Resumo

RODRIGUEZ-BATISTA, Lisandra; ESCALONA-ARRANZ, Julio César; ROJAS-VARGAS, Julio Alberto  e  HERNANDEZ-SOSA, Edgar. Design of drugs with potential antitumoral activity. Rev Cub Quim [online]. 2016, vol.28, n.2, pp. 579-594. ISSN 2224-5421.

Cancer is a health problem, resulting in the first cause of death worldwide. In the present paper, a Quantitative Structure-Activity Relationship (QSAR) study was developed as a tool for the design of new drugs with potential antitumor activity. Discriminant Linear Analysis and Neural Network were the mathematics methods used to estimate the activity of in a data set consisting in 300 compounds. The biological activity, extracted from the US National Cancer Institute was divided by cluster analysis in a training and prediction series. A model with 10 variables and 84,33 % of correct classification was obtained by a discriminant function meanwhile, the neural network tested with the same number of variables resulted in a 89,67 % of accuracy. Also was calculated the contribution of different structural fragments on the cytostatic activity, and quantified their contribution. Six new compounds were designed predicting a good antitumor activity. In general, the predictive quality of the neural network model was higher than the linear discriminant.

Palavras-chave : cancer; QSAR study; antitumor activity.

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