A Genetic Algorithm for Detection of Relevant Descriptors in ADMET Prediction

ROCÍO LUJÁN CECCHINI; AXEL JUAN SOTO; GUSTAVO ESTEBAN VAZQUEZ; IGNACIO PONZONI

Angra dos Reis, Brasil

Simposio; Brazilian Symposium on Bioinformatics 2007; 2007

In this work, a novel approach for descriptor selection aimed to phys-icochemical property prediction is presented. The capacity of determining the most significant set of descriptors is of great importance due to their contribu-tion for improving ADMET prediction models. The proposed methodology combines a genetic algorithm with decision trees. Experimental analysis was carried out for predicting the octanol-water partition coefficient (logP) using neural networks as prediction method. The performance results showed the good potential of this technique.