title: Blast sampling for structural and functional analyses.
abstract: BACKGROUND
  The post-genomic era is characterised by a torrent of biological information flooding the public databases. As a direct consequence, similarity searches starting with a single query sequence frequently lead to the identification of hundreds, or even thousands of potential homologues. The huge volume of data renders the subsequent structural, functional and evolutionary analyses very difficult. It is therefore essential to develop new strategies for efficient sampling of this large sequence space, in order to reduce the number of sequences to be processed. At the same time, it is important to retain the most pertinent sequences for structural and functional studies.
  
  
  RESULTS
  An exhaustive analysis on a large scale test set (284 protein families) was performed to compare the efficiency of four different sampling methods aimed at selecting the most pertinent sequences. These four methods sample the proteins detected by BlastP searches and can be divided into two categories: two customisable methods where the user defines either the maximal number or the percentage of sequences to be selected; two automatic methods in which the number of sequences selected is determined by the program. We focused our analysis on the potential information content of the sampled sets of sequences using multiple alignment of complete sequences as the main validation tool. The study considered two criteria: the total number of sequences in BlastP and their associated E-values. The subsequent analyses investigated the influence of the sampling methods on the E-value distributions, the sequence coverage, the final multiple alignment quality and the active site characterisation at various residue conservation thresholds as a function of these criteria.
  
  
  CONCLUSIONS
  The comparative analysis of the four sampling methods allows us to propose a suitable sampling strategy that significantly reduces the number of homologous sequences required for alignment, while at the same time maintaining the relevant information concerning the active site residues.
authors.affiliation: Laboratoire de Bioinformatique et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. friedric@igbmc.u-strasbg.fr <friedric@igbmc.u-strasbg.fr>
authors.forename: Anne
authors.initials: A
authors.lastname: Friedrich
authors.forename: Raymond
authors.initials: R
authors.lastname: Ripp
authors.forename: Nicolas
authors.initials: N
authors.lastname: Garnier
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Bettler
authors.forename: Gilbert
authors.initials: G
authors.lastname: Deléage
authors.forename: Olivier
authors.initials: O
authors.lastname: Poch
authors.forename: Luc
authors.initials: L
authors.lastname: Moulinier
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D017124:Conserved Sequence; D003628:Database Management Systems; D030562:Databases, Protein; D016247:Information Storage and Retrieval / Q000379:methods*; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins