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      Searching the protein structure databank with weak sequence patterns and structural constraints.

      Journal of Molecular Biology

      Amino Acid Sequence, Cytochrome c Group, chemistry, Databases as Topic, Endopeptidases, Epidermal Growth Factor, Kringles, Software, Molecular Sequence Data, Pattern Recognition, Automated, Proteins, Sensitivity and Specificity, Sequence Alignment, Sequence Homology, Amino Acid, Amino Acid Motifs

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          A method is described in which proteins that match PROSITE patterns are filtered by the root-mean-square deviation of the local 3D structures of the probe and target over the pattern components. This was found to increase the discrimination between true and false members of the protein family but was dependent on how unique the structural features in the pattern were compared to equivalent fragments extracted from the structure databank (for example; if the pattern fell in an alpha-helix, then discrimination was poor.) We then generalised the sequence patterns (by widening the range of amino acid residues allowed at each position) and monitored how well the structural information helped retain specificity. While the discrimination of the pure sequence pattern had generally disappeared at information content values less than ten bits, the discrimination of the combined sequence structure probe remained high at this point before following a similar decay. The displacement between these curves indicates that the structural component is, on average, equivalent to about ten bits. The sequence patterns were also filtered using the structure comparison program SAP, giving a global, rather than local "view" of the proteins. This allowed the information content of the sequence patterns to become even less specific but raised problems of whether some proteins encountered with the same fold but no PROSITE pattern should constitute family members. Copyright 2000 Academic Press.

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