pK_a modelling and prediction of drug molecules through GA‐KPLS and L‐M ANN

Abstract

Genetic algorithm and partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg- Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between dissociation constant (pK(a) ) and descriptors for 60 drug compounds. The applied internal (leave-group-out cross validation (LGO-CV)) and external (test set) validation methods were used for the predictive power of models. Descriptors of GA-KPLS model were selected as inputs in L-M ANN model. The results indicate that L-M ANN can be used as an alternative modeling tool for quantitative structure-property relationship (QSPR) studies.

Calculation of VS,max and Its Use as a Descriptor for the Theoretical Calculation of pKa Values for Carboxylic Acids

“…[16] for N-Base ligands at the semi empirical AM1 level of theory, as well as a Principal Components Analysis (PCA) for organic and inorganic acids (RMSE = 0.0195) [17]. Moreover, genetic algorithms (GA) and neural networks (NN) have employed frontier orbital energies for a chemical space of sixty commercial drugs [18] (GA, R 2 = 0.703; NN, R 2 = 0.929). Thus far, the only major commercial program capable of including the effects of molecular conformations on the estimation of p K a values is ‘Jaguar p Ka ′ [19,20].…”

Estudio espectrofotométrico y electroquímico en medio acuoso del fármaco ketoprofeno

“…En la literatura se encuentra reportada la constante acidez (pKa) del ketoprofeno, mediante electroforesis capilar en un medio de agua-metanol-acetona [16] ; también potenciométricamente en agua-acetonitrilo [17] , así mismo en cromatografía de líquidos de alta resolución [18] , sin embargo, hay muy pocos estudios de la molécula en medio acuoso. De igual forma se reportan estudios teóricos de modelado y predicción de pKa mediante Algoritmos Genéticos [19] .…”