Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics

Chio, Hokin; Guest, Ellen E.; Hobman, Jon L.; Dottorini, Tania; Hirst, Jonathan D.; Stekel, Dov J.

Abstract

Antibiotics enter the environment through waste streams, where they can exert selective pressure for antimicrobial resistance in bacteria. However, many antibiotics are excreted as partly metabolized forms, or can be subject to partial breakdown in wastewater treatment, soil, or through natural processes in the environment. If a metabolite is bioactive, even at sub-lethal levels, and also stable in the environment, then it could provide selection pressure for resistance. (5S)-penicilloic acid of piperacillin has previously been found complexed to the binding pocket of penicillin binding protein 3 (PBP3) of Pseudomonas aeruginosa. Here, we predicted the affinities of all potentially relevant antibiotic metabolites of ten different penicillins to that target protein, using molecular docking and molecular dynamics simulations. Docking predicts that, in addition to penicilloic acid, pseudopenicillin derivatives of these penicillins, as well as 6-aminopenicillanic acid (6APA), could also bind to this target. MD simulations further confirmed that (5R)-pseudopenicillin and 6APA bind the target protein, in addition to (5S)-penicilloic acid. Thus, it is possible that these metabolites are bioactive, and, if stable in the environment, could be contaminants selective for antibiotic resistance. This could have considerable significance for environmental surveillance for antibiotics as a means to reduce antimicrobial resistance, because targeted mass spectrometry could be required for relevant metabolites as well as the native antibiotics.

Citation

Chio, H., Guest, E. E., Hobman, J. L., Dottorini, T., Hirst, J. D., & Stekel, D. J. (2023). Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics. Journal of Molecular Graphics and Modelling, 123, Article 108508. https://doi.org/10.1016/j.jmgm.2023.108508

• Journal Article Type: Article
• Acceptance Date: May 4, 2023
• Online Publication Date: May 24, 2023
• Publication Date: Sep 1, 2023
• Deposit Date: May 16, 2023
• Publicly Available Date: May 17, 2023
• Journal: Journal of Molecular Graphics and Modelling
• Print ISSN: 1093-3263
• Electronic ISSN: 1873-4243
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 123
• Article Number: 108508
• DOI: https://doi.org/10.1016/j.jmgm.2023.108508
• Keywords: Penicillin; Metabolites resistance; Molecular docking; Molecular dynamics
• Public URL: https://nottingham-repository.worktribe.com/output/20830639
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S1093326323001067?via%3Dihub