title: Analysis of peptides from known proteins: clusterization in sequence space.
abstract: A combinatorial sequence space (CSS) model was introduced to represent sequences as a set of overlapping k-tuples of some fixed length which correspond to points in the CSS. The aim was to analyze clusterization of protein sequences in the CSS and to test various hypotheses about the possible evolutionary basis of this clusterization. The authors developed an easy-to-use technique which can reveal and analyze such a clusterization in a multidimensional CSS. Application of the technique led to an unexpectedly high clusterization of points in the CSS corresponding to k-tuples from known proteins. The clusterization could not be inferred from nonuniform amino acid frequencies or be explained by the influence of homologous data. None of the tested possible evolutionary and structural factors could explain the clusterization observed either. It looked as if certain protein sequence variations occurred and were fixed in the early course of evolution. Subsequent evolution (predominantly neutral) allowed only a limited number of changes and permitted new variants which led to preservation of certain k-tuples during the course of evolution. This was consistent with the theory of exon shuffling and protein block structure evolution. Possible applications of sequence space features found were also discussed.
authors: Supercomputer Computations Research Institute, Florida State University, Tallahassee 32306-4052.
authors: V B
authors: VB
authors: Strelets
authors: I N
authors: IN
authors: Shindyalov
authors: H A
authors: HA
authors: Lim
mesh_terms: D005075:Biological Evolution; D008957:Models, Genetic; D005810:Multigene Family; D010455:Peptides / Q000235:genetics*; D011506:Proteins / Q000235:genetics*
chemical_list: D010455:Peptides; D011506:Proteins