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Predicting antibiotic resistance de novo

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Fowler Lab
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Predicting antibiotic resistance de novo

I’ve moved…

Philip Fowler, 14th March 20165th August 2018

Today is my first day as a Senior Researcher in Modernising Medical Microbiology in the Nuffield Department of Medicine at the University of Oxford. Practically I’ll be based at the John Radcliffe Hospital in Oxford.

I was a Postdoctoral Researcher in the SBCB Unit at the Department of Biochemistry for ten years, working with Professor Mark Sansom. During that time I used computer simulation to study the function of a variety of membrane proteins, focussing mainly on cell signalling, transporters and ion channels.

Now I will be leading efforts to predict whether novel bacterial mutations lead to antibiotic resistance (or not). The key idea is to examine the effect of each mutation on the binding of the antibiotic to its target protein. This boils down to calculating how the binding free energy changes when you make the mutation — something that alchemical free energy methods, such as thermodynamic integration is well-suited to.

More soon.

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antimicrobial resistance clinical microbiology miscellaneous tuberculosis

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Comments (2)

  1. Oliver Beckstein says:
    14th March 2016 at 9:07 pm

    Congratulations, Phil!

    Cool to use statistical physics, computer simulations and structural biology to combat the pressing problem of bacterial resistance to antimicrobials. That’s a fight we (as a civilization) can’t afford to loose.

    Reply
  2. Pingback: Setting up a GROMACS cluster | Philip W Fowler

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