From integrative atomic-resolution ensembles of disordered proteins to simulations of phase-separated condensates.

Abstract

Dysregulation of biomolecular condensates of disordered proteins such as tau and TDP-43 is a driver of neurodegenerative diseases. A detailed understanding of the structure and dynamics of disordered proteins in dilute and condensed states will help to elucidate their roles in health and disease. However, the inherent flexibility of disordered proteins and their condensates makes structural studies and their interpretation challenging. Atomistic molecular dynamics simulations could help to address this challenge, but the need for long simulations has stymied progress. To overcome this limitation, we adopt a hierarchical approach, combining a highly accurate description of local structures with efficient sampling of possible global structures. We show how to make use of experimental data in the modeling of disordered proteins with a Bayesian formalism, overcoming the problem of exponentially varying weights in the ensemble refinement of long-chain polymeric molecules with importance sampling. Our atomic-resolution ensembles of dilute α-synuclein and tau agree well with small-angle X-ray scattering and NMR data, which were not used to generate the ensembles. For tau we find that pathogenic P301 mutations shift the ensemble towards locally more extended structures, which may be more aggregation prone. Using the same framework we simulate phase-separated condensates not just of tau but also of the neurodegeneration-linked protein TDP-43. Our atomistic simulations of TDP-43 complement coarse-grained simulations of its phase behavior which together demonstrate how phosphorylation of TDP-43 gives rise to an anti-aggregation effect. Thus TDP-43 phosphorylation may help to counteract progression of neurodegenerative diseases such as amyotrophic lateral sclerosis and frontotemporal dementia.