Abstract

Self-assembly and protein-folding are examples of dynamical processes in which systems transform into ordered states that minimise their free energy. The time scales associated with these processes vary over a wide range: in particular, assembly or folding may be slow for a number of different reasons. Here, we concentrate on slow dynamics that comes from kinetic trapping in metastable states. In self-assembly, we discuss a set of kinetic factors that are essential in designing systems that will assemble effectively [1]. In protein-folding, we show how a novel method based on biased ensembles of trajectories can identify metastable states from large computational data sets. For several model proteins, the method identifies metastable states that are rich in beta-sheet structure [2]: we discuss possible connections with the formation of amyloid fibrils.

[1] S Whitelam and RL Jack, arXiv:1407.2505, to appear in Ann Rev Phys Chem. [2] JK Weber, RL Jack, CR Schwantes and VS Pande, Biophys J 107 , 974 (2014)