title: On the necessity of dissecting sequence similarity scores into segment-specific contributions for inferring protein homology, function prediction and annotation.
abstract: BACKGROUND
  Protein sequence similarities to any types of non-globular segments (coiled coils, low complexity regions, transmembrane regions, long loops, etc. where either positional sequence conservation is the result of a very simple, physically induced pattern or rather integral sequence properties are critical) are pertinent sources for mistaken homologies. Regretfully, these considerations regularly escape attention in large-scale annotation studies since, often, there is no substitute to manual handling of these cases. Quantitative criteria are required to suppress events of function annotation transfer as a result of false homology assignments.
  
  
  RESULTS
  The sequence homology concept is based on the similarity comparison between the structural elements, the basic building blocks for conferring the overall fold of a protein. We propose to dissect the total similarity score into fold-critical and other, remaining contributions and suggest that, for a valid homology statement, the fold-relevant score contribution should at least be significant on its own. As part of the article, we provide the DissectHMMER software program for dissecting HMMER2/3 scores into segment-specific contributions. We show that DissectHMMER reproduces HMMER2/3 scores with sufficient accuracy and that it is useful in automated decisions about homology for instructive sequence examples. To generalize the dissection concept for cases without 3D structural information, we find that a dissection based on alignment quality is an appropriate surrogate. The approach was applied to a large-scale study of SMART and PFAM domains in the space of seed sequences and in the space of UniProt/SwissProt.
  
  
  CONCLUSIONS
  Sequence similarity core dissection with regard to fold-critical and other contributions systematically suppresses false hits and, additionally, recovers previously obscured homology relationships such as the one between aquaporins and formate/nitrite transporters that, so far, was only supported by structure comparison.
authors.affiliation: Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore. wongwc@bii.a-star.edu.sg.
authors.forename: Wing-Cheong
authors.initials: WC
authors.lastname: Wong
authors.forename: Sebastian
authors.initials: S
authors.lastname: Maurer-Stroh
authors.forename: Birgit
authors.initials: B
authors.lastname: Eisenhaber
authors.forename: Frank
authors.initials: F
authors.lastname: Eisenhaber
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D017124:Conserved Sequence / Q000235:genetics; D006801:Humans; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid; D012984:Software
chemical_list: D011506:Proteins