In this paper, a Multilinear Regression (MLR) analysis has been carried out in order to accurately
predict physicochemical properties and biological activities of a group of antibacterial quinolones
by means of a set of structural descriptors called topological indices. The aim of this work is to develop
prediction equations for these properties after collecting the maximum number of data from the literature
on antibacterial quinolones.
The five regression functions selected by presenting the best combination of various statistical parameters,
subsequently validated by means of internal validation (intercorrelation, Y-randomization and
leave-one-out cross-validation tests), allowed the reliable prediction of minimum inhibitory concentration
50 versus Staphylococcus aureus (MIC50Sa), Streptococcus pyogenes (MIC50Spy) and Bacteroides
fragilis (MIC50Bf), Mean Residence Time (MRT) after oral administration and volume of distribution
We conclude that the combination of molecular topology methods and MLR provides an excellent tool
for the prediction of pharmacological properties.