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Structural classification of αββ and ββα supersecondary structure units in proteins
Authors:Nathalie S. Boutonnet  Andrey V. Kajava  Marianne J. Rooman
Abstract:We present a fully automatic structural classification of supersecondary structure units, consisting of two hydrogen-bonded β strands, preceded or followed by an α helix. The classification is performed on the spatial arrangement of the secondary structure elements, irrespective of the length and conformation of the intervening loops. The similarity of the arrangements is estimated by a structure alignment procedure that uses as similarity measure the root mean square deviation of superimposed backbone atoms. Applied to a set of 141 well-resolved nonhomologous protein structures, the classification yields 11 families of recurrent arrangements. In addition, fragments that are structurally intermediate between the families are found; they reveal the continuity of the classification. The analysis of the families shows that the α helix and β hairpin axes can adopt virtually all relative orientations, with, however, some preferable orientations; moreover, according to the orientation, preferences in the left/right handedness of the α–β connection are observed. These preferences can be explained by favorable side by side packing of the α helix and the β hairpin, local interactions in the region of the α–β connection or stabilizing environments in the parent protein. Furthermore, fold recognition procedures and structure prediction algorithms coupled to database-derived potentials suggest that the preferable nature of these arrangements does not imply their intrinsic stability. They usually accommodate a large number of sequences, of which only a subset is predicted to stabilize the motif. The motifs predicted as stable could correspond to nuclei formed at the very beginning of the folding process. Proteins 30:193–212, 1998. © 1998 Wiley-Liss, Inc.
Keywords:secondary structure arrangements  protein structure database  left/right topology  knowledge-based structure prediction  intrinsic stability
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