Data-sieving hydrophobicity plots.
Hydrophobicity plots provide clues to the tertiary structure of proteins (J. Kyte and R. F. Doolittle, 1982, J. Mol. Biol. 157, 105; C. Chothia, 1984, Annu. Rev. Biochem. 53, 537; T. P. Hopp and K. R. Woods, 1982, Proc. Natl. Acad. Sci. USA 78, 3824). To render domains more visible, the raw data are usually smoothed using a running mean of between 5 and 19 amino acids. This type of smoothing still incorporates two disadvantages. First, peculiar residues that do not share the properties of most of the amino acids in the domain may prevent its identification. Second, as a low-pass frequency filter the running mean smoothes sudden transitions from one domain, or phase, to another. Data-sieving is described here as an alternative method for identifying domains within amino acid sequences. The data-sieve is based on a running median and is characterized by a single parameter, the mesh size, which controls its resolution. It is a technique that could be applied to other series data and, in multidimensions, to images in the same way as a median filter.
Bangham
J A
JA
School of Biology, University of East Anglia, Norwich, United Kingdom.
D000465:Algorithms; D000595:Amino Acid Sequence; D007091:Image Processing, Computer-Assisted; D011487:Protein Conformation; D011498:Protein Precursors; D011950:Receptors, Cholinergic
D011498:Protein Precursors; D011950:Receptors, Cholinergic