Outputs (2)

Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics (2023)
Journal Article
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

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 w... Read More about Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics.

Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming (2022)
Journal Article
Peng, Z., Maciel-Guerra, A., Baker, M., Zhang, X., Hu, Y., Wang, W., …Dottorini, T. (2022). Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming. PLoS Computational Biology, 18(3), Article e1010018. https://doi.org/10.1371/journal.pcbi.1010018

Anthropogenic environments such as those created by intensive farming of livestock, have been proposed to provide ideal selection pressure for the emergence of antimicrobial-resistant Escherichia coli bacteria and antimicrobial resistance genes (ARGs... Read More about Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming.