New publication: Predicting resistance is (not) futile Philip Fowler, 21st August 201921st August 2019 Our “First Reactions” article has been published in ACS Central Science. We discuss the paper, Predicting Kinase Inhibitor Resistance: Physics-Based and Data-Driven Approaches, by Matteo Aldeghi, Vytautas Gapsys and Bert de Groot, which is in the same issue of the journal. Aldeghi et al. apply a series of methods to try and predict the effect of individual mutations on how well tyrosine kinase inhibitors bind to the Abl kinase. These methods include not only alchemical free energy methods but also machine learning. You can read it here. Share this:TwitterBlueskyEmailLinkedInMastodon Related antimicrobial resistance molecular dynamics publication
computing Setting up a GROMACS cluster 28th April 2016 Recently I’ve moved to the John Radcliffe hospital and my old lab kindly let me… Share this:TwitterBlueskyEmailLinkedInMastodon Pages: 1 2 3 4 5 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:TwitterBlueskyEmailLinkedInMastodon Read More
antimicrobial resistance New preprint: predicting rifampicin resistance 16th August 202416th August 2024 In this preprint we train a series of machine learning models on protein mutations found… Share this:TwitterBlueskyEmailLinkedInMastodon Read More