Molecular factors governing inhibition of arylimidamides against Leishmania: conservative computational modeling to improve chemotherapies

Abstract

A dataset of 55 compounds with inhibitory activity against Leishmania donovani axenic amastigotes and Leishmania amazonensis intracellular parasites was examined through three-dimensional quantitative structure-activity relationship modeling employing molecular descriptors from both rigid and flexible compound alignments. For training and testing purposes, the compounds were divided into two datasets of 45 and 10 compounds, respectively. Statistically significant models were constructed and validated via the internal and external predictions. For all models employing steric, electrostatic, hydrophobic, H-donor and H-acceptor molecular descriptors, the R² values were greater than 0.90 and the SEE values were less than 0.22. The models obtained from rigid and flexible compounds were employed together to obtain a conservative method for predictions. This method minimized under predictions. Molecular descriptors from the models were then extrapolated, for the overall predictive devices and the individual compounds, and examined with regard to inhibitory activity. Information gained from the molecular descriptors is useful in the design of novel compounds. The models obtained can be employed to predict activities of the compounds designed and/or form predictions for compounds that exist and have not yet been examined with biological inhibitory assays.