New Publication: Predicting affinities for peptide transporters Philip Fowler, 29th January 201629th September 2018 PepT1 is a nutrient transporter found in the cells that line your small intestine. It is not only responsible for the uptake of di- and tai-peptides, and therefore much of your dietary proteins, but also the uptake of most β-lactam antibiotics. This serendipity ensures that we can take (many of) these important drugs orally. Our ultimate goal is to develop the capability to predict modifications to drug scaffolds that will improve or enable their uptake by PepT1, thereby improving their oral bioavailability. In this paper, just published online in the new journal Cell Chemical Biology (and free to download, thanks to the Wellcome Trust), we show that it is possible to predict how well a series of di- and tai-peptides bind to a bacterial homologue of PepT1 using a hierarchical approach that combines an end-point free energy method with thermodynamic integration. Since there is no structure of PepT1, we then tried our method on a homology model we have published in 2015. We found that method lost its predictive power. By studying a range of homology models of intermediate quality, we showed that it is highly likely an experimental structure of hPepT1 will be required for in silico accurate predictions of transport. This is the second paper that Firdaus Samsudin has published as part of his DPhil here in Oxford. 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 computing molecular dynamics publication research
computing GROMACS on AWS 13th January 20164th December 2016 In this post I’m going to show how I created an Amazon Machine Instance with… 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 preprint: Predicting antibiotic resistance in complex protein targets 4th January 20224th January 2022 In this preprint, which Alice has been working on for several years, we show how… 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
citizen science Automated detection of bacterial growth on 96-well plates (AMyGDA) 11th December 20175th August 2018 I am involved in an international collaboration, the Comprehensive Resistance Prediction for Tuberculosis: an International Consortium… 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