Improving protein order-disorder classification using charge-hydropathy plots

Fei Huang, Christopher J. Oldfield, Bin Xue, Wei Lun Hsu, Jingwei Meng, Xiaowen Liu, Li Shen, Pedro Romero, Vladimir N. Uversky, A. Keith Dunker

Research output: Contribution to journalArticle

29 Scopus citations


Background: The earliest whole protein order/disorder predictor (Uversky et al., Proteins, 41: 415-427 (2000)), herein called the charge-hydropathy (C-H) plot, was originally developed using the Kyte-Doolittle (1982) hydropathy scale (Kyte & Doolittle., J. Mol. Biol, 157: 105-132(1982)). Here the goal is to determine whether the performance of the C-H plot in separating structured and disordered proteins can be improved by using an alternative hydropathy scale. Results: Using the performance of the CH-plot as the metric, we compared 19 alternative hydropathy scales, with the finding that the Guy (1985) hydropathy scale (Guy, Biophys. J, 47:61-70(1985)) was the best of the tested hydropathy scales for separating large collections structured proteins and intrinsically disordered proteins (IDPs) on the C-H plot. Next, we developed a new scale, named IDP-Hydropathy, which further improves the discrimination between structured proteins and IDPs. Applying the C-H plot to a dataset containing 109 IDPs and 563 non-homologous fully structured proteins, the Kyte-Doolittle (1982) hydropathy scale, the Guy (1985) hydropathy scale, and the IDP-Hydropathy scale gave balanced two-state classification accuracies of 79%, 84%, and 90%, respectively, indicating a very substantial overall improvement is obtained by using different hydropathy scales. A correlation study shows that IDP-Hydropathy is strongly correlated with other hydropathy scales, thus suggesting that IDP-Hydropathy probably has only minor contributions from amino acid properties other than hydropathy. Conclusion: We suggest that IDP-Hydropathy would likely be the best scale to use for any type of algorithm developed to predict protein disorder.

Original languageEnglish (US)
Article numberS4
JournalBMC bioinformatics
Issue number17
StatePublished - Dec 16 2014


  • Intrinsically disordered proteins
  • Natively unstructured or unfolded proteins
  • Structure and disorder prediction
  • Support vector machines

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Improving protein order-disorder classification using charge-hydropathy plots'. Together they form a unique fingerprint.

  • Cite this

    Huang, F., Oldfield, C. J., Xue, B., Hsu, W. L., Meng, J., Liu, X., Shen, L., Romero, P., Uversky, V. N., & Dunker, A. K. (2014). Improving protein order-disorder classification using charge-hydropathy plots. BMC bioinformatics, 15(17), [S4].