0000000000182331

AUTHOR

Miguel Angel Cabrera

showing 3 related works from this author

A topological substructural approach for the prediction of P-glycoprotein substrates

2006

A topological substructural molecular design approach (TOPS-MODE) has been used to predict whether a given compound is a P-glycoprotein (P-gp) substrate or not. A linear discriminant model was developed to classify a data set of 163 compounds as substrates or nonsubstrates (91 substrates and 72 nonsubstrates). The final model fit the data with sensitivity of 82.42% and specificity of 79.17%, for a final accuracy of 80.98%. The model was validated through the use of an external validation set (40 compounds, 22 substrates and 18 nonsubstrates) with a 77.50% of prediction accuracy; fivefold full cross-validation (removing 40 compounds in each cycle, 80.50% of good prediction) and the predictio…

Quantitative structure–activity relationshipMolecular modelLinear modelQuantitative Structure-Activity RelationshipPharmaceutical ScienceLinear discriminant analysisTopologyModels BiologicalData setSet (abstract data type)Pharmaceutical PreparationsPredictive Value of TestsTest setLinear ModelsComputer SimulationATP Binding Cassette Transporter Subfamily B Member 1Sensitivity (control systems)FluoroquinolonesMathematicsJournal of Pharmaceutical Sciences
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TOPS-MODE approach for the prediction of blood-brain barrier permeation.

2004

The blood-brain barrier permeation has been investigated by using a topological substructural molecular design approach (TOPS-MODE). A linear regression model was developed to predict the in vivo blood-brain partitioning coefficient on a data set of 119 compounds, treated as the logarithm of the blood-brain concentration ratio. The final model explained the 70% of the variance and it was validated through the use of an external validation set (33 compounds of the 119, MAE = 0.33), a leave-one-out crossvalidation (q(2) = 0.65, S(press) = 0.43), fivefold full crossvalidation (removing 28 compounds in each cycle, MAE = 33, RMSE = 0.43) and the prediction of +/- values for an external test set …

Mean squared errorLogarithmChemistryPharmaceutical ScienceThermodynamicsPenetration (firestop)PermeationConcentration ratioModels BiologicalPartition coefficientCapillary PermeabilityBlood-Brain BarrierPredictive Value of TestsTest setLinear regressionLinear ModelsComputer SimulationJournal of pharmaceutical sciences
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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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