Search results for "Molecular Descriptor"

showing 10 items of 54 documents

Bond-Based 2D Quadratic Fingerprints in QSAR Studies: Virtual and In vitro Tyrosinase Inhibitory Activity Elucidation

2010

In this report, we show the results of quantitative structure–activity relationship (QSAR) studies of tyrosinase inhibitory activity, by using the bond-based quadratic indices as molecular descriptors (MDs) and linear discriminant analysis (LDA), to generate discriminant functions to predict the anti-tyrosinase activity. The best two models [Eqs (6) and (12)] out of the total 12 QSAR models developed here show accuracies of 93.51% and 91.21%, as well as high Matthews correlation coefficients (C) of 0.86 and 0.82, respectively, in the training set. The validation external series depicts values of 90.00% and 89.44% for these best two equations (6) and (12), respectively. Afterwards, a second …

PharmacologyVirtual screeningQuantitative structure–activity relationshipChemistryStereochemistryTyrosinaseOrganic ChemistryLinear discriminant analysisBiochemistrychemistry.chemical_compoundQuadratic equationDiscriminantMolecular descriptorDrug DiscoveryMolecular MedicineKojic acidChemical Biology & Drug Design
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Interaction between flavour compounds and beta-lactoglobulin: approach by NMR and 2D/3D-QSAR studies of ligands

2004

 author cannot archive publisher's version/PDF; International audience; Interactions between flavour compounds and beta-lactoglobulin (BLG) have been the subject of several studies, but there are no unanimous binding site explanations. In our laboratory, interactions between BLG, and two flavour compounds, beta-ionone and gamma-decalactone, were studied by 2D-NMR spectroscopy. It appears that several amino acids affected by binding of gamma-decalactone are buried in the central cavity, whereas binding of beta-ionone affects amino acids located in a groove near the outer surface of the protein. 2D/3D-QSAR studies were performed using QSAR+ module of Cerius2 and Catalyst. The QSAR equation pr…

Quantitative structure–activity relationshipAROMAMolecular modelStereochemistry01 natural sciences03 medical and health sciencesComputational chemistryMolecular descriptor[SDV.IDA]Life Sciences [q-bio]/Food engineeringFLAVOURBinding site030304 developmental biology3D-QSAR0303 health sciencesChemistryHydrogen bondLigand[ SDV.IDA ] Life Sciences [q-bio]/Food engineeringGeneral Chemistry[SDV.IDA] Life Sciences [q-bio]/Food engineeringAffinitiesBETA-LACTOGLOBULIN0104 chemical sciences010404 medicinal & biomolecular chemistry2D-QSAR2D-NMRTwo-dimensional nuclear magnetic resonance spectroscopyFood Science
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Quantitative Structure–Activity Relationship of the 4,5α-Dihydrotestosterone Steroid Family

2006

Predictive Quantitative Structure - Activity Relationship (QSAR) models of Anabolic/ Androgenic (A/A) activities for the 4,5a-dihydrotestosterone steroid family were obtained by means of multilinear regression using quantum and physicochemical Molecular Descriptors (MDs) as well as a genetic algorithm for the selection of the best subset of MDs. MDs included in our QSAR models allow the structural interpretation of the biological process, evidencing the main role of the shape of molecules, hydrophobicity, and electronic properties. Attempts were made to include lipophilicity (octanol-water partition coefficient) as well as electronic (lowest unoccupied molecular orbital properties and dipol…

Quantitative structure–activity relationshipAnabolismStereochemistryChemistrymedicine.medical_treatmentOrganic ChemistryRing (chemistry)Computer Science ApplicationsSteroidMolecular descriptorDihydrotestosteroneDrug DiscoveryLipophilicitymedicineAnabolic steroidmedicine.drugQSAR & Combinatorial Science
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Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.

2017

The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic action (MOA), including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles, and soft electrophiles. Because it is often difficult to determine correctly the mechanism of action of a compound, quantitative structure-activity relationship (QSAR) methods, which have proved their interest in toxicity prediction, can be used. In this work, several QSAR models for the prediction of MOA of 221 phenols to the ciliated protozoan Tetrahymena pyriformis, using Chemistry Development Kit descriptors, are reported. Four machine learning techniques (ML), k-nearest neighbours, support vector…

Quantitative structure–activity relationshipAntiprotozoal AgentsQuantitative Structure-Activity RelationshipBioengineeringModes of toxic action010501 environmental sciencesMachine learningcomputer.software_genre01 natural sciencesMachine Learningchemistry.chemical_compoundPhenolsMolecular descriptorDrug DiscoveryPhenols0105 earth and related environmental sciencesCiliated protozoanArtificial neural networkbusiness.industryTetrahymena pyriformisGeneral Medicine0104 chemical sciencesSupport vector machine010404 medicinal & biomolecular chemistrychemistryTetrahymena pyriformisMolecular MedicineArtificial intelligenceNeural Networks ComputerbusinesscomputerSAR and QSAR in environmental research
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Bond-extended stochastic and nonstochastic bilinear indices. I. QSPR/QSAR applications to the description of properties/activities of small-medium si…

2010

Bond-extended stochastic and nonstochastic bilinear indices are introduced in this article as novel bond-level molecular descriptors (MDs). These novel totals (whole-molecule) MDs are based on bilinear maps (forms) similar to use defined in linear algebra. The proposed nonstochastic indices try to match molecular structure provided by the molecular topology by using the kth Edge(Bond)-Adjacency Matrix (Ek, designed here as a nonstochastic E matrix). The stochastic parameters are computed by using the kth stochastic edge-adjacency matrix, ESk, as matrix operators of bilinear transformations. This new edge (bond)-adjacency relationship can be obtained directly from Ek and can be considered li…

Quantitative structure–activity relationshipChemistryBilinear interpolationCondensed Matter PhysicsAtomic and Molecular Physics and Opticschemistry.chemical_compoundsymbols.namesakeComputational chemistryPolarizabilityMolecular descriptorLinear regressionLinear algebrasymbolsApplied mathematicsMolecular graphPhysical and Theoretical Chemistryvan der Waals forceInternational Journal of Quantum Chemistry
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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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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 & Medicinal Chemistry
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Event-based criteria in GT-STAF information indices: theory, exploratory diversity analysis and QSPR applications

2012

Versatile event-based approaches for the definition of novel information theory-based indices (IFIs) are presented. An event in this context is the criterion followed in the "discovery" of molecular substructures, which in turn serve as basis for the construction of the generalized incidence and relations frequency matrices, Q and F, respectively. From the resultant F, Shannon's, mutual, conditional and joint entropy-based IFIs are computed. In previous reports, an event named connected subgraphs was presented. The present study is an extension of this notion, in which we introduce other events, namely: terminal paths, vertex path incidence, quantum subgraphs, walks of length k, Sach's subg…

Quantitative structure–activity relationshipEntropyChemistry OrganicInformation TheoryQuantitative Structure-Activity RelationshipBioengineeringInformation theoryJoint entropyMolecular descriptorDrug DiscoveryComputer GraphicsCluster AnalysisEntropy (information theory)QuantumMathematicsDiscrete mathematicsMolecular StructureLinear modelComputational BiologyGeneral MedicineEthylenesModels TheoreticalLinear ModelsMolecular MedicineSubstructureHydrophobic and Hydrophilic InteractionsAlgorithmsSoftwareSAR and QSAR in Environmental Research
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Similarity boosted quantitative structure-activity relationship--a systematic study of enhancing structural descriptors by molecular similarity.

2013

The concept of molecular similarity is one of the most central in the fields of predictive toxicology and quantitative structure-activity relationship (QSAR) research. Many toxicological responses result from a multimechanistic process and, consequently, structural diversity among the active compounds is likely. Combining this knowledge, we introduce similarity boosted QSAR modeling, where we calculate molecular descriptors using similarities with respect to representative reference compounds to aid a statistical learning algorithm in distinguishing between different structural classes. We present three approaches for the selection of reference compounds, one by literature search and two by…

Quantitative structure–activity relationshipInformaticsbusiness.industryStatistical learningGeneral Chemical EngineeringStructural diversityQuantitative Structure-Activity RelationshipPattern recognitionGeneral ChemistryPredictive toxicologyLibrary and Information Sciencescomputer.software_genreToxicologyComputer Science ApplicationsSimilarity (network science)Molecular descriptorArtificial intelligenceData miningbusinessCluster analysiscomputerMathematicsJournal of chemical information and modeling
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Unified Markov thermodynamics based on stochastic forms to classify drugs considering molecular structure, partition system, and biological species:

2005

Abstract To date, molecular descriptors do not commonly account for important information beyond chemical structure. The present work, attempts to extend, in this sense, the stochastic molecular descriptors (Gonzalez-Diaz, H. et al., J. Mol. Mod. 2002, 8, 237), incorporating information about the specific biphasic partition system, the biological species, and chemical structure inside the molecular descriptors. Consequently, MARCH-INSIDE molecular descriptors may be identified with time-dependent thermodynamic parameters (entropy and mean free energy) of partition process. A classification function was developed to classify data of 423 drugs and up to 14 different partition systems at the s…

Quantitative structure–activity relationshipMolecular modelMarkov chainChemistryStereochemistryOrganic ChemistryClinical BiochemistryPharmaceutical ScienceWiener indexMarkov modelBiochemistryPartition coefficientMolecular descriptorDrug DiscoveryMolecular MedicineBiological systemMolecular BiologyAntibacterial agentBioorganic & Medicinal Chemistry Letters
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