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Updated: Jun 2, 2026

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
Published on: April 3, 2026
pK(a) modelling and prediction of drug molecules through GA-KPLS and L-M ANN
H Noorizadeh1, A Farmany, M Noorizadeh
1Faculty of Science, Islamic Azad University, Ilam Branch, Ilam, Iran. hadinoorizadeh@yahoo.com
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.
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