Abstract
Malaria is a disease caused by protozoan parasites of the genus Plasmodium that affects millions of people worldwide. In recent years there have been parasite resistances to several drugs, including the first-line antimalarial treatment. With the aim of proposing new drugs candidates for the treatment of disease, Quantitative Structure⁻Activity Relationship (QSAR) methodology was applied to 83 N-myristoyltransferase inhibitors, synthesized by Leatherbarrow et al. The QSAR models were developed using 63 compounds, the training set, and externally validated using 20 compounds, the test set. Ten different alignments for the two test sets were tested and the models were generated by the technique that combines genetic algorithms and partial least squares. The best model shows r² = 0.757, q²(adjusted) = 0.634, R²(pred) = 0.746, R²(m) = 0.716, ∆R²(m) = 0.133, R²(p) = 0.609, and R²(r) = 0.110. This work suggested a good correlation with the experimental results and allows the design of new potent N-myristoyltransferase inhibitors.