RESUMEN

Simple molecular descriptors of extensive series of 1,3,5-triazinyl sulfonamide derivatives, based on the structure of sulfonamides and their physicochemical properties, were designed and calculated. These descriptors were successfully applied as inputs for artificial neural network (ANN) modelling of the relationship between the structure and biological activity. The optimized ANN architecture was applied to the prediction of the inhibition activity of 1,3,5-triazinyl sulfonamides against human carbonic anhydrase (hCA) II, tumour-associated hCA IX, and their selectivity (hCA II/hCA IX).

Asunto(s)

Redes Neurales de la Computación , Sulfonamidas/química , Triazinas/química , Antígenos de Neoplasias/metabolismo , Anhidrasa Carbónica II/antagonistas & inhibidores , Anhidrasa Carbónica II/metabolismo , Anhidrasa Carbónica IX/antagonistas & inhibidores , Anhidrasa Carbónica IX/metabolismo , Inhibidores de Anhidrasa Carbónica/química , Inhibidores de Anhidrasa Carbónica/metabolismo , Diseño de Fármacos , Humanos , Sulfonamidas/metabolismo