Abstract
Intrinsically disordered proteins (IDPs) can adopt a range of conformations from globules to swollen coils. This large range of conformational preferences for different IDPs raises the question of how conformational preferences are encoded by sequence. Global compositional features of a sequence such as the fraction of charged residues and the net charge per residue engender certain conformational biases. However, more specific sequence features such as the patterning of oppositely charged residues, expansion driving residues, or residues that can undergo posttranslational modifications can also influence the conformational ensembles of an IDP. Here, we outline how to calculate important global compositional features and patterning metrics that can be used to classify IDPs into different conformational classes and predict relative changes in conformation for sequences with the same amino acid composition. Although increased effort has been devoted to determining conformational properties of IDPs in recent years, quantitative predictions of conformation directly from sequence remain difficult and often inaccurate. Thus, if quantitative predictions of conformational properties are desired, then sequence-specific simulations must be performed.
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Acknowledgments
I thank Alex S. Holehouse and Garrett Ginell for collating much of the small-angle X-ray scattering data shown in Table 3. I am also grateful to Rohit V. Pappu, Alex S. Holehouse, Megan C. Cohan, and Martin J. Fossat, as well as other members of the Pappu lab, for their many helpful discussions. I also thank Rahul K. Das, Alex S. Holehouse, and Tyler S. Harmon for use of their simulation results. This work was supported by the National Institutes of Health (grant 5R01NS056114 to Dr. Rohit V. Pappu).
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Ruff, K.M. (2020). Predicting Conformational Properties of Intrinsically Disordered Proteins from Sequence. In: Kragelund, B.B., Skriver, K. (eds) Intrinsically Disordered Proteins. Methods in Molecular Biology, vol 2141. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0524-0_18
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