Research in our group focuses on the physics of proteins. Here, it is crucial to understand for a given protein the relation between its sequence of amino acids and the set of thermally accessible conformations, and to comprehend the mechanism by which the protein folds into its native structure. This problem is of enormous importance as the function of a protein is closely related to its 3D shape, and mis-folded proteins can cause a variety of diseases.

Computer experiments offer one way to gain such knowledge but are extremely difficult for realistic protein models: all-atom models lead to a rough energy landscape with a huge number of local minima separated by high barriers. Hence, sampling of low-energy conformations becomes a hard computational task, and physical quantities cannot be calculated accurately from simple low-temperature molecular dynamics or Monte Carlo simulations.

A significant part of our research is concerned with overcoming this multiple-minima problem in protein simulations. Its center piece is the continuing development and advancement of novel numerical techniques (the generalized-ensemble approach) with the final goal of simulating stable domains in proteins (usually of order 50-200 residues). Multicanonical sampling, parallel tempering and energy landscape paving are some of the techniques used in our group. These techniques allow sampling of low-energy configurations without that the simulations gets trapped in a local minimum. As an example we show in the figure the time series of temperature and energy as obtained in a parallel tempering simulation of the 36-residue protein HP-36. The figure is taken from C.Y. Lin, C.-K. Hu and U.H.E. Hansmann, Proteins 52 (2003) 436. Related to our algorithmic work is the development and publication of new software for simulations of protein. Our programs are collected in the free program package SMMP (Simple Molecular Mechanics for Proteins).

Current applications of our techniques focus on probing the mechanism of folding in small proteins and the conditions under which proteins mis-fold and aggregate. This often involves analysis of the energy landscape of these molecules. We show as an example the folding funnel of the 20-residue trp-cage protein with an overlap of the configuration found at the bottom of the funnel with the experimentally determined structure (the figure is taken from A. Schug, W. Wenzel and U.H.E. Hansmann, J. Chem. Phys., 122 (2005) 194711). Protein-ligand binding and protein interaction networks are other questions that we study and provide an interface with bioinformatics groups.

A potential application of the technqiues developed in our group is the prediction of structure and function of proteins solely from their chemical composition (the sequence of amino acids). Our results from the recent CASP7 competition of structure prediction methods can be found here.

A more detailed introduction into the research of our group can be found in the Outline of research directions.