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The Order-Disorder Continuum: Linking Predictions of Protein Structure and Disorder through Molecular Simulation - PubMed

  • ️Wed Jan 01 2020

Review

The Order-Disorder Continuum: Linking Predictions of Protein Structure and Disorder through Molecular Simulation

Claire C Hsu et al. Sci Rep. 2020.

Abstract

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions within proteins (IDRs) serve an increasingly expansive list of biological functions, including regulation of transcription and translation, protein phosphorylation, cellular signal transduction, as well as mechanical roles. The strong link between protein function and disorder motivates a deeper fundamental characterization of IDPs and IDRs for discovering new functions and relevant mechanisms. We review recent advances in experimental techniques that have improved identification of disordered regions in proteins. Yet, experimentally curated disorder information still does not currently scale to the level of experimentally determined structural information in folded protein databases, and disorder predictors rely on several different binary definitions of disorder. To link secondary structure prediction algorithms developed for folded proteins and protein disorder predictors, we conduct molecular dynamics simulations on representative proteins from the Protein Data Bank, comparing secondary structure and disorder predictions with simulation results. We find that structure predictor performance from neural networks can be leveraged for the identification of highly dynamic regions within molecules, linked to disorder. Low accuracy structure predictions suggest a lack of static structure for regions that disorder predictors fail to identify. While disorder databases continue to expand, secondary structure predictors and molecular simulations can improve disorder predictor performance, which aids discovery of novel functions of IDPs and IDRs. These observations provide a platform for the development of new, integrated structural databases and fusion of prediction tools toward protein disorder characterization in health and disease.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1

(a) Experimental and simulation techniques used to define protein structure and dynamics at different time and length-scales. (“MD” – molecular dynamics; “AFM” – atomic force microscopy; “SAXS” – small angle X-ray scattering; “SANS” – small angle neutron scattering; “EM” – electron microscopy; “NMR” – nuclear magnetic resonance spectroscopy; “smFRET” – single molecule fluorescence resonance energy transfer) (b) Movement at different length-scales (bonds, side chains, residues, and domains) that can be characterized. Visualization with VMD.

Figure 2
Figure 2

% coil content vs order counter for sampled molecules, 3PLW (b) 2R6V (c) 1DZF (d) 3HZ8 (e) 3UMH. The five proteins are ordered from greatest to least coil content.

Figure 3
Figure 3

Prediction accuracy for all proteins in each of five bins (the test set split into bins of differing helix/beta content) in increasing order, using 2D-CNN as implemented in Supplemental Information. Confidence interval = 0.95.

Figure 4
Figure 4

Prediction Accuracy of 5 samples (a) 3PLW (b) 2R6V (c) 1DZF (d) 3HZ8 (e) 3UMH), with increasing order (sampled proteins).

Figure 5
Figure 5

Predicted disorder with IUPred, DisoPRED, and DISOclust predictors (i) and secondary structure prediction accuracy based on SPIDER3, DeepCNF, 2D-CNN, and SSPRO8 predictors (ii) highlighted with molecular structure longevity through molecular dynamics simulation (i, ii) for (a) 3PLW (b) 2R6V (c) 1DZF (d) 3HZ8 (e) 3UMH. For longevity, blue regions indicate higher longevity regions while white regions indicate lower longevity regions.

Figure 6
Figure 6

Models of the five sampled proteins in this study: (i) 3PLW (ii) 2R6V (iii) 1DZF (iv) 3HZ8 (v) 3UMH. (a) Molecular longevity on a red/blue scale for low/high structural longevity. (b) DSSP assignments with red (coiled), green (beta), and blue (helix) structures.

Figure 7
Figure 7

Root mean square fluctuation (RMSF) per-residue plots highlighted with molecular structure longevity through molecular dynamics simulation for (a) 3PLW (b) 2R6V (c) 1DZF (d) 3HZ8 (e) 3UMH. For longevity, blue regions indicate higher longevity regions while white regions indicate lower longevity regions.

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