title: Enhanced statistics for local alignment of multiple alignments improves prediction of protein function and structure.
abstract: BACKGROUND
  Improved comparisons of multiple sequence alignments (profiles) with other profiles can identify subtle relationships between protein families and motifs significantly beyond the resolution of sequence-based comparisons.
  
  
  RESULTS
  The local alignment of multiple alignments (LAMA) method was modified to estimate alignment score significance by applying a new measure based on Fisher's combining method. To verify the new procedure, we used known protein structures, sequence annotations and cyclical relations consistency analysis (CYRCA) sets of consistently aligned blocks. Using the new significance measure improved the sensitivity of LAMA without altering its selectivity. The program performed better than other profile-to-profile methods (COMPASS and Prof_sim) and a sequence-to-profile method (PSI-BLAST). The testing was large scale and used several parameters, including pseudo-counts profile calculations and local ungapped blocks or more extended gapped profiles. This comparison provides guidelines to the relative advantages of each method for different cases. We demonstrate and discuss the unique advantages of using block multiple alignments of protein motifs.
authors.affiliation: Department of Molecular Genetics, Weizmann Institute of Science Rehovot 76100, Israel.
authors.forename: Milana
authors.initials: M
authors.lastname: Frenkel-Morgenstern
authors.forename: Hillary
authors.initials: H
authors.lastname: Voet
authors.forename: Shmuel
authors.initials: S
authors.lastname: Pietrokovski
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D030562:Databases, Protein; D008956:Models, Chemical; D015233:Models, Statistical; D011506:Proteins / Q000032:analysis / Q000737:chemistry* / Q000145:classification*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins