Prof. Dr. Martin Zacharias


Biomolecular Dynamics

Academic Career and Research Areas

The research of Prof. Zacharias (b. 1961) focuses on the structure and dynamics of biomolecules. He uses computer simulation methods to study the movement of proteins and nucleic acids imaged with atomic resolution and understand the forces generated. A major goal is to understand the molecular mechanism of association processes between biomolecules in order to make realistic predictions about biomolecular structure formation and association. His work also involves creating realistic predictions on the structure formation and association of biomolecules.

After studying at Freie Universität Berlin, Prof. Zacharias did his doctorate there in 1991 in cooperation with the Max Planck Institute for Molecular Genetics. He went on to do postdoctoral research at the University of Houston and the University of Colorado. After that, he completed his lecturer qualification at Humboldt University in Berlin and headed up a research group at Leibniz Institute for Molecular Biotechnology in Jena. He took up a professorship at Jacobs University Bremen prior to accepting his current position of Chair of Biomolecular Dynamics at TUM in 2009.


  • Member “Faculty of 1000” (2009)
  • Affiliate Member PNNL (1999)
  • DFG-Habilitation scholarship holder (1996)
  • DFG Research Fellow (1992)

Zacharias M: "Predicting allosteric changes from conformational ensembles". Structure. 2017; 25(3): 393-394.


Hellenkamp B, Wortmann P, Kandzia F, Zacharias M, Hugel T: "Multidomain structure and correlated dynamics determined by self-consistent FRET networks". Nature Methods. 2017; 14(2): 174-180.


Schwierz N, Frost CV, Geissler PL, Zacharias M: "Dynamics of Seeded Aβ40-Fibril Growth from Atomistic Molecular Dynamics Simulations: Kinetic Trapping and Reduced Water Mobility in the Locking Step". Journal of the American Chemical Society. 2016; 138(2): 527-539.


Kilchherr F, Wachauf C, Pelz B, Rief M, Zacharias M, Dietz H: "Single-molecule dissection of stacking forces in DNA". Science. 2016; 353 (6304).


Schindler CE, de Vries SJ, Sasse A, Zacharias M: "SAXS Data Alone can Generate High-Quality Models of Protein-Protein Complexes". Structure. 2016; 24(8): 1387-1397.