Fold recognition and accurate sequence–structure alignment of sequences directing β‐sheet proteins

摘要: The ability to predict structure from sequence is particularly important for toxins, virulence factors, allergens, cytokines, and other proteins of public health importance. Many such functions are represented in the parallel beta-helix beta-trefoil families. A method using pairwise beta-strand interaction probabilities coupled with evolutionary information by profiles developed tackle these problems folds. algorithm BetaWrapPro employs a "wrapping" component that may capture folding processes an initiation stage followed processive already-formed motifs. outperforms all previous motif recognition programs folds, recognizing 100% sensitivity 99.7% specificity 92.5% specificity, crossvalidation on database nonredundant known positive negative examples fold classes PDB. It additionally aligns 88% residues beta-helices 86% beta-trefoils accurately (within four exact position) structural template, which then used side-chain packing program SCWRL produce 3D predictions. One striking result has been prediction unexpected pollen allergen, its recent confirmation through solution structure. Web server running available outputs putative PDB-style coordinates sequences predicted form target