Lars Sandberg, Computational Chemist at the Drug Discovery Unit, University of Dundee
Room Kilsbregen, Alfa floor 4, SciLifeLab, Tomtebodavägen 23A, Solna
Good chemical starting points are likely to increase the chance for success of a drug discovery project. One way of finding starting points is by screening a large set of lead-like molecules available in-house (the screening library). Both the quantity and quality of the screening library compounds determine the success rate of finding opportune hits. I will present the way the brand new DDU-BMGF lead-like diversity library was designed and assembled.
Today drug discovery projects generate vast amounts of data, a majority of which will never be utilized by the project itself. However, if this data from all projects is compiled, it can be used to build statistical predictive models of the SAR driving screening assays. Such predictive chemistry models can be made available to all drug discovery projects and be used in the molecular design process to profile and rank virtual compounds and help guiding medicinal chemistry. I will discuss some examples of such models made public to the DDU.
For more information contact:
Ylva Gravenfors, ylva.gravenfors@localhost
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