures as well as the development of approaches efficiently prioritizing such compounds constitute active areas of research in computational medicinal chemistry and anticancer drug discovery. In this direction, we…

Quantitative structure–activity relationshipTelomeraseGeneral Chemical EngineeringDrug Evaluation PreclinicalQuantitative Structure-Activity RelationshipComputational biologyLibrary and Information SciencesBiologyG-quadruplexCrystallography X-RayLigandsMolecular Docking Simulationchemistry.chemical_compoundDrug DiscoveryHumansCell ProliferationGeneticsVirtual screeningMolecular StructureDrug discoveryQSARGeneral ChemistryFibroblastsTelomereComputer Science ApplicationsTelomereG-QuadruplexesMolecular Docking SimulationchemistryAcridinesDNAHeLa Cells
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