title: CLIPS-1D: analysis of multiple sequence alignments to deduce for residue-positions a role in catalysis, ligand-binding, or protein structure.
abstract: BACKGROUND
  One aim of the in silico characterization of proteins is to identify all residue-positions, which are crucial for function or structure. Several sequence-based algorithms exist, which predict functionally important sites. However, with respect to sequence information, many functionally and structurally important sites are hard to distinguish and consequently a large number of incorrectly predicted functional sites have to be expected. This is why we were interested to design a new classifier that differentiates between functionally and structurally important sites and to assess its performance on representative datasets.
  
  
  RESULTS
  We have implemented CLIPS-1D, which predicts a role in catalysis, ligand-binding, or protein structure for residue-positions in a mutually exclusive manner. By analyzing a multiple sequence alignment, the algorithm scores conservation as well as abundance of residues at individual sites and their local neighborhood and categorizes by means of a multiclass support vector machine. A cross-validation confirmed that residue-positions involved in catalysis were identified with state-of-the-art quality; the mean MCC-value was 0.34. For structurally important sites, prediction quality was considerably higher (mean MCC = 0.67). For ligand-binding sites, prediction quality was lower (mean MCC = 0.12), because binding sites and structurally important residue-positions share conservation and abundance values, which makes their separation difficult. We show that classification success varies for residues in a class-specific manner. This is why our algorithm computes residue-specific p-values, which allow for the statistical assessment of each individual prediction. CLIPS-1D is available as a Web service at http://www-bioinf.uni-regensburg.de/.
  
  
  CONCLUSIONS
  CLIPS-1D is a classifier, whose prediction quality has been determined separately for catalytic sites, ligand-binding sites, and structurally important sites. It generates hypotheses about residue-positions important for a set of homologous proteins and focuses on conservation and abundance signals. Thus, the algorithm can be applied in cases where function cannot be transferred from well-characterized proteins by means of sequence comparison.
authors.affiliation: Institute of Biophysics and Physical Biochemistry, University of Regensburg, 93040 Regensburg, Germany. Rainer.Merkl@biologie.uni-regensburg.de
authors.forename: Jan-Oliver
authors.initials: JO
authors.lastname: Janda
authors.forename: Markus
authors.initials: M
authors.lastname: Busch
authors.forename: Fabian
authors.initials: F
authors.lastname: Kück
authors.forename: Mikhail
authors.initials: M
authors.lastname: Porfenenko
authors.forename: Rainer
authors.initials: R
authors.lastname: Merkl
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D002384:Catalysis; D005994:Glycerophosphates / Q000378:metabolism; D007209:Indole-3-Glycerol-Phosphate Synthase / Q000737:chemistry / Q000378:metabolism; D020407:Internet; D008024:Ligands; D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D016415:Sequence Alignment / Q000379:methods*; D048229:Sulfolobus solfataricus / Q000201:enzymology; D060388:Support Vector Machine
chemical_list: D005994:Glycerophosphates; D008024:Ligands; D011506:Proteins; C008117:indoleglycerol phosphate; D007209:Indole-3-Glycerol-Phosphate Synthase