title: Combinatorial model for sequence and spatial motif discovery in short sequence fragments: examples from beta-barrel membrane proteins.
abstract: Motifs are over-represented sequence or spatial patterns appearing in proteins. They often play important roles in maintaining protein stability and in facilitating protein functions. When motifs are located in short sequence fragments, as in transmembrane domains that are only 10-20 residues in length, and when there is only very limited data, it is difficult to identify motifs. In this study, we develop combinatorial models for assessing statistically significant sequence and spatial patterns. We show our method can uncover previously unknown sequence and spatial motifs in beta-barrel membrane proteins.
authors.affiliation: Dept. of Bioeng., Illinois Univ., Chicago, IL 60607-7052, USA.
authors.forename: Ronald
authors.initials: R
authors.lastname: Jackups
authors.forename: Jie
authors.initials: J
authors.lastname: Liang
mesh_terms: D020816:Amino Acid Motifs; D001698:Biomedical Engineering; D006860:Hydrogen Bonding; D008565:Membrane Proteins / Q000737:chemistry* / Q000235:genetics; D008958:Models, Molecular; D015233:Models, Statistical; D010446:Peptide Fragments / Q000737:chemistry* / Q000235:genetics; D017510:Protein Folding; D017433:Protein Structure, Secondary; D020539:Sequence Analysis, Protein / Q000706:statistics & numerical data*
chemical_list: D008565:Membrane Proteins; D010446:Peptide Fragments