Prediction of quinolone activity against Mycobacterium avium by molecular topology and virtual computational screening

We conducted a quantitative structure-activity relationship study using a d atabase of 158 quinolones previously tested against Mycobacterium avium-M. intracellulare complex in order to develop a model capable of predicting th e activity of new quinolones against the M. avium-M, intracellulare complex in vitro. Topological indices were used as structural descriptors and were related to anti-M. avium-M. intracellulare complex activity by using the l inear discriminant analysis (LDA) statistical technique. The discriminant e quation thus obtained correctly classified 137 of the 158 quinolones. inclu ding 37 of a test group of 44 randomly chosen compounds, This model was the n applied to 24 quinolones, including recently developed fluoroquinolones, whose MICs were subsequently determined in vitro by using the Alamar blue m icroplate assay; the biological results confirmed the model's predictions. The MICs of these 24 quinolones were then treated by multilinear regression (MLR) to establish a model capable of classifying them according to their in vitro activities. Using this model, a good correlation between measured and predicted MICs was found (r(2) = 0.88; r(cv)(2) [cross-validation corre lation] = 0.82), Moxifloxacin, sparfloxacin, and gatifloxacin were the most potent against the M. avium- M. intracellulare complex. with MICs of 0.2, 0.4, and 0.9 mu g/ml, respectively. Finally, virtual modifications of these three drugs were evaluated in LDA and MLR models in order to determine the importance of different substituents in their activity, We conclude that t he combination of molecular-topology methods, LDA, and MLR provides an exce llent tool fur the design of new quinolone structures with enhanced activit y.