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- W2147601891 abstract "Fuzzy cluster analysis has been applied to the 20 amino acids by using 65 physicochemical properties as a basis for classification. The clustering products, the fuzzy sets (i.e., classical sets with associated membership functions), have provided a new measure of amino acid similarities for use in protein folding studies. This work demonstrates that fuzzy sets of simple molecular attributes, when assigned to amino acid residues in a protein's sequence, can predict the secondary structure of the sequence with reasonable accuracy. An approach is presented for discriminating standard folding states, using near-optimum information splitting in half-overlapping segments of the sequence of assigned membership functions. The method is applied to a nonredundant set of 252 proteins and yields ˜73% matching for correctly predicted and correctly rejected residues with ˜60% overall success rate for the correctly recognized ones in three folding states: α-helix, β-strand, and coil. The most useful attributes for discriminating these states appear to be related to size, polarity, and thermodynamic factors. Van der Waals volume, apparent average thickness of surrounding molecular free volume, and a measure of dimensionless surface electron density can explain ˜95% of prediction results. Hydrogen bonding and hydrophobicity indices do not yet enable clear clustering and prediction." @default.
- W2147601891 created "2016-06-24" @default.
- W2147601891 creator A5070468507 @default.
- W2147601891 date "1995-06-01" @default.
- W2147601891 modified "2023-10-16" @default.
- W2147601891 title "Fuzzy cluster analysis of simple physicochemical properties of amino acids for recognizing secondary structure in proteins" @default.
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- W2147601891 doi "https://doi.org/10.1002/pro.5560040616" @default.
- W2147601891 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2143138" @default.
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