Exploring MIA-QSARs for farnesyltransferase inhibitory effect of antimalarial compounds refined by docking simulations

Abstract

Two series of farnesyltransferase (FTase) inhibi- tors were grouped and their antimalarial activi-ties modeled by means of multivariate image analysis applied to quantitative structure-activ- ity relationship (MIA-QSAR). A reliable model was achieved, with r2 for calibration, external prediction and leave-one-out cross-validation of 0.96, 0.87 and 0.83, respectively. Therefore, bio-logical activities of congeners can be estimated using the QSAR model. The bioactivities of new compounds based on the miscellany of sub-structures of the two classes of FTase inhibitors were predicted using the MIA-QSAR model and the most promising ones were submitted to ADME (absorption, distribution, metabolism and excretion) and docking evaluation. Despite the smaller interaction energy of the two most pro-mising, predicted compounds in comparison to the two most active compounds of the data set, one of the proposed structures did not violate any Lipinski’s rule of five. Therefore, it is either a potential drug or may drive synthesis of similar, improved compounds.