Martin Zacharias

Center of Functional Protein Assemblies and Physics Department, Technical University of Munich , Ernst-Otto-Fischer-Str. 8, D-85747 Garching, Germany

Protein interaction modulation studied by ligand design and molecular simulations

Abstract

Protein molecules and the interaction with other biomolecules are essential for many biological processes including signal transduction, immune reactions and many diseases. Recent machine learning and deep learning methods allow one to predict the structure of proteins in complex with other biomolecules and also with organic ligands. Complex formation of proteins often results in new pockets at the interface that can be targets for binding of complex stabilizing compounds. We have developed and evaluated molecular simulation approaches to identify such putative binding cavities. In combined with ligand and cyclic peptide design methods our efforts also focus on identifying possible new compounds binding at protein-protein complex interfaces. In addition, the realistic evaluation and scoring of putative binders is of critical importance. The application of rapid knowledge-based as well as molecular simulation based free energy calculations to score designed binders will also be discussed.