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SUMMARY:School of Chemistry Colloquium:  Dr Antonia Mey (University of Edinburgh)
DESCRIPTION:Proteins drive most biological processes. Understanding how proteins function and how they interact with other molecules is essential for us to comprehend life and aids in regulating diseases. One way to regulate protein function is through small molecules that interact with proteins to inhibit their activity. However, discovering new molecules and efficient methods to predict how effectively they may bind to a target protein is a challenging task.    Harnessing computational tools, using machine learning and molecular simulations, provides atomistic models for studying the interactions between a small molecule and a protein. To make computational models valuable, they need to have a predictive power such as proposing a ligand pose, typically done by docking algorithms, or a free energy of binding, often done through so called alchemical free energy calculations. In this talk, I will walk you through our process of creating new molecules from x-ray fragment hits using a generative machine learning model looking at the SARS-CoV-2 main protease. I will also highlight two different ways in which we can assess the free energy of binding: through machine learning and alchemical free energy calculations, where we will look at protein examples involved in cancers and antimicrobial resistance.     This talk is open to final year undergraduate project students, MSc students, PhD students, PDRAs and academic staff. https://events.st-andrews.ac.uk/events/school-of-chemistry-colloquium-dr-antonia-mey-university-of-edinburgh/
LOCATION:Purdie Building
URL:https://events.st-andrews.ac.uk/events/school-of-chemistry-colloquium-dr-antonia-mey-university-of-edinburgh/
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