Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis.
Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for
new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure
activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of
leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r2 =
0.98 and q2 = 0.77) as an indication of the statistical internal and external consistency of the models. The best model was
employed to predict pKi values for a series of test set compounds, and the predicted values were in good agreement with
the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular
modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target
enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors
within this structural class.
Keywords: Human African trypanosomiasis, aldolase, molecular modeling, QSAR
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