title: Structure-dependent sequence alignment for remotely related proteins.
abstract: BACKGROUND
  The quality of a model structure derived from a comparative modeling procedure is dictated by the accuracy of the predicted sequence-template alignment. As the sequence-template pairs are increasingly remote in sequence relationship, the prediction of the sequence-template alignments becomes increasingly problematic with sequence alignment methods. Structural information of the template, used in connection with the sequence relationship of the sequence-template pair, could significantly improve the accuracy of the sequence-template alignment. In this paper, we describe a sequence-template alignment method that integrates sequence and structural information to enhance the accuracy of sequence-template alignments for distantly related protein pairs.
  
  
  RESULTS
  The structure-dependent sequence alignment (SDSA) procedure was optimized for coverage and accuracy on a training set of 412 protein pairs; the structures for each of the training pairs are similar (RMSD< approximately 4A) but the sequence relationship is undetectable (average pair-wise sequence identity = 8%). The optimized SDSA procedure was then applied to extend PSI-BLAST local alignments by calculating the global alignments under the constraint of the residue pairs in the local alignments. This composite alignment procedure was assessed with a testing set of 1421 protein pairs, of which the pair-wise structures are similar (RMSD< approximately 4A) but the sequences are marginally related at best in each pair (average pair-wise sequence identity = 13%). The assessment showed that the composite alignment procedure predicted more aligned residues pairs with an average of 27% increase in correctly aligned residues over the standard PSI-BLAST alignments for the protein pairs in the testing set.
authors.affiliation: Department of Pharmacology and Columbia Genome Center, Columbia University, 630 West 168th street, PH 7 W Room 318, New York, NY 10032, USA. ay1@columbia.edu
authors.forename: An-Suei
authors.initials: AS
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000235:genetics; D011786:Quality Control; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins