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Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics
Hokin Chio, Ellen E Guest, View ORCID ProfileJon L Hobman, View ORCID ProfileTania Dottorini, View ORCID ProfileJonathan D Hirst, View ORCID ProfileDov J Stekel
doi: https://doi.org/10.1101/2022.09.06.506739
Hokin Chio
1School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, LE12 5RD, UK
Ellen E Guest
2School of Chemistry, University of Nottingham, Nottingham, NG7 2RD, UK
Jon L Hobman
1School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, LE12 5RD, UK
Tania Dottorini
3School of Veterinary Medicine and Sciences, University of Nottingham, Sutton Bonington Campus, Loughborough, LE12 5RD, UK
Jonathan D Hirst
2School of Chemistry, University of Nottingham, Nottingham, NG7 2RD, UK
Dov J Stekel
1School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, LE12 5RD, UK
4Department of Mathematics and Applied Mathematics, University of Johannesburg, Aukland Park Kingsway Campus, Rossmore, Johannesburg, South Africa

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Posted September 06, 2022.
Predicting bioactivity of antibiotic metabolites by molecular docking and dynamics
Hokin Chio, Ellen E Guest, Jon L Hobman, Tania Dottorini, Jonathan D Hirst, Dov J Stekel
bioRxiv 2022.09.06.506739; doi: https://doi.org/10.1101/2022.09.06.506739
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