Using prediction profiles with both a and P motifs

Using prediction profiles with both a and P motifs 

Membrane import machinery protein mas6 yeast was predicted with a maximum of only two short transmembrane helices 101-116 and 201-215, instead of four expected, but with many potential amphipathic P-strands. High peak in P-amphipathicity just next to the LDL or IDI motif is found at the mas6 yeast residue 69, mpcp rat (from mitochondrial carrier family) residue 83 and achl xenla residue 350. Observed amphipathic P-structure of a leucine rich repeat peptide LRP32 also contains LDL motif [99]. This motif may be important 

The observation that conformational preferences are specified by the contexts - local segment primary structure, amino acid attributes, the three-dimensional environment in protein and environmental media, has been discussed before [102-105] Algorithms that do take into account context-dependence of preferences [106] generally perform better for secondary structure prediction In this report simple mathematical representation of context dependence is obtained through preference flmctions that are analytical fiinctions of the surrounding sequence hydrophobicity or of any other amino acid attribute. Furthermore, preference functions are used to predict secondary structure motifs. It has turned out that for integral membrane proteins preference functions are excellent predictors of transmembrane segments in helical conformation In fact preference functions are much better predictors than the hydrophobicity scale chosen to extract these functions. 

Transmembrane helical segments are predicted by us with a high accuracy in 168 integral membrane proteins. All of 168 tested membrane proteins are recognized as such, because at least one transmembrane segment is predicted in each protein. No TMH is predicted in porins. 

The main goal of this work was accurate prediction of transmembrane helical structures, but we do realize that membrane proteins may exist that have both a-helices and P-strands as transmembrane structure. Preference function method is capable of predicting separately a-helical and P-strand conformation of segments that have potential to become 

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