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Multiscale Biomolecular Simulation

Sam I Riboswitch
SAM I Riboswitch with ligand.
Figure active conformation HK853
Active conformation of Histidine Kinase as deduced by integrating genomic analysis with molecular simulation.

The tremendous growth of computational resources in the last decades has enabled the use of computers to perform virtual experiments that study a wide range of questions in biology. Concurrent efforts in theory, experiment and simulation have emerged as a new paradigm to speed the discovery of scientific phenomena and new technological applications, in particular at the interface between the life and physical sciences.

The Research Group Multiscale Biomolecular Simulation aims at quantitatively understanding the structural and dynamical molecular mechanism of genetic regulation in HPC computer simulations. We want to connect method development directly with life-science applications and focus on systems of high biological relevance in the context of genetic regulation. Examples of such system which we currently investigate are Two-Component Signal Transduction Systems and regulatory ncRNA like Riboswitches or the group II intron. The challenge in simulating these systems is reaching sufficiently long time-scales while maintaining a realistic description. We therefore develop high-performance computational tools which apply a multi-scaling approach, in which we combine efficient sampling techniques at a coarse-grained level of description with more expensive but more detailed models. Ultimately, the knowledge gained on the biomolecular systems might find application in synthetic biology or pharmacology, by controlling their genetic regulation and helping development modules for synthetic biology.

General Public:

3 minutes video clip on protein folding simulations.

 

Open Positions:

Bachelor and Master-Thesis

Please contact me (schug∂kit.edu) directly to inquire about possible thesis topics. Typically, we are looking for candidates in the fields of:

  • Protein & RNA Structure Prediction using Co-Evolutionary Information
  • Coarse-Grained Simulations and Simulation Methods

PhD Thesis

currently no openings