In computational biology, the key goal is to circumvent the intrinsically slow dynamics due to the ruggedness of the free energy landscapes. Examples deal with the thermodynamic characterization of the different states of complex biomolecules, the description of the binding of different biomolecules, or its interaction with ions. Often this analysis is performed with classical force fields, either on the atomistic or the coarse grain level.
In computational chemistry, a more accurate, quantum mechanical, description of intra- and intermolecular interactions is required, in particular when chemical bonds are either formed or broken. Fully quantum-mechanical and hybrid QM/MM approaches usually suffer from severe sampling limitations due to their high computational cost. An important topic for this conference will be developing enhanced sampling techniques for this type of multi-scale simulation and the study the behavior close to interfaces.
In computational physics, free energy methods are, for instance, applied to characterize the phase behavior of complex condensed matter systems. Considerable efforts are being made in the field to devise computational methods to simulate temperature or pressure induced phase transitions in crystalline systems.
Free energy methods are also increasingly employed in other multi-disciplinary areas such as nanotechnology, materials science and computer-aided drug design, which all have significant economic and social impact within the European community.