A comparison of three methods to predict T cell-presented sequences within antigenic proteins led to the view that recurrent hydrophobic residues might nucleate excised peptides as alpha-helices against hydrophobic surfaces. Such helices could be protease-protected structures on their way to desetope binding. The compared methods were: the amphipathicity algorithm of DeLisi and Berzofsky [Proc. natn. Acad. Sci. U.S.A. 82, 7048-7052. (1985)] as modified by Margalit et al. [J. Immun. 138, 2213-2229. (1987)] the strip of-helix hydrophobicity algorithm (SOHHA) of Stille et al. [Molec. Immun. 24, 1021-1027. (1987)] and the motifs algorithm of Rothbard and Taylor [EMBO J. 7, 93-100. (1988)]. Correct prediction was defined at two levels of stringency: (1) the predicted sequence overlapped the experimentally reported sequence when the ratio of the intersection of both to the union of both greater than or equal to 0.5 or (2) the sequences touched when there was a non-empty intersection of both sequences. We determined the sensitivity (correct predictions/number of reported T cell-presented sequences) and efficiency (correct predictions/number of predictions) at each level of stringency. In terms of overlap, the SOHHA was more sensitive (0.43) than the amphipathicity (0.29) (not significant) and motifs (0.0, 0.0) (p less than 0.05) predictions and more efficient (0.35) than the amphipathicity (0.14) and motifs (0.0, 0.0) predictions. At the less stringent criterion touching, the amphipathicity method (0.71) was as sensitive as motif Rothbard-4 (0.79) and more sensitive than SOHHA (0.57) and motif Rothbard-5 (0.43). At that criterion, the SOHHA was more efficient (0.47) than the amphipathicity (0.36) and motifs (0.25, 0.40) methods. We hypothesize that the comparability of these approaches reflected the common, predominant influence of recurrent hydrophobicity in their predictions.

The strip-of-helix hydrophobicity algorithm was devised to identify protein sequences which, when coiled as alpha or 3(10) helices, had one axial, hydrophobic strip and otherwise variably hydrophilic residues. The strip-of-helix hydrophobicity algorithm also ranked such sequences according to an index, the mean hydrophobicity of amino acids in the axial strip. This algorithm well predicted T cell-presented fragments of antigenic proteins. A derivative of this algorithm (the structural helices algorithm (SHA] was tested for the prediction of helices in crystallographically defined proteins. For the SHA, eight amino acid sequences, 2 cycles plus one amino acid in an alpha helix, with strip-of-helix hydrophobicity indices greater than 2.5, were selected with overlapping segments joined. These selections were terminated according to simple "capping rules," which took into account the roles of N-terminal Asn or Pro and C-terminal Gly in the stability of helices. In analyses of 35 crystallographically defined proteins with known alpha and 3(10) helices, the predictions with the SHA overlapped (had overlap indices x greater than or equal to 0.5) with 34% of known helices, touched (had overlap indices 0.5 greater than x greater than 0) or overlapped with 66% of known helices, or were neighboring (came within 6 residues) or touched or overlapped with 82% of known helices. At each level of judging the quality of prediction, the SHA was usually less sensitive (correct predictions/total number of known helices) and more efficient (correct predictions/total number of predictions) than the Chou-Fasman and Garnier-Robson methods. It was simpler in design and calculation. The chemical mechanisms underlying these algorithms appear to apply both to protein folding and to selection of T cell-presented antigenic sequences.