Search results for "quantitative"

showing 10 items of 2409 documents

Chromatographic evaluation of the toxicity in fish of pesticides

2004

Abstract Ecotoxicity assessment is essential before placing new chemical substances on the market. An investigation of the use of the chromatographic retention (log k) in biopartitioning micellar chromatography (BMC) as an in vitro approach to evaluate the toxicity in fish of pesticides (acute toxicity levels as pLC50) is proposed. A heterogeneous data set of 85 pesticides from six chemical families with available experimental fish toxicity data (ECOTOX database from U.S. Environmental Protection Agency (EPA)) was used. For pesticides exhibiting non-polar narcosis mechanism in fish (non-specific toxicity), more reliable models and precise pLC50 estimations are obtained from log k (quantitat…

Quantitative structure–activity relationshipChromatographyToxicity dataChemistryClinical BiochemistryFishesQuantitative Structure-Activity RelationshipCell BiologyGeneral MedicinePesticideBiochemistryAcute toxicityAnalytical ChemistryEnvironmental chemistryToxicityAnimalsFish <Actinopterygii>Spectrophotometry UltravioletPesticidesEcotoxicityChromatography LiquidJournal of Chromatography B
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Antiprotozoan lead discovery by aligning dry and wet screening: Prediction, synthesis, and biological assay of novel quinoxalinones

2014

Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In …

Quantitative structure–activity relationshipClinical BiochemistryAntiprotozoal AgentsQuantitative Structure-Activity RelationshipPharmaceutical ScienceLinear classifierBioinformaticsMachine learningcomputer.software_genreBiochemistryQuinoxalinesMolecular descriptorDrug DiscoveryBioassayMolecular BiologyVirtual screeningMolecular Structurebusiness.industryChemistryOrganic ChemistryBenchmark databaseDrug developmentCyclizationMolecular MedicineIn silico StudyArtificial intelligenceTOMOCOMD-CARDD SoftwarebusinessClassifier (UML)computer
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Atom-based 3D-chiral quadratic indices. Part 2: prediction of the corticosteroid-binding globulinbinding affinity of the 31 benchmark steroids data s…

2005

A quantitative structure-activity relationship (QSAR) study to predict the relative affinities of the steroid 'benchmark' data set to the corticosteroid-binding globulin (CBG) is described. It is shown that the 3D-chiral quadratic indices closely correlate with the measured CBG affinity values for the 31 steroids. The calculated descriptors were correlated with biological data through multiple linear regressions. Two statistically significant models were obtained when non-stochastic (R = 0.924 and s = 0.46) as well as stochastic (R = 0.929 and s = 0.46) 3D-chiral quadratic indices were used. A leave-one-out (LOO) approach to model validation is used here; the best results obtained in the cr…

Quantitative structure–activity relationshipClinical BiochemistryPharmaceutical ScienceQuantitative Structure-Activity RelationshipBiochemistryCross-validationStructure-Activity RelationshipQuadratic equationDrug DiscoveryLinear regressionApplied mathematicsComputer SimulationMolecular BiologyTranscortinChromatographyMolecular StructureChemistryOrganic ChemistryComputational BiologyRegression analysisAffinitiesData setDatabases as TopicModels ChemicalTopological indexMolecular MedicineSteroidsBioorganicmedicinal chemistry
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Protein linear indices of the ‘macromolecular pseudograph α-carbon atom adjacency matrix’ in bioinformatics. Part 1: Prediction of protein stability …

2005

Abstract A novel approach to bio-macromolecular design from a linear algebra point of view is introduced. A protein’s total (whole protein) and local (one or more amino acid) linear indices are a new set of bio-macromolecular descriptors of relevance to protein QSAR/QSPR studies. These amino-acid level biochemical descriptors are based on the calculation of linear maps on R n [ f k ( x m i ) : R n → R n ] in canonical basis. These bio-macromolecular indices are calculated from the kth power of the macromolecular pseudograph α-carbon atom adjacency matrix. Total linear indices are linear functional on R n . That is, the kth total linear indices are linear maps from R n to the scalar R [ f k …

Quantitative structure–activity relationshipClinical BiochemistryQuantitative Structure-Activity RelationshipPharmaceutical ScienceBiochemistryCombinatoricsViral ProteinsLinear formDrug DiscoveryLinear regressionViral Regulatory and Accessory ProteinsMolecular BiologyAlanineChemistryOrganic ChemistryTemperatureLinear modelComputational BiologyProteinsModels TheoreticalLinear discriminant analysisMatthews correlation coefficientRepressor ProteinsAmino Acid SubstitutionTopological indexMutationLinear algebraLinear ModelsMolecular MedicineSoftwareBioorganic &amp; Medicinal Chemistry
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New qsar models for polyhalogenated aromatics

1994

Electronic properties of polychlorinated dibenzo p dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs), and polychlorinated diphenyl ethers (PCDEs) were calculated using the semi-empirical AM1 method The calculated electronic descriptors — the energy of the lowest unoccupied molecular orbital (ELUMO), the energy of the highest occupied molecular orbital (EHOMO), the ELUMO-EHOMO gap (dE), and molecular polarizability — are related to the Ah receptor binding affinity values of PCDDs, PCDFs, and PCBs and immunotoxicity values for PCDEs The quantitative structure activity relationships (QSARs) based on chlorine substitution patterns were also constructed, an…

Quantitative structure–activity relationshipComputational chemistryPolychlorinated Dibenzo-p-dioxinsChemistryStereochemistryHealth Toxicology and MutagenesisChlorine atomEnvironmental ChemistryHOMO/LUMOPolychlorinated dibenzofuransPolychlorinated diphenyl ethersBinding affinitiesElectronic propertiesEnvironmental Toxicology and Chemistry
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New set of 2D/3D thermodynamic indices for proteins. A formalism based on "Molten Globule" theory

2010

Abstract We define eight new macromolecular indices, and several related descriptors for proteins. The coarse grained methodology used for its deduction ensures its fast execution and becomes a powerful potential tool to explore large databases of protein structures. The indices are intended for stability studies, predicting Φ -values, predicting folding rate constants, protein QSAR/QSPR as well as protein alignment studies. Also, these indices could be used as scoring function in protein-protein docking or 3D protein structure prediction algorithms and any others applications which need a numerical code for proteins and/or residues from 2D or 3D format.

Quantitative structure–activity relationshipComputer sciencePhysics and Astronomy(all)Protein structure predictionMolten globuleFolding degreeFormalism (philosophy of mathematics)Protein indicesProtein structureFPIDocking (molecular)Protein stabilityPhysical chemistryBiological systemStatistical potentialMacromoleculeProtein folding descriptor
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Discrimination and Molecular Design of New Theoretical Hypolipaemic Agents Using the Molecular Connectivity Functions

2000

The molecular topology model and discriminant analysis have been applied to the prediction and QSAR interpretation of some pharmacological properties of hypolipaemic drugs using multivariable regression equations with their statistical parameters. Regression analysis showed that the molecular topology model predicts these properties. The corresponding stability (cross-validation) studies done on the selected prediction models confirmed the goodness of the fits. The method used for hypolipaemic activity selection was a linear discriminant analysis (LDA). We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and design of new hypolip…

Quantitative structure–activity relationshipComputer sciencebusiness.industryMultivariable calculusPattern recognitionGeneral ChemistryLinear discriminant analysisComputer Science ApplicationsInterpretation (model theory)Computational Theory and MathematicsArtificial intelligenceMolecular topologybusinessInformation SystemsJournal of Chemical Information and Computer Sciences
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QSAR methods for the discovery of new inflammatory bowel disease drugs

2013

Inflammatory bowel disease (IBD) represents an important class of chronic gastrointestinal tract disease. And although there are already several useful treatments to reduce and control the symptoms, there is still no cure. One drug discovery technique used is the computer-aided (in silico) discovery approach which has largely demonstrated efficacy. Computational techniques, when used in combination with traditional drug discovery methodology, greatly increase the chance of drug discovery in a sustainable and economical fashion.This review aims to provide the most recent and important advances of in silico IBD drug discovery. While this review is mainly focused on QSAR methods, especially th…

Quantitative structure–activity relationshipCrohn's diseaseDrug discoverybusiness.industryIn silicoQuantitative Structure-Activity RelationshipDiseaseInflammatory Bowel Diseasesmedicine.diseaseBioinformaticsUlcerative colitisInflammatory bowel diseaseDrug DiscoverymedicineComputer-Aided DesignHumansMolecular topologybusinessExpert Opinion on Drug Discovery
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Predicting antitrichomonal activity: A computational screening using atom-based bilinear indices and experimental proofs

2006

Existing Trichomonas vaginalis therapies are out of reach for most trichomoniasis people in developing countries and, where available, they are limited by their toxicity (mainly in pregnant women) and their cost. New antitrichomonal agents are needed to combat emerging metronidazole-resistant trichomoniasis and reduce the side effects associated with currently available drugs. Toward this end, atom-based bilinear indices, a new TOMOCOMD-CARDD molecular descriptor, and linear discriminant analysis (LDA) were used to discover novel, potent, and non-toxic lead trichomonacidal chemicals. Two discriminant functions were obtained with the use of non-stochastic and stochastic atom-type bilinear in…

Quantitative structure–activity relationshipDatabases FactualMolecular modelStereochemistryClinical BiochemistryDrug Evaluation PreclinicalPharmaceutical ScienceAntitrichomonal AgentsLigandsBiochemistryCross-validationChemometricsStructure-Activity Relationshipchemistry.chemical_compoundArtificial IntelligencePredictive Value of TestsMolecular descriptorDrug DiscoveryTrichomonas vaginalisAnimalsCluster AnalysisComputer SimulationMolecular BiologyStochastic ProcessesOrganic ChemistryComputational BiologyReproducibility of ResultsLinear discriminant analysisAntitrichomonal agentchemistryData Interpretation StatisticalTopological indexLinear ModelsMolecular MedicineBiological systemAlgorithmsBioorganic &amp; Medicinal Chemistry
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Dragon method for finding novel tyrosinase inhibitors: Biosilico identification and experimental in vitro assays

2006

QSAR (quantitative structure-activity relationship) studies of tyrosinase inhibitors employing Dragon descriptors and linear discriminant analysis (LDA) are presented here. A data set of 653 compounds, 245 with tyrosinase inhibitory activity and 408 having other clinical uses were used. The active data set was processed by k-means cluster analysis in order to design training and prediction series. Seven LDA-based QSAR models were obtained. The discriminant functions applied showed a globally good classification of 99.79% for the best model Class=-96.067+1.988 x 10(2)X0Av +9 1.907 BIC3 + 6.853 CIC1 in the training set. External validation processes to assess the robustness and predictive pow…

Quantitative structure–activity relationshipDatabases FactualStereochemistryTyrosinaseQuantitative Structure-Activity RelationshipComputational biologyLigandsChemometricschemistry.chemical_compoundPiperidinesDrug DiscoveryComputer SimulationPharmacologyVirtual screeningbiologyChemistryOrganic ChemistryIn vitro toxicologyComputational BiologyDiscriminant AnalysisReproducibility of ResultsGeneral MedicineLinear discriminant analysisEnzyme inhibitorDrug Designbiology.proteinPeptidesKojic acidSoftwareEuropean Journal of Medicinal Chemistry
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