Novel structural analogues of piperine as inhibitors of the NorA efflux pump of Staphylococcus aureus.

OBJECTIVES: Evaluation of novel synthetic analogues of piperine as inhibitors of multidrug efflux pump NorA of Staphylococcus aureus. METHODS: A library of piperine-derived compounds was evaluated for their potential to inhibit ethidium bromide efflux in NorA-overexpressing S. aureus SA 1199B. The active compounds were then individually combined with ciprofloxacin to study the potentiation of ciprofloxacin's activity. RESULTS: Based on the efflux inhibition assay, a library of 200 compounds was screened. Three piperine analogues, namely SK-20, SK-56 and SK-29, were found to be the most potent inhibitors of the NorA efflux pump. These inhibitors acted in a synergistic manner with ciprofloxacin, by substantially increasing its activity against both NorA-overexpressing and wild-type S. aureus isolates. These analogues were 2- to 4-fold more potent than piperine at a significantly lower minimal effective concentration. Furthermore, these inhibitors also significantly suppressed the in vitro emergence of ciprofloxacin-resistant S. aureus. CONCLUSIONS: A newly identified class of compounds derived from a natural amide, piperine, is more potent than the parent molecule in potentiating the activity of ciprofloxacin through the inhibition of the NorA efflux pump. These molecules may prove useful in augmenting the antibacterial activities of fluoroquinolones in a clinical setting.

Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors.

Quantitative structure activity relationship (QSAR) analysis of piperine analogs as inhibitors of efflux pump NorA from Staphylococcus aureus has been performed in order to obtain a highly accurate model enabling prediction of inhibition of S. aureus NorA of new chemical entities from natural sources as well as synthetic ones. Algorithm based on genetic function approximation method of variable selection in Cerius2 was used to generate the model. Among several types of descriptors viz., topological, spatial, thermodynamic, information content and E-state indices that were considered in generating the QSAR model, three descriptors such as partial negative surface area of the compounds, area of the molecular shadow in the XZ plane and heat of formation of the molecules resulted in a statistically significant model with r(2)=0.962 and cross-validation parameter q(2)=0.917. The validation of the QSAR models was done by cross-validation, leave-25%-out and external test set prediction. The theoretical approach indicates that the increase in the exposed partial negative surface area increases the inhibitory activity of the compound against NorA whereas the area of the molecular shadow in the XZ plane is inversely proportional to the inhibitory activity. This model also explains the relationship of the heat of formation of the compound with the inhibitory activity. The model is not only able to predict the activity of new compounds but also explains the important regions in the molecules in quantitative manner.