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

Abstract

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.

Integrative conformational ensembles of Sic1 using different initial pools and optimization methods

“…Experimental data is known to make ensembles more similar to one another (Ahmed et al, 2021; Larsen et al, 2020; Tiberti et al, 2015). Our results show that ensembles that agree with experimental data and were generated from an MD prior (a03ws-BME, a03ws-ENSEMBLE, a99SBdisp-ENSEMBLE) have similar H-bond PMFs.…”

Improving Martini 3 for disordered and multidomain proteins

“…We chose a set of twelve IDPs and three multidomain proteins to cover a range of different systems with available SAXS data ( Riback et al, 2017 ; Cordeiro et al, 2019 ; Mylonas et al, 2008 ; Riback et al, 2017 ; Ahmed et al, 2021 ; Martin et al, 2020 ; Johnson et al, 2017 ; Gomes et al, 2020 ; Kjaergaard et al, 2010 ; Jephthah et al, 2019 ; Fagerberg et al, 2020 ; Sonntag et al, 2017 ; Martin et al, 2021 ) and ran MD simulations of each protein using the Martini 3 force field. For all proteins, we found that the ensembles generated with Martini 3 were too compact when comparing the average R g from the simulations with values calculated from SAXS profiles using Guinier analyses.…”

“…We selected a set of twelve IDPs of varied sequence, with lengths between 24 and 334 amino acid residues and with SAXS data available: the N-terminal region of pertactin (PNt) ( Riback et al, 2017 ), the NR interaction domain of N-CoR (CoRNID) ( Cordeiro et al, 2019 ), two deletion mutants of Tau (K19 and K25) ( Mylonas et al, 2008 ), the ‘plug domain from a TonB-dependent receptor (FhuA) ( Riback et al, 2017 ), α-synuclein (aSyn) ( Ahmed et al, 2021 ), the low-complexity domain of hnRNPA1 (A1) ( Martin et al, 2020 ), theT-domain of colicin N (ColNT) ( Johnson et al, 2017 ), Sic1 ( Gomes et al, 2020 ), the activation domain of ACTR (ACTR) ( Kjaergaard et al, 2010 ), Histatin-5 (Hst5) ( Jephthah et al, 2019 ) and a tandem repeat of Histatin-5 (Hst52) ( Fagerberg et al, 2020 ) (Table 1).…”

Generating Ensembles of Dynamic Misfolding Proteins

“…In smFRET studies, care must be taken to ensure that the fluorescent dyes do not alter the proteins’ properties which is of key concern for IDPs/IDRs ( Borgia et al, 2016 ). Small angle X-ray scattering (SAXS), on the other hand, is a dye-free ensemble technique that reports on the overall shape of the protein under investigation and can be used to derive the overall compactness of the ensemble by weighting various conformations present in solution ( Różycki et al, 2011 ; Ahmed et al, 2021 ). Both techniques have been used extensively to generate ensemble representations of IDPs or multidomain proteins which contain a significant portion of IDRs ( Bernadó et al, 2005b ; Merchant et al, 2007 ; Holmstrom et al, 2018 ).…”