VDDE portfolio software
Engage in a virtual drug design exercise focused on team-based learning for final year undergraduate and MSc students in Chemistry for Drug Discovery. The exercise involves submitting new molecules weekly with no constraints, requiring the generation of physicochemical data and docking compounds against protein targets. Explore the multidisciplinary and time-consuming nature of this classroom exercise, as students work on software output and explore refining predictive models for huge time savings in drug discovery
Download Presentation
Please find below an Image/Link to download the presentation.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author.If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.
You are allowed to download the files provided on this website for personal or commercial use, subject to the condition that they are used lawfully. All files are the property of their respective owners.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author.
E N D
Presentation Transcript
VDDE portfolio software Steve Flower chssef@bath.ac.uk
Virtual Drug Design Exercise Team-based learning exercise Open ended (very!) Final Year Undergraduate Chemistry for Drug Discovery (8 sessions) MSc Drug Discovery (5 sessions)
A Multidisciplinary Team-Based Classroom Exercise for Small Molecule Drug Discovery Charlotte A. Dodson, Stephen E. Flower, and Mark Thomas J. Chem. Educ. 2023, 100, 9, 3320 3332 https://pubs.acs.org/doi/full/10.1021/acs.jchemed.3c00066
Very, very time consuming!!! Weekly: Each team submit 4 new molecules no constraints infinite variety! Requires: Generation of physicochemical data for 16-20 molecules Need to dock their compounds against the protein targets Each molecule: data from >5 different web- based predictors and 3 software packages
Summary Software development: Patrick Taylor and Toby Lewis-Atwell Have developed early-stage software to predict physicochemical data Huge time savings! Next steps: Refine model Automate docking and assay data
