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. 2012 Oct;180(1):201-15.
doi: 10.1016/j.jsb.2012.05.013. Epub 2012 May 29.

High-throughput characterization of intrinsic disorder in proteins from the Protein Structure Initiative

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High-throughput characterization of intrinsic disorder in proteins from the Protein Structure Initiative

Derrick E Johnson et al. J Struct Biol. 2012 Oct.

Abstract

The identification of intrinsically disordered proteins (IDPs) among the targets that fail to form satisfactory crystal structures in the Protein Structure Initiative represents a key to reducing the costs and time for determining three-dimensional structures of proteins. To help in this endeavor, several Protein Structure Initiative Centers were asked to send samples of both crystallizable proteins and proteins that failed to crystallize. The abundance of intrinsic disorder in these proteins was evaluated via computational analysis using predictors of natural disordered regions (PONDR®) and the potential cleavage sites and corresponding fragments were determined. Then, the target proteins were analyzed for intrinsic disorder by their resistance to limited proteolysis. The rates of tryptic digestion of sample target proteins were compared to those of lysozyme/myoglobin, apomyoglobin, and α-casein as standards of ordered, partially disordered and completely disordered proteins, respectively. At the next stage, the protein samples were subjected to both far-UV and near-UV circular dichroism (CD) analysis. For most of the samples, a good agreement between CD data, predictions of disorder and the rates of limited tryptic digestion was established. Further experimentation is being performed on a smaller subset of these samples in order to obtain more detailed information on the ordered/disordered nature of the proteins.

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Figures

Figure 1
Figure 1
Evaluation of the abundance of intrinsic disorder in proteins at various stages of the structure determination pipelines. A. The distribution of target proteins successfully passed through the different stages of these pipelines. The number of proteins at each stage is divided by the number of selected proteins. B. Abundance of predicted disordered residues in sequences of proteins at major pipeline stages. Here, at any given stage, the values calculated for each sequence were summed up and divided by the number of proteins and this stage. C. Amount of proteins containing predicted IDRs longer than 30 residues at each structure determination stage. D. Relative number of proteins with predicted long IDRs, which are at least 100 residue-long. For all plots, disorder was evaluated using the PONDR® VSL2 predictor. Sequences for this plot were obtained from the target progress tracking database (TargetDB: http://targetdb.rcsb.org).
Figure 2
Figure 2
Cumulative Distribution Function (CDF) and CH-plot of standards and example proteins: Panel A – boundary (), lysozyme c (), apomyoglobin (), α-casein(); Panel B – boundary (), lysozyme c (), apomyoglobin(), α-casein().
Figure 3
Figure 3
PONDR® plot and trypsin digestion prediction of standards. VSL2P (blue), VL3E (green), VLXT (red), potentially accessible, disorder-based cut sites (), inaccessible cut sites (x)). Panel A – α-casein; Panel B – myoglobin and apo-myoglobin; Panel C – lysozyme.
Figure 4
Figure 4
Time course of the limited trypsin digestion of standard proteins by 0.2 µM trypsin (A, C, and E) and 1 µM trypsin (B, D, and F). Plots A and B show the digestion results for α-casein. Plots C and D represent the data on the apo-myoglobin trypsinolysis. Plots E and F illustrate tryptic cleavage of lysozyme. In each plot, the first and the last lanes correspond to the molecular mass standards. Numbers reflect the time points at which the proteolysis was quenched.
Figure 5
Figure 5
Spectroscopic analysis of the standard proteins. A. Near-UV CD spectra of standard proteins at 1 mg/ml. B. Far-UV CD spectra of standard proteins at 1 mg/ml.
Figure 6
Figure 6
Crystal structure of BSGCAIR30378 (PDB ID: 2I15). A. Structure of the BSGCAIR30378 trimer. B. Structure of the monomeric species (cartoon representation). C. Structure of the monomeric species (solvent accessible surface representation). D. Multiple structure alignment of the three monomeric species from the biological unit of BSGCAIR30378 (PDB ID: 2I15). The alignment was performed using the MultiProt tool (http://bioinfo3d.cs.tau.ac.il/MultiProt/) (Shatsky et al., 2004). All images were created using the VMD tool (Humphrey et al., 1996).
Figure 7
Figure 7
Disorder analysis of BSGCAIR30378. A. PONDR® plots (VSL2P (blue), VL3 (green), VLXT (red)) and trypsin digestion prediction (potentially accessible cut sites (), inaccessible cut sites (x)). B. SDS-PAGE analysis of limited digestion. C. Far-UV CD spectrum. D. Near-UV CD spectrum.
Figure 8
Figure 8
Disorder analysis of BSGCAIR30903. A. PONDR® plots (VSL2P (blue), VL3 (green), VLXT (red)) and trypsin digestion prediction (potentially accessible cut sites (), inaccessible cut sites (x)). B. SDS-PAGE analysis of limited digestion. C. Far-UV CD spectrum. D. Near-UV CD spectrum.
Figure 9
Figure 9
Disorder analysis of NYSGXRC10336x. A. PONDR® plots (VSL2P (blue), VL3 (green), VLXT (red)) and trypsin digestion prediction (potentially accessible cut sites (), inaccessible cut sites (x)). B. SDS-PAGE analysis of limited digestion. C. Far-UV CD spectrum. D. Near-UV CD spectrum.
Figure 10
Figure 10
Disorder analysis of BSGCAIR30998. A. PONDR® plots (VSL2P (blue), VL3 (green), VLXT (red)) and trypsin digestion prediction (potentially accessible cut sites (), inaccessible cut sites (x)). B. SDS-PAGE analysis of limited digestion. C. Far-UV CD spectrum. D. Near-UV CD spectrum.
Figure 11
Figure 11
Cumulative distribution function (CDF) (plots A and B) and CH-plot analyses (plots C and D) of non-crystallizable (plots A and C) and crystallizable (plots B and D) PSI target proteins.
Figure 12
Figure 12
Far- (plots A and C) and near-UV CD spectra (plots B and D) of non-crystallizable (plots A and B) and crystallizable (plots C and D) PSI targets analyzed in this study.

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