Structural classification of alphabetabeta and betabetaalpha supersecondary structure units in proteins.

We present a fully automatic structural classification of supersecondary structure units, consisting of two hydrogen-bonded beta strands, preceded or followed by an alpha 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 alpha helix and beta 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 alpha-beta connection are observed. These preferences can be explained by favorable side by side packing of the alpha helix and the beta hairpin, local interactions in the region of the alpha-beta 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.

Automatic analysis of protein conformational changes by multiple linkage clustering.

An automatic algorithm is presented for analyzing protein conformational changes such as those occurring upon substrate binding or in different crystal forms of the same protein. Using, as sole information, the atomic coordinates of a pair of protein structures, the procedure first generates structure alignments, which optimize the root-mean-square deviation of the backbone atoms. To this end, equivalent secondary structures and/or loops from both proteins are combined by a multiple linkage hierarchic clustering algorithm, which generates several intertwined clustering trees. Automatic analysis of these clustering trees is used to dissect the mechanism of the conformational change. It allows the identification of the static core, representing the collection of secondary structures which undergo no structural changes, as well as other entities which move like rigid bodies. It also permits the description of the movement of secondary structures or loops relative to this core or entities. USing this information, it can be inferred whether a particular conformational change involves shear or hinge motion, or components of both. The algorithm is applied to the analysis of the conformational changes of citrate synthase, lactate dehydrogenase, lactoferrin and beta-glucosyltransferase, representing typical examples of shear- and hinge-type mechanisms, and a varied range in movement size. The results are shown to be in excellent agreement with previous analyses, and to provide additional information which gives a more complete and objective picture of the conformational change. Using our automatic algorithm, we find that any conformational change may be viewed as having components of both shear- and hinge-type motion. Determining which of these is most appropriate requires the combination of the information provided by our procedure with detailed knowledge of the protein tertiary structures.

Optimal protein structure alignments by multiple linkage clustering: application to distantly related proteins.

A fully automatic procedure for aligning two protein structures is presented. It uses as sole structural similarity measure the root mean square (r.m.s.) deviation of superimposed backbone atoms (N, C alpha, C and O) and is designed to yield optimal solutions with respect to this measure. In a first step, the procedure identifies protein segments with similar conformations in both proteins. In a second step, a novel multiple linkage clustering algorithm is used to identify segment combinations which yield optimal global structure alignments. Several structure alignments can usually be obtained for a given pair of proteins, which are exploited here to define automatically the common structural core of a protein family. Furthermore, an automatic analysis of the clustering trees is described which enables detection of rigid-body movements between structure elements. To illustrate the performance of our procedure, we apply it to families of distantly related proteins. One groups the three alpha + beta proteins ubiquitin, ferredoxin and the B1-domain of protein G. Their common structure motif consists of four beta-strands and the only alpha-helix, with one strand and the helix being displaced as a rigid body relative to the remaining three beta-strands. The other family consists of beta-proteins from the Greek key group, in particular actinoxanthin, the immunoglobulin variable domain and plastocyanin. Their consensus motif, composed of five beta-strands and a turn, is identified, mostly intact, in all Greek key proteins except the trypsins, and interestingly also in three other beta-protein families, the lipocalins, the neuraminidases and the lectins. This result provides new insights into the evolutionary relationships in the very diverse group of all beta-proteins.