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Intrinsically semi-disordered state and its role in induced folding and protein aggregation - PubMed

Intrinsically semi-disordered state and its role in induced folding and protein aggregation

Tuo Zhang et al. Cell Biochem Biophys. 2013.

Abstract

Intrinsically disordered proteins (IDPs) refer to those proteins without fixed three-dimensional structures under physiological conditions. Although experiments suggest that the conformations of IDPs can vary from random coils, semi-compact globules, to compact globules with different contents of secondary structures, computational efforts to separate IDPs into different states are not yet successful. Recently, we developed a neural-network-based disorder prediction technique SPINE-D that was ranked as one of the top performing techniques for disorder prediction in the biannual meeting of critical assessment of structure prediction techniques (CASP 9, 2010). Here, we further analyze the results from SPINE-D prediction by defining a semi-disordered state that has about 50% predicted probability to be disordered or ordered. This semi-disordered state is partially collapsed with intermediate levels of predicted solvent accessibility and secondary structure content. The relative difference in compositions between semi-disordered and fully disordered regions is highly correlated with amyloid aggregation propensity (a correlation coefficient of 0.86 if excluding four charged residues and proline, 0.73 if not). In addition, we observed that some semi-disordered regions participate in induced folding, and others play key roles in protein aggregation. More specifically, a semi-disordered region is amyloidogenic in fully unstructured proteins (such as alpha-synuclein and Sup35) but prone to local unfolding that exposes the hydrophobic core to aggregation in structured globular proteins (such as SOD1 and lysozyme). A transition from full disorder to semi-disorder at about 30-40 Qs is observed in the poly-Q (poly-glutamine) tract of huntingtin. The accuracy of using semi-disorder to predict binding-induced folding and aggregation is compared with several methods trained for the purpose. These results indicate the usefulness of three-state classification (order, semi-disorder, and full-disorder) in distinguishing nonfolding from induced-folding and aggregation-resistant from aggregation-prone IDPs and in locating weakly stable, locally unfolding, and potentially aggregation regions in structured proteins. A comparison with five representative disorder-prediction methods showed that SPINE-D is the only method with a clear separation of semi-disorder from ordered and fully disordered states.

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Figures

Fig. 1
Fig. 1

The distribution of disorder probability predicted by SPINE-D at residue level before (a) and after scaling (b) and at long segment level (>30 amino acid residues) (c) for three datasets (DX4080, SL477, and Control703). The insert in (a) shows the fine detail around the disorder probability of 0.06. The negative control set (stable monomeric proteins) does not have a peak for fully disordered residues or regions, indicating the usefulness of separating semi-disorder from full disorder

Fig. 2
Fig. 2

Ordered (green), semi-disordered (blue), and fully disordered (red) regions in term of fraction of exposed residues (x-axis) and fraction of residues with secondary structures (y-axis) based on SPINE-D results of the DX4080 dataset. A residue is defined as exposed if its predicted solvent accessibility is greater than 25 %. Secondary structures and solvent accessibility are predicted by SPINE-X and Real-SPINE 3, respectively (Color figure online)

Fig. 3
Fig. 3

(a) The Gibbs triangle diagram of the fractions of residues in three states (ordered, semi-disordered, fully disordered residues) for all proteins in the three datasets as labeled. Each protein is a point and its position is determined by three fractions of residues. (b) Disorder probability profiles with zero ordered residues (f o = 0) for the chain A of the PDB ID 2qt4 (2qt4A) in the control set, for DP00179 (chain B in PDB ID 1DPJ) in SL477, and for chain C of PDB ID 2prg (2prgC) in DX4080. The semi-disordered regions correspond to structured regions (horizontal lines) stabilized by disulfide bonds (2qt4A), by binding-induced folding (DP00179 and 2prgC). Only one structured region of 2prgC bound with its target is visible in this figure. The gray area indicates the region defined as semi-disordered

Fig. 4
Fig. 4

Structured regions (blue bar) by induced folding of disordered proteins are compared with their semi-disordered regions (probability profile within the gray region) in eight additional proteins with predicted f o = 0 in the DX4080 dataset (PDB IDs as labeled). Only one structured region (1ytvN) corresponds to a fully disordered region at the N-terminal end of chain N of 1ytv. But it is semi-disordered after removing the terminal effect (dashed line). The N-terminal region of chain G of 1mey (consensus zinc finger) does not have coordinates but the same region in identical chains C and F does. Thus, the whole chain G made of mostly the semi-disordered state can be labeled as structured from residue 1 to 85 after binding with DNA in a trimeric form (Color figure online)

Fig. 5
Fig. 5

Transition of the polyglutamine tract of huntingtin from a fully disordered to a partially semi-disordered state. Fraction of glutamines (Qs) in a semi-disordered state (fQ in red) and the average disorder probability (P, in blue) in the poly-Q region as a function of the number of glutamines in the poly-Q tract of huntingtin (Color figure online)

Fig. 6
Fig. 6

Semi-disordered state in unstructured (alpha-synuclein and Sup35) and structured proteins (SOD1 and human lysozyme). Predicted disordered probability profiles (P in red) compared with compaction ratios for three different regions at normal pH from combined NMR experiments and replica exchange molecular dynamics simulations of alpha-synuclein (in blue) (a), the measured Cys accessibility profile (scaled by the largest accessibility of 82.2 %, in blue) of yeast Sup 35 (b), root mean squared distance (RMSD) from native by molecular dynamics simulations of SOD1 (c), and the unstructured regions in a partially unfolded state detected by H/D exchange (blue) and the fibril core region from proteolysis (orange) (d). In (c), open regions in blue line correspond locally unfolded regions of SOD1. RMSD values are rescaled and shifted to facilitate comparison. The gray bar indicates the region defined as semi-disordered in disorder probability (0.4 ≤ P ≤ 0.7) (Color figure online)

Fig. 7
Fig. 7

The disorder probability profile of acylphosphate from hyperthermophilic archaeon Sulfolobus solfataricus (Sso AcP) predicted from SPINE-D (red line). The semi-disordered residues from 1 to 12 at the N-terminal after removing terminal effect agree with the unstructured region for the first 12 residues from the NMR experiment (PDB #1Y9O) (blue) (Color figure online)

Fig. 8
Fig. 8

Strong positive correlation between amyloid aggregation propensity at pH 7 and relative difference in compositions of amino acid residue types between semi-disordered and fully disordered regions [(Crsd−Crfd)/Crfd, green squares] or between ordered and semi-disordered regions [(Cro−Crsd)/Crsd, blue circles] generated from the DX4080 dataset. Cro,Crsd, and Crfdare compositions of amino acid residues for ordered, semi-disordered, and fully disordered states, respectively. Above and below zero of [(Crsd−Crfd)/Crfd] or [(Cro−Crsd)/Crsd] indicates enrichment or depletion relative to fully disordered regions or semi-disordered regions, respectively

Fig. 9
Fig. 9

(a) Distributions of predicted disorder probabilities for five on-line servers (Disopred2, IU-long, MD, MFDp, and Dispro) in addition to SPINE-D as labeled. (b) Disorder probability of yeast Sup 35 predicted by the above five methods in addition to SPINE-D as labeled. No methods except SPINE-D (in red) separated a collapsed N-terminal region and an extended C-terminal region in agreement with the experimental Cys accessibility data (in black) (Color figure online)

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