Skip to content
Fowler Lab
Fowler Lab

Predicting antibiotic resistance de novo

  • News
  • Publications
  • Members
  • Research
    • Overview
    • Manifesto
    • Software
    • Reproducibility
  • Teaching
  • Contact
    • PhDs
  • Wiki
Fowler Lab
Fowler Lab

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.

Share this:

  • Share on X (Opens in new window) X
  • Share on Bluesky (Opens in new window) Bluesky
  • Email a link to a friend (Opens in new window) Email
  • Share on LinkedIn (Opens in new window) LinkedIn
  • Share on Mastodon (Opens in new window) Mastodon

Related

antimicrobial resistance clinical microbiology miscellaneous tuberculosis

Post navigation

Previous post
Next post

Related Posts

antimicrobial resistance

GARC: A Grammar for Antimicrobial Resistance Catalogues

25th November 201817th November 2020

During the CRyPTIC project it has become obvious that we need a grammar to describe…

Share this:

  • Share on X (Opens in new window) X
  • Share on Bluesky (Opens in new window) Bluesky
  • Email a link to a friend (Opens in new window) Email
  • Share on LinkedIn (Opens in new window) LinkedIn
  • Share on Mastodon (Opens in new window) Mastodon
Read More
antimicrobial resistance

New publication: Assessing Drug Susceptibility in Tuberculosis

28th September 201829th September 2018

A paper was published in the New England Journal of Medicine earlier this week by…

Share this:

  • Share on X (Opens in new window) X
  • Share on Bluesky (Opens in new window) Bluesky
  • Email a link to a friend (Opens in new window) Email
  • Share on LinkedIn (Opens in new window) LinkedIn
  • Share on Mastodon (Opens in new window) Mastodon
Read More

Dylan’s bedaquline paper one of the most read in Microbial Genomics in September!

20th October 202520th October 2025

Received a lovely email from Dr Peter Cotgreave who is the Chief Executive of the…

Share this:

  • Share on X (Opens in new window) X
  • Share on Bluesky (Opens in new window) Bluesky
  • Email a link to a friend (Opens in new window) Email
  • Share on LinkedIn (Opens in new window) LinkedIn
  • Share on Mastodon (Opens in new window) Mastodon
Read More

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

Leave a Reply to Oliver Beckstein Cancel reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.

To find out more, including how to control cookies, see here: Cookie Policy
    ©2026 Fowler Lab | WordPress Theme by SuperbThemes