The talk focuses on mycobacterial thioredoxin reductase (TrxR) as a promising tuberculosis drug target. TrxR is essential for thiol redox balance in Mycobacterium tuberculosis and differs from human enzymes, making selective inhibition possible. Prof. Koch will present two strategies for discovering inhibitors: structure-based design using high-throughput docking and crystallographic fragment screening supported by structure-based design and AI-based synthesis prediction.
About the speaker
Prof. Oliver Koch studied pharmacy and earned his PhD in pharmaceutical chemistry at the University of Marburg. He also completed postgraduate studies in computer science, focusing on machine learning and neural networks. After postdoctoral work at the Cambridge Crystallographic Data Centre, he returned to Germany as an independent junior group leader at TU Dortmund University. Since April 2022 he has been W2 Heisenberg Professor of Computational Drug Discovery at the University of Münster.
