A comprehensive computational study to explore promising natural bioactive compounds targeting glycosyltransferase MurG in Escherichia coli for potential drug development

Abstract

Peptidoglycan is a carbohydrate with a cross-linked structure that protects the cytoplasmic membrane of bacterial cells from damage. The mechanism of peptidoglycan biosynthesis involves the main synthesizing enzyme glycosyltransferase MurG, which is known as a potential target for antibiotic therapy. Many MurG inhibitors have been recognized as MurG targets, but high toxicity and drug-resistant Escherichia coli strains remain the most important problems for further development. In addition, the discovery of selective MurG inhibitors has been limited to the synthesis of peptidoglycan-mimicking compounds. The present study employed drug discovery, such as virtual screening using molecular docking, drug likeness ADMET proprieties predictions, and molecular dynamics (MD) simulation, to identify potential natural products (NPs) for Escherichia coli. We conducted a screening of 30,926 NPs from the NPASS database. Subsequently, 20 of these compounds successfully passed the potency, pharmacokinetic, ADMET screening assays, and their validation was further confirmed through molecular docking. The best three hits and the standard were chosen for further MD simulations up to 400 ns and energy calculations to investigate the stability of the NPs-MurG complexes. The analyses of MD simulations and total binding energies suggested the higher stability of NPC272174. The potential compounds can be further explored in vivo and in vitro for promising novel antibacterial drug discovery.

Keywords: Escherichia coli; Antibacterial; Antibiotics resistance; Molecular dynamics; MurG; Natural products; Virtual screening.

Figure 1

Peptidoglycan component synthesis (PCS) cycle catalyzed by MraY, MurG and penicillin-binding proteins. Numbers from (1–8) represent common antibiotics targeting the synthesis of bacterial cell walls.

Figure 2

Overlays of the crystal structures of the MurG enzyme from E. coli (magenta, PDB code: 1nlm) and Pseudomonas aeruginosa (orange, pdb: 3s2u) complexed with UDP-GlcNAc (grey) in the gorge region.

Figure 3

In silico screening method utilized in the study.

Figure 4

Superimposition of the UDP_GlcNAc native ligand and the top five hits interacted in the MurG active site, pdb:1nlm. Showing the binding poses in a groove between the two domains.

Figure 5

Docking structures of the best five NPs interacted with MurG binding site of E. coli. Ligands are presented in stick, while MurG residues are depicted in thin-stick with olive colour. The structures of A, B, C, D, E and F are NPC272174, NPC170742, NPC117260, NPC277205, NPC259098 NPs and UDP_GlcNAc, respectively. Important hydrogen bonds are highlighted.

Figure 6

RMSD curve of the complexes of (a) NPC272174 and standard UDP_GlcNAc. (b) NPC170742, NPC259098, and standard UDP_GlcNAc backbone atoms complexed with MurG enzyme of E. coli.

Figure 7

Rg profile of the compounds (a) NPC272174 and standard UDP_GlcNAc. (b) NPC170742, NPC259098, and standard UDP_GlcNAc complexed with MurG enzyme of E. coli.

Figure 8

Fluctuation profile (a) RMSF plot of the NPC272174 and standard UDP_GlcNAc compounds. (b) RMSF plot of the NPC170742, NPC259098, and standard UDP_GlcNAc compounds complexed with MurG enzyme during the simulation time. (c) Amino acid residues involve the highest RMSF value in the ligands-MurG complex structures.

Figure 9

Energetic components per-residue decomposition of (a) the standard UDP_GlcNAc. (b) NPC727174 complexes with MurG enzyme of E. coli.

Figure 10

Overlays of the conformational dynamics snapshot for NPC272174-MurG complex taken at different simulation times. The conformation colors corresponding to the appropriate time are highlighted.