The postsynaptic density (PSD) is a complex network of proteins located beneath the postsynaptic membrane. It contains a number of multivalent scaffold proteins that are organized into different layers and link membrane receptors to the cytoskeleton. The PSD is capable of dynamic reorganization, is characteristically different in specific neuron types and is involved in the molecular processes of learning and memory. We are using experimental and computational approaches to characterize selected proteins in detail and the network formation in general.

Recently developed computational tools allow for the generation of 'dynamic structural ensembles' corresponding to a set of conformers whose diversity reflects the experimentally determined internal dynamics of the molecule at a given time scale. The emphasis is on the correspondence with experimental data, which can be achieved using additional restraints, derived primarily from NMR spectroscopy, that are characteristic of the internal mobility. Such restraints are usually applied to multiple replicas of the simulated molecule simultaneously, requiring modifications and extensions of commonly available molecular dynamics software. The conformer sets resulting from such calculations serve as an atomic-detail model of the dynamic nature of the biomolecule and can be used to interpret biomolecular processes at high resolution.