Application of computational methods for class A GPCR Ligand discovery
Abstract
AIMS: Due to antibiotic tolerance of microbes within biofilm, non-antibiotic methods for prevention and treatment of implant-related infections are preferable. The goal of this work is to evaluate a facile loading strategy for medium-chain fatty-acid signaling molecules 2-heptycyclopropane-1-carboxylic acid (2CP), cis-2-decenoic acid (C2DA), and trans-2-decenoic acid, which all act as diffusible signaling factors (DSFs), onto titanium surfaces for comparison of their antimicrobial efficacy. METHODS AND RESULTS: Titanium coupons were drop-coated with 0.75 mg of DSF in ethanol and dried. Surface characteristics and the presence of DSF were confirmed with Fourier Transform infrared spectroscopy, x-ray photoelectron spectroscopy, and water contact angle. Antimicrobial assays analyzing biofilm and planktonic Staphylococcus aureus, Escherichia coli, or Candida albicans viability showed that planktonic growth was reduced after 24-h incubation but only sustained through 72 h for S. aureus and C. albicans. Biofilm formation on the titanium coupons was also reduced for all strains at the 24-h time point, but not through 72 h for E. coli. Although ∼60% of the loaded DSF was released within the first 2 days, enough remained on the surface after 4 days of elution to significantly inhibit E. coli and C. albicans biofilm. Cytocompatibility evaluations with a fibroblast cell line showed that none of the DSF-loaded groups decreased viability, while C2DA and 2CP increased viability by up to 50%. CONCLUSIONS: In this study, we found that DSF-loaded titanium coupons can inhibit planktonic microbes and prevent biofilm attachment, without toxicity to mammalian cells.
Publication Title
Journal of Molecular Graphics and Modelling
Recommended Citation
Harrison, Z., Montgomery, E., Hoffman, B., Perez, F., Bush, J., Bumgardner, J., Fujiwara, T., Baker, D., & Jennings, J. (2023). Application of computational methods for class A GPCR Ligand discovery. Journal of Molecular Graphics and Modelling, 121 https://doi.org/10.1016/j.jmgm.2023.108434