Detection of protein fold similarity based on correlation of amino acid properties.
An increasing number of proteins with weak sequence similarity have been found to assume similar three-dimensional fold and often have similar or related biochemical or biophysical functions. We propose a method for detecting the fold similarity between two proteins with low sequence similarity based on their amino acid properties alone. The method, the proximity correlation matrix (PCM) method, is built on the observation that the physical properties of neighboring amino acid residues in sequence at structurally equivalent positions of two proteins of similar fold are often correlated even when amino acid sequences are different. The hydrophobicity is shown to be the most strongly correlated property for all protein fold classes. The PCM method was tested on 420 proteins belonging to 64 different known folds, each having at least three proteins with little sequence similarity. The method was able to detect fold similarities for 40% of the 420 sequences. Compared with sequence comparison and several fold-recognition methods, the method demonstrates good performance in detecting fold similarities among the proteins with low sequence identity. Applied to the complete genome of Methanococcus jannaschii, the method recognized the folds for 22 hypothetical proteins.
Grigoriev
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Department of Chemistry and E. O. Lawrence Berkeley National Laboratory, University of California, Berkeley, CA 94720, USA.
Kim
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SH
D000595:Amino Acid Sequence; D017017:Methanococcus / Q000235:genetics; D017510:Protein Folding; D017433:Protein Structure, Secondary