Accuracy of protein hydropathy predictions.

Satu Jääskeläinen, Pentti Riikonen, Tapio Salakoski, Mauno Vihinen

Research output: Contribution to journalArticlepeer-review

3 Citations (SciVal)

Abstract

Hydropathy is a dominant force in protein folding. Sequence-based hydropathy predictions are widely used, without knowledge about their accuracy and reliability. We investigated the prediction accuracy of 56 hydropathy scales by correlating predicted values with the accessible surface area in known protein structures. Results for different amino acids vary greatly within each scale. We also investigated prediction accuracies of amino acids separately in secondary structural elements and in protein fold families. Despite very low overall correlation, hydropathy predictions can still be used if the shape of the plot is important instead of the prediction values.
Original languageEnglish
Pages (from-to)735-754
JournalInternational Journal of Data Mining and Bioinformatics
Volume4
Issue number6
Publication statusPublished - 2010
Externally publishedYes

Subject classification (UKÄ)

  • Medical Genetics

Keywords

  • Computational Biology: methods
  • Proteins: chemistry
  • Proteins: metabolism

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