AUTOMATIC CLASSIFICATION AND ANALYSIS OF ALPHA-ALPHA-TURN MOTIFS IN PROTEINS

An automatic procedure for the classification of short protein fragmen ts, representing turn motifs between two consecutive secondary structu res, is presented. This procedure has two steps. Fragments of given le ngth are first grouped on the basis of their backbone dihedral angle v alues, and then clustered as a function of the root-mean-square deviat ion of their superimposed backbone atoms. The classification procedure identifies 63 families of turn motifs with at least five members, in a dataset of 141 proteins. A detailed analysis is presented of the ten identified alpha alpha-turn families, of which four correspond to nov el motifs. The sequence and structure features that characterize these families are described. It is found that some features are conserved within the fragments belonging to the same family, but their environme nt in the parent protein varies considerably. N-capping interactions a nd helix stop signals are encountered in a number of families, where t hey seem to stabilize the motif conformation. Tn two families, one wit h three residues in the loop, and one with four, an appreciable fracti on of the members displays both types of characteristic helix end inte ractions in the same motif. Interestingly, contrary to most other alph a alpha-turns, the relative frequency of these two motifs is much high er than that of short protein segments with the same loop conformation . Furthermore, the family with three residues in the loop includes the helix-turn-helix motif known to bind DNA. It seems to be the only one among the ten identified families that can be related to biological f unction. (C) 1996 Academic Press Limited