Prof. Martin Zacharias

Technische Universität München

Project P7: Dynamics of Substrate-Protease Interactions


Combining available structural and biochemical data with molecular modeling and simulation methods we will derive structural models in order to advance the understanding of how substrates are recognized and processed by γ-secretase and other intramembrane proteases.


MD simulations and molecular docking will be used to analyze structure, dynamics and enzyme interactions of substrates and to generate putative structural models for substrate binding to γ-secretase. These models will be generated by integrating available experimental data on mutations in the enzyme and substrates and biochemical and biophysical data obtained by experimental FOR2290 groups.


The models will form a basis for understanding the substrate recognition and possible design of inhibitors and modulators.


Publications (FOR 2290)


The dynamics of γ-secretase and its substrates.

Hitzenberger M, Götz A, Menig S, Brunschweiger B, Zacharias M, Scharnagl C.

Semin Cell Dev Biol. 2020 May 16. pii: S1084-9521(18)30274-X. doi: 10.1016/j.semcdb.2020.04.008. [Epub ahead of print] Review. PMID: 32423851



Uncovering the Binding Mode of γ -Secretase Inhibitors.

Hitzenberger M, Zacharias M.

ACS Chem Neurosci. 2019 Jun 25. doi: 10.1021/acschemneuro.9b00272. [Epub ahead of print] PMID: 31244051



Structural Modeling of γ-Secretase Aβ n Complex Formation and Substrate Processing.

Hitzenberger M, Zacharias M.

ACS Chem Neurosci. 2019 Mar 20;10(3):1826-1840. doi: 10.1021/acschemneuro.8b00725. Epub 2019 Jan 30. PMID: 30638370



 γ-Secretase Studied by Atomistic Molecular Dynamics Simulations: Global Dynamics, Enzyme Activation, Water Distribution and Lipid Binding
Manuel Hitzenberger, Martin Zacharias
Front Chem. 2018; 6: 640.
Published online 2019 Jan 4. doi: 10.3389/fchem.2018.00640 PMCID: PMC6328467

Research Unit FOR 2290