Molecular modeling study of micro and nanocurcumin with in vitro and in vivo antibacterial validation

Abstract

Repurposing natural compounds as inhibitory targets to combat bacterial virulence is an important potential strategy to overcome resistance to traditional antibiotics, in the present study, the antibacterial activity of micro-curcumin and nano-sized curcumin was investigated against four predominant bacterial pathogens, namely, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Bacillus subtilis. Curcumin bactericidal susceptibility could be summarized as the order, P. aeruginosa > B. subtilis > S. aureus > E. coli. Molecular docking analysis was conducted to confirm the impact of curcumin on the most vital and positively identified quorum-sensing pathway signaling proteins SecA-SecY, LsrR, PqsR (MvfR), AgrA which act as key players in the bacterial communication systems. The in silico physicochemical properties revealed that curcumin as a nutraceutical can be classified as a drug-like compound. An in vivo infected wound model was employed in four groups of albino rats. Topical application of nano-curcumin lotion showed a marked reduction in wound area (98.8%) as well as nearly 100% reduction in total bacterial viable count compared to the control group, on the fifteenth day post-treatment post-injury. The obtained data suggested that curcumin nanoparticles exhibited superior antibacterial activity and may possess clinical utility as a novel topical antimicrobial and wound healing agent.

Figure 1

Characterization of nanocurcumin showing: UV–visible spectrum (A), DLS showing particle size (B), TEM image (C), and solubility of micro (yellow, left) and nano (orange, right) curcumin in water (D).

Figure 2

Antibacterial activity of MC (1), NC (2) and ciprofloxacin (3) against the four tested bacterial isolates.

Figure 3

Antibacterial activity of MC and Nc based on growth turbidity (a) measurement and total viable bacterial count (b).

Figure 4

Mode of action of curcumin and ciprofloxacin.

Figure 5

Receptor binding domain interaction with curcumin (A) and Ciprofloxacin (B), the right figure shows the 3d structure of the active site for the protein with curcumin and Ciprofloxacin, the left figure shows the 2d interacting residues of the protein with curcumin and Ciprofloxacin (A1): SecA-SecY protein of B. subtilis. (B1): LsrA protein of E. coli, (C1): PqsR (MvfR) protein of P. aeruginosa, (D1): AgrA protein of S. aureus.

Figure 6

Structure of curcumin tested compound (A) and the ADME properties of the structure (B).

Figure 7

Root means square fluctuation (RMSF) (A) analysis of AgrA (A), LsrR (B), SecA-SecY (C), PqsR (MvfR) (D) proteins in association with curcumin complexes throughout 100 ns. SecA-SecY from B. subtilis, LsrR from E. coli, PqsR (MvfR) from P. aeruginosa, and AgrA from S. aureus.

Figure 8

Root mean square deviation (RMSD) trajectories of AgrA (A), LsrR (B), SecA-SecY (C), and PqsR (MvfR) (D) protein complexes throughout 100 ns.[SecA-SecY from B. subtilis, LsrR from E. coli, PqsR (MvfR) from P. aeruginosa, and AgrA from S. aureus].

Figure 9

Ligand property trajectory (A1), protein–ligand plots (B1) and protein–ligand interaction residues (C1) for: AgrA protein (A), LsrR protein (B), SecA-SecY protein (C) and PqsR (MvfR) protein (D) during MD simulation at 100 ns.

Figure 10

Wound healing over time (in days post-treatment) in vivo evaluation (A) photograph images, (B) the % of wound healing versus healing time, and (C) % bacterial viable count, results grouped in 20 s (0–20% blue, 20–40% orange, 40–60% gray, 60–80% yellow, and 80–100% green) in the studied animals, [Group I; infected wounded animals treated with blank lotion (negative control group), group II; infected wounded animals treated with micro-curcumin lotion, group III; infected wounded animals treated with nano-curcumin lotion, group IV; infected wounded animals treated with standard antibiotic Framycetin (Soframycin) ointment (positive control group).] [Animals per group = 6].