Professorship for Theoretical Physics - Computational Interface Physics

The Risselada group employs molecular simulation techniques to tackle re­le­vant problems in the field of biophysics and related molecular fields within a multidisciplinary and inter­dis­ci­plin­ary re­search environment (e.g., the RESOLV excellence cluster). Particularly, we focus on the development of enhanced sampling and multiscale methods to study phenomena occurring at fluid (e.g., biological lipid membranes) and solid interfaces (e.g., metal interfaces and graphene). An im­por­tant current focuses is on a subject coined "facial recognition of fluid interfaces", i.e., how can (bio)mol­ecules optimally recognize and bind fluid interfaces despite their highly disordered and dynamic nature. To this aim, we develop evolutionary molecular dynamics simulations (evo-MD) methods which couple evolutionary algorithms (sampling of chemical space) to coarse-grained molecular dynamic simulations (sampling of phase-space) to resolve the global optima in chemical space. In essence, evo-MD enables mol­ecules to adapt themselves to optimally recognize fluid interfaces in the course of a simulated evolution. Our re­search may yield unique insights on how biomolecules such as peptides and proteins recognize distinct fluid features in biological lipid membranes with interesting applications for the fields of drug de­sign, surfactant de­sign, and the de­sign of (bio)sensors.