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Natively Disordered Proteins

Functions and Predictions

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Abstract

Proteins can exist in at least three forms: the ordered form (solid-like), the partially folded form (collapsed, molten globule-like or liquid-like) and the extended form (extended, random coil-like or gas-like). The protein trinity hypothesis has two components: (i) a given native protein can be in any one of the three forms, depending on the sequence and the environment; and (ii) function can arise from any one of the three forms or from transitions between them. In this study, bioinformatics and data mining were used to investigate intrinsic disorder in proteins and develop neural network-based predictors of natural disordered regions (PONDR) that can discriminate between ordered and disordered residues with up to 84% accuracy. Predictions of intrinsic disorder indicate that the three kingdoms follow the disorder ranking eubacteria < archaebacteria ≪ eukaryotes, with approximately half of eukaryotic proteins predicted to contain substantial regions of intrinsic disorder. Many of the known disordered regions are involved in signalling, regulation or control. Involvement of highly flexible or disordered regions in signalling is logical: a flexible sensor more readily undergoes conformational change in response to environmental perturbations than does a rigid one. Thus, the increased disorder in the eukaryotes is likely the direct result of an increased need for signalling and regulation in nucleated organisms. PONDR can also be used to detect molecular recognition elements that are disordered in the unbound state and become structured when bound to a biologically meaningful partner. Application of disorder predictions to cell-signalling, cancer-associated and control protein databases supports the widespread occurrence of protein disorder in these processes.

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Acknowledgements

This work has been supported by the Indiana Genomics Initiative (INGEN), which in turn is funded in part by the Lilly Endowment. NIH grant 1-RO1-LM007688-01A1 also provided support.

There are no potential conflicts of interest directly relevant to the content of this study.

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Correspondence to Dr Pedro Romero.

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Romero, P., Obradovic, Z. & Dunker, A.K. Natively Disordered Proteins. Appl-Bioinformatics 3, 105–113 (2004). https://doi.org/10.2165/00822942-200403020-00005

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Keywords

  • Nuclear Magnetic Resonance
  • Intrinsic Disorder
  • Sequence Window
  • Label Dataset
  • Disorder Prediction