Skip to content
Fowler Lab
Fowler Lab

Predicting antibiotic resistance de novo

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

Predicting antibiotic resistance de novo

New publication: Nothing to Sneeze At – A Dynamic and Integrative Computational Model of an Influenza A Virion

Philip Fowler, 6th March 2015

In this paper we show how we built and then simulated a model of the influenza A virion. Rather than model every atom of every lipid, a “coarse-grained” representation (MARTINI) is instead used which replaces roughly every four atoms by a single coarse-grained bead. Microsecond simulations then start to give us insight into how the surface proteins move and whether they cluster. For these simulations we used the PRACE supercomputer, CURIE, which is based in France. I’ve previously posted some scaling data on the different PRACE machines – the system used was not the virion but is similar in size.

With a system of this size and complexity just creating the initial set of coordinates is a challenge. My part in this project was to develop a new method for inserting the surface proteins into the lipids. This method is currently under review at another journal and I will update this blog post when it is published.

The paper is free to download and you can find it here.

Oh, and this makes three papers in the journal Structure in the last eight months which is new PB.

Share this:

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

Related

publication

Post navigation

Previous post
Next post

Related Posts

antimicrobial resistance

New preprint: compensatory mutations are associated with increased growth in resistant samples of M. tuberculosis.

22nd June 20238th December 2023

In this preprint, Viki Brunner shows how, using the large CRyPTIC dataset, she can recapitulate…

Share this:

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

New publication: Differential occupational risks to healthcare workers from SARS-CoV- 2

2nd July 202022nd August 2020

Very pleased and proud to be included on this manuscript, which has been published in…

Share this:

  • Click to share on X (Opens in new window) X
  • Click to share on Bluesky (Opens in new window) Bluesky
  • Click to email a link to a friend (Opens in new window) Email
  • Click to share on LinkedIn (Opens in new window) LinkedIn
  • Click to share on Mastodon (Opens in new window) Mastodon
Read More
publication

New Publication: NRas slows the rate at which a model lipid bilayer phase separates

13th June 2014

  Here we examine by computer simulation what effect adding a small cell-signalling protein does…

Share this:

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

Comment

  1. Pingback: New Publication: Alchembed | Philip W Fowler

Leave a Reply 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
    ©2025 Fowler Lab | WordPress Theme by SuperbThemes
     

    Loading Comments...