title: Ensemble approach to predict specificity determinants: benchmarking and validation.
abstract: BACKGROUND
  It is extremely important and challenging to identify the sites that are responsible for functional specification or diversification in protein families. In this study, a rigorous comparative benchmarking protocol was employed to provide a reliable evaluation of methods which predict the specificity determining sites. Subsequently, three best performing methods were applied to identify new potential specificity determining sites through ensemble approach and common agreement of their prediction results.
  
  
  RESULTS
  It was shown that the analysis of structural characteristics of predicted specificity determining sites might provide the means to validate their prediction accuracy. For example, we found that for smaller distances it holds true that the more reliable the prediction method is, the closer predicted specificity determining sites are to each other and to the ligand.
  
  
  CONCLUSIONS
  We observed certain similarities of structural features between predicted and actual subsites which might point to their functional relevance. We speculate that majority of the identified potential specificity determining sites might be indirectly involved in specific interactions and could be ideal target for mutagenesis experiments.
authors: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA. chakraba@ncbi.nlm.nih.gov
authors: Saikat
authors: S
authors: Chakrabarti
authors: Anna R
authors: AR
authors: Panchenko
mesh_terms: D019985:Benchmarking; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*
chemical_list: D011506:Proteins