Wed, 20 Feb 2019, 16:00 CET (Berlin)

Prof. Dr. Matthias Rarey, Center for Bioinformatics, Hamburg, Germany

Machine learning in the context of bioactivity

The search for bioactive compounds is the key step in early drug discovery. Among other techniques, the sim­i­lar­i­ty principle (in the form of matched molecular pairs or free energy prediction), structure-based virtual screen­ing, and of course experimental high throughput screening are applied. In this talk, our results related to the use of machine learning (ML) in these three design scenarios are summarized. How well does classical ML on matched molecular pairs affinity data perform? What signals do ML-based scoring functions for protein-ligand docking capture? How can we make use of ML in the evaluation of experimental screening data?

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