Interests

Membrane proteins play a central role in many of the biological activities of cells. Current estimates indicate that roughly 30% of the human genome codes for membrane proteins and it is believed that the overwhelming majority of drugs use them as targets. Nevertheless there are, at present, only a hand full of crystallographic structures at atomic or near-atomic resolutions. This is mainly due to difficulties with overexpression and crystallization of membrane proteins. A variety of computational techniques have been employed to provide both likely membrane protein structures and offer insight into their function and interaction with the membrane environment. Monte Carlo methods can provide useful information about the equilibrium state of a given system, be it the native folding state of a protein or its preferred position in a membrane. This is done by generating random trial moves that are rejected or accepted according to the Boltzmann weight of the respective energy differences they cause. Molecular Dynamics on the other hand offers a detailed view of the trajectory over time of a protein by solving explicitly the equations of motion for every atom in the system. This allows an analysis of the kinetics of membrane proteins and their surrounding. The focus of my research is the development of an implicit membrane representation to study membrane protein folding and function using Monte Carlo and Molecular Dynamics methods.