0000000000769956

AUTHOR

Humberto González Díaz

showing 2 related works from this author

3D-Chiral quadratic indices of the ‘molecular pseudograph’s atom adjacency matrix’ and their application to central chirality codification: classific…

2004

Quadratic indices of the 'molecular pseudograph's atom adjacency matrix' have been generalized to codify chemical structure information for chiral drugs. These 3D-chiral quadratic indices make use of a trigonometric 3D-chirality correction factor. These indices are nonsymmetric and reduced to classical (2D) descriptors when symmetry is not codified. By this reason, it is expected that they will be useful to predict symmetry-dependent properties. 3D-Chirality quadratic indices are real numbers and thus, can be easily calculated in TOMOCOMD-CARDD software. These descriptors circumvent the inability of conventional 2D quadratic indices (Molecules 2003, 8, 687-726. http://www.mdpi.org) and othe…

Models MolecularQuantitative structure–activity relationshipChemistryStereochemistryOrganic ChemistryClinical BiochemistryStability (learning theory)Computational BiologyQuantitative Structure-Activity RelationshipPharmaceutical ScienceAngiotensin-Converting Enzyme InhibitorsStereoisomerismLinear discriminant analysisBiochemistryCross-validationQuadratic equationTest setDrug DiscoveryLinear regressionReceptors sigmaMolecular MedicineApplied mathematicsAdjacency matrixMolecular BiologyBioorganic & Medicinal Chemistry
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A topological sub-structural approach for predicting human intestinal absorption of drugs.

2004

The human intestinal absorption (HIA) of drugs was studied using a topological sub-structural approach (TOPS-MODE). The drugs were divided into three classes according to reported cutoff values for HIA. "Poor" absorption was defined as HIAor =30%, "high" absorption as HIAor =80%, whereas "moderate" absorption was defined between these two values (30%HIA79%). Two linear discriminant analyses were carried out on a training set of 82 compounds. The percentages of correct classification, for both models, were 89.02%. The predictive power of the models were validated by three test: a leave-one-out cross validation procedure (88.9% and 87.9%), an external prediction set of 127 drugs (92.9% and 80…

PharmacologyQuantitative structure–activity relationshipChemistryOrganic ChemistryBiological AvailabilityQuantitative Structure-Activity RelationshipGeneral MedicineModels TheoreticalLinear discriminant analysisTopologyCross-validationIntestinal absorptionBioavailabilityIntestinal AbsorptionPharmaceutical PreparationsTest setDrug DiscoveryHuman intestinal absorptionCutoffHumansIntestinal MucosaEuropean journal of medicinal chemistry
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