title: Non-sequential structure-based alignments reveal topology-independent core packing arrangements in proteins.
abstract: BACKGROUND
  Proteins of the same class often share a secondary structure packing arrangement but differ in how the secondary structure units are ordered in the sequence. We find that proteins that share a common core also share local sequence-structure similarities, and these can be exploited to align structures with different topologies. In this study, segments from a library of local sequence-structure alignments were assembled hierarchically, enforcing the compactness and conserved inter-residue contacts but not sequential ordering. Previous structure-based alignment methods often ignore sequence similarity, local structural equivalence and compactness.
  
  
  RESULTS
  The new program, SCALI (Structural Core ALIgnment), can efficiently find conserved packing arrangements, even if they are non-sequentially ordered in space. SCALI alignments conserve remote sequence similarity and contain fewer alignment errors. Clustering of our pairwise non-sequential alignments shows that recurrent packing arrangements exist in topologically different structures. For example, the three-layer sandwich domain architecture may be divided into four structural subclasses based on internal packing arrangements. These subclasses represent an intermediate level of structure classification, more general than topology, but more specific than architecture as defined in CATH. A strategy is presented for developing a set of predictive hidden Markov models based on multiple SCALI alignments.
authors.affiliation: Department of Biology, Rensselaer Polytechnic Institute Troy, NY 12180, USA.
authors.forename: Xin
authors.initials: X
authors.lastname: Yuan
authors.forename: Christopher
authors.initials: C
authors.lastname: Bystroff
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D017124:Conserved Sequence; D008390:Markov Chains; D008956:Models, Chemical; D015233:Models, Statistical; D008969:Molecular Sequence Data; D011487:Protein Conformation; D011506:Proteins / Q000032:analysis / Q000737:chemistry* / Q000145:classification*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins