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. 2021 Apr:271:106552.
doi: 10.1016/j.bpc.2021.106552. Epub 2021 Jan 26.

Effects of pH on an IDP conformational ensemble explored by molecular dynamics simulation

Richard J Lindsay  1 , Rachael A Mansbach  2 , S Gnanakaran  3 , Tongye Shen  4
Affiliations

Effects of pH on an IDP conformational ensemble explored by molecular dynamics simulation

Richard J Lindsay et al. Biophys Chem. 2021 Apr.

Abstract

The conformational ensemble of intrinsically disordered proteins, such as α-synuclein, are responsible for their function and malfunction. Misfolding of α-synuclein can lead to neurodegenerative diseases, and the ability to study their conformations and those of other intrinsically disordered proteins under varying physiological conditions can be crucial to understanding and preventing pathologies. In contrast to well-folded peptides, a consensus feature of IDPs is their low hydropathy and high charge, which makes their conformations sensitive to pH perturbation. We examine a prominent member of this subset of IDPs, α-synuclein, using a divide-and-conquer scheme that provides enhanced sampling of IDP structural ensembles. We constructed conformational ensembles of α-synuclein under neutral (pH ~ 7) and low (pH ~ 3) pH conditions and compared our results with available information obtained from smFRET, SAXS, and NMR studies. Specifically, α-synuclein has been found to in a more compact state at low pH conditions and the structural changes observed are consistent with those from experiments. We also characterize the conformational and dynamic differences between these ensembles and discussed the implication on promoting pathogenic fibril formation. We find that under low pH conditions, neutralization of negatively charged residues leads to compaction of the C-terminal portion of α-synuclein while internal reorganization allows α-synuclein to maintain its overall end-to-end distance. We also observe different levels of intra-protein interaction between three regions of α-synuclein at varying pH and a shift towards more hydrophilic interactions with decreasing pH.

Keywords: Alpha-synuclein; FRET; Intrinsically disordered protein; Molecular dynamics.

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Conflict of interest statement

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1.
Figure 1.
An overview of sampling method used to study α-synuclein. Panel I illustrates the cutting of a protein into shorter segments. Panel II represents the use of molecular dynamics simulations to produce a diverse ensemble of conformers fora given segment. Panel III depicts the combining of conformers to produce full IDP structures. Panel IV depicts the weighting process used to obtain the final ensemble statistics.
Figure 2.
Figure 2.
(top panel) Sequence of human α-synuclein with charged residues labeled for asyn3 and asyn7. Individual segments are denoted by shaded boxes with overlapping regions shown by overlapping frames. The charge state of each amino acid at pH 3 is shown above the sequence and charge state of pH 7 is shown below. (lower left) A list of charge properties for each segment. (lower right) A running sum of the charge of α-synuclein at pH 7 (black) and pH 3 (red), where the total charge can be read at the C-terminus as −8 e and +16 e, respectively.
Figure 3.
Figure 3.
(A) The probability distribution of gyradius for asyn7 (black) and asyn3 (red). The black dashed line represents the experimental gyradius value at physiological pH calculated by Araki et. al [28] using SEC-SAXS. The dotted-dashed lines show SAXS-based gyradius values calculated by Fink et. al at physiological pH (black) and pH ~ 3 (red). (B) The internal scaling profile is shown for asyn7 (black) and asyn3 (red).
Figure 4.
Figure 4.
Inverse of residue pair distances (selected residues to E130 at C-terminus) obtained from simulation. They are selected for a direct comparison with available experimental data and arranged in the same order used in FRET efficiency (Figure 2 of ref. [26]). The distributions of 1/r are shown with pH ~ 7 represented by a black line and pH ~ 3 represented by a red line.
Figure 5.
Figure 5.
Distance distributions of six charged residue pairs for asyn7 (black) and asyn3 (red). Panel A has the largest sequence distance between residues, which decreases with each panel.
Figure 6.
Figure 6.
Secondary structure composition of asyn7 ensemble (A) and asyn3 ensemble (B). Multiple types of coils and turns indicative of disorder are excluded for clarity. Y-axis represents the fraction of conformers where a structure is present.
Figure 7.
Figure 7.
Results of contact analyses. (A) Weighted contact maps representing the persistent contacts at each pH condition are shown, with asyn7 on the left and asyn3 on the right. (B) The graph depicts the first principal component resulting from mean implicit principal component analysis (mi-PCA), with neutral pH represented by a black line and low pH with a red line. (C) Residues are re-ranked according to their hydrophobicity and contacts are plotted onto this hydrophobicity space. Index 1 represents the least hydrophobic (most hydrophilic) residue and index 140 represents the most hydrophobic (least hydrophilic) residue. All rankings are based on the physiological pH condition. (C, left) Hydrophobicity-ranked contact map for asyn7. (C, right) Hydrophobicity-ranked contact map for asyn3. (D) Residues are shown re-ranked by hydrophobicity with contacts between differing regions (N-terminus, NAC, C-terminus) represented by different colors.
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