NorA is a member of the Major Facilitator Superfamily (MFS) drug efflux pumps that have been shown to mediate
antibiotic resistance in Staphylococcus aureus (SA). In this study, QSAR analysis, virtual screening and molecular
docking were implemented in an effort to discover novel SA NorA efflux pump inhibitors. Originally, a set of 47 structurally
diverse compounds compiled from the literature was used to develop linear QSAR models and another set of 15 different
compounds were chosen for extra validation. The final model which was estimated by statistical values for the full
data set (n = 45, Q2 = 0.80, RMSE = 0.20) and for the external test set (n = 15, R2 = 0.60, |res|max = 0.75, |res|min = 0.02)
was applied on the collection of 182 flavonoides and the traditional Chinese medicine (TCM) database to screen for novel
NorA inhibitors. Finally, 33 lead compounds that met the Lipinski's rules of five/three and had good predicted pIC50 values
from in silico screening process were employed to analyze the binding ability by docking studies on NorA homology
model in place of its unavailable crystal structures at two active sites, the central channel and the Walker B.
Keywords: Antibiotic resistance, docking, QSAR, virtual screening, NorA, staphylococcus aureus.
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