Combined 3D-QSAR and molecular docking analysis of thienopyrimidine derivatives as Staphylococcus aureus inhibitors

Abstract

The discovery of antibacterials is considered one of the greatest medical achievements of all time. In this work, a combination of three computational analyzes: 3D-QSAR, molecular docking and ADME evaluation were applied in thienopyrimidine derivatives intended toward gram-positive bacterium Staphylococcus aureus. The validity of 3D-QSAR model was tested with a set of data which is divided into a training and a test set. The two models constructed (CoMFA and CoMSIA) show good statistical reliability (q2 = 0.758; r2 = 0.96; r2pred = 0.783) and (q2 = 0.744; r2 = 0.97; r2pred = 0.625) respectively. In addition, docking methods were applied to understand the structural features responsible for the affinity of the ligands in the binding of S. aureus DNA gyrase. Drug likeness and ADME analysis applied in this series of new proposed compounds, have shown that the five lead molecules would have the potential to be effective drugs and could be used as a starting point for designing compounds against Staphylococcus aureus.