title: INTREPID--INformation-theoretic TREe traversal for Protein functional site IDentification.
abstract: BACKGROUND
  Identification of functionally important residues in proteins plays a significant role in biological discovery. Here, we present INTREPID--an information-theoretic approach for functional site identification that exploits the information in large diverse multiple sequence alignments (MSAs). INTREPID uses a traversal of the phylogeny in combination with a positional conservation score, based on Jensen-Shannon divergence, to rank positions in an MSA. While knowledge of protein 3D structure can significantly improve the accuracy of functional site identification, since structural information is not available for a majority of proteins, INTREPID relies solely on sequence information. We evaluated INTREPID on two tasks: predicting catalytic residues and predicting specificity determinants.
  
  
  RESULTS
  In catalytic residue prediction, INTREPID provides significant improvements over Evolutionary Trace, ConSurf as well as over a baseline global conservation method on a set of 100 manually curated enzymes from the Catalytic Site Atlas. In particular, INTREPID is able to better predict catalytic positions that are not globally conserved and hence, attains improved sensitivity at high values of specificity. We also investigated the performance of INTREPID as a function of the evolutionary divergence of the protein family. We found that INTREPID is better able to exploit the diversity in such families and that accuracy improves when homologs with very low sequence identity are included in an alignment. In specificity determinant prediction, when subtype information is known, INTREPID-SPEC, a variant of INTREPID, attains accuracies that are competitive with other approaches for this task.
  
  
  BACKGROUND
  INTREPID is available for 16919 families in the PhyloFacts resource (http://phylogenomics.berkeley.edu/phylofacts).
authors.affiliation: Department of Electrical Engineering & Computer Science and Department of Bioengineering, University of California, Berkeley, USA. sriram_s@cs.berkeley.edu
authors.forename: Sriram
authors.initials: S
authors.lastname: Sankararaman
authors.forename: Kimmen
authors.initials: K
authors.lastname: Sjölander
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D030562:Databases, Protein; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000235:genetics; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein; D012984:Software
chemical_list: D011506:Proteins
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