Protein-ligand binding affinities are driven by the balance between multiple factors, many of which can only partially be accounted for by force field-based methods.
On the contrary, the first principle nature of quantum mechanics (QM) calculations enables systematic improvements to the accuracy by which biomolecular recognition is described.
Despite the greater accuracy, QM methods have not been routinely used in drug discovery due to the high computational costs required to deal with large biological systems.
This webinar will show examples in which the QM was applied to different problems in the early stages of drug discovery, from assessing water energetics, to helping the design of macrocycles, fragment optimisation and potency prediction.
About the Presenter
Dr Iva Lukac is driven to find ways of efficiently visualizing scientific data and developing new computational methods to help bring us one step closer to a new medicine.
Following completion of her PhD Iva worked at the Drug Discovery Unit at the University of Dundee, alongside scientists focused on developing new treatments for neglected tropical disease.
At the same time Machine Learning and AI in drug discovery was gaining momentum, and so Iva enrolled with the University of Dundee to study for an MSc in Data Science which she was awarded in 2022.
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