Abstract
Undecaprenyl Pyrophosphate Synthase (UPPS) is a vital target enzyme in the early stages of bacterial cell wall biosynthesis. UPPS inhibitors have antibacterial activity against resistant strains such as MRSA and VRE. In this study, we used several consecutive computer-based protocols to identify novel UPPS inhibitors. The 3D QSAR pharmacophore model generation (HypoGen algorithm) protocol was used to generate a valid predictive pharmacophore model using a set of UPPS inhibitors with known reported activity. The developed model consists of four pharmacophoric features: one hydrogen bond acceptor, two hydrophobic, and one aromatic ring. It had a correlation coefficient of 0.86 and a null cost difference of 191.39, reflecting its high predictive power. Hypo1 was proven to be statistically significant using Fischer's randomization at a 95% confidence level. The validated pharmacophore model was used for the virtual screening of several databases. The resulting hits were filtered using SMART and Lipinski filters. The hits were docked into the binding site of the UPPS protein, affording 70 hits with higher docking affinities than the reference compound (6TC, - 21.17 kcal/mol). The top five hits were selected through extensive docking analysis and visual inspection based on docking affinities, fit values, and key residue interactions with the UPPS receptor. Moreover, molecular dynamic simulations of the top hits were performed to confirm the stability of the protein-ligand complexes, yielding five promising novel UPPS inhibitors.