Refinement of α-Synuclein Ensembles Against SAXS Data: Comparison of Force Fields and Methods

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt


The inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulation times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the protein α-synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data.

TidsskriftFrontiers in Molecular Biosciences
Antal sider13
StatusUdgivet - 2021

Bibliografisk note

Funding Information:
We thank A. Kikhney and C. Jeffries for assistance during data collection at the P12 SAXS beamline. We thank D. E. Shaw Research for sharing the molecular dynamics trajectories. Funding. We acknowledge support by a grant from the Lundbeck Foundation to the BRAINSTRUC Structural Biology Initiative (R155-2015-2666). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
© Copyright © 2021 Ahmed, Skaanning, Jussupow, Newcombe, Kragelund, Camilloni, Langkilde and Lindorff-Larsen.

Antal downloads er baseret på statistik fra Google Scholar og

Ingen data tilgængelig

ID: 262899103