Innovative Computational Methods for Protein Structure Prediction, Drug Discovery, and Therapeutic Design

  • Jens Meiler (Vanderbilt University, Nashville Tenessee)
Hörsaal für Theoretische Physik Universität Leipzig (Leipzig)


The protein folding problem – i.e. predicting the three-dimensional structure of a protein from its amino acid sequence alone – is an unsolved problem in computational biology. I will present a novel computational approach to this problem that assembles protein tertiary structure from predicted secondary structure elements. I will demonstrate how this algorithm can be combined with limited EPR- and NMR-spectroscopic data to determine the structure of membrane proteins, an important class of proteins targeted by therapeutics. Structure- and Ligand-based computer aided drug discovery (CADD) algorithms are leveraged to develop small molecule therapeutics that bind to proteins. I will introduce ROSETTALIGAND, an algorithm that allows protein-small molecule docking with full protein and ligand flexibility. I will illustrate the application of machine learning algorithms for ligand-based CADD, specifically the discovery of allosteric modulators of human brain receptors for the treatment of schizophrenia and other neurological diseases.

19.11.13 13.10.20

Colloquium of the Faculty of Physics and Geosciences

MPI for Mathematics in the Sciences Live Stream

Katharina Matschke

MPI for Mathematics in the Sciences Contact via Mail