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Evolutionary relationships in the glutathione reductase superfamily
Author(s) -
Ojha Sunil,
Meng Elaine,
Babbitt Patricia C
Publication year - 2006
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.20.5.a905-a
Subject(s) - superfamily , computational biology , context (archaeology) , genome , biology , protein superfamily , protein data bank (rcsb pdb) , mechanism (biology) , genetics , conserved sequence , protein family , gene , biochemistry , peptide sequence , paleontology , philosophy , epistemology
Computational methods are used to assign functions to many of the genes discovered by the genome projects and recent studies have shown that the degree of misannotation that results may be significant. Combining independent approaches based on homology and genome context to assign overall function and extrapolate details of chemical mechanism may result in fewer misannotations. Using a “mechanistically diverse superfamily” framework, we have clustered highly divergent sequences and structures from proteins in the glutathione reductase superfamily and correlated the conserved aspects of their chemical mechanisms with invariant structural features. We have clustered 1600 superfamily sequences into 9 subgroups comprising 15 families and extrapolated chemical mechanisms for characterized members to annotate hypothetical proteins assigned to each family. Independent support for these assignments was provided from genome context and co‐evolution profiles linking uncharacterized members to characterized proteins in each family. Further, comparisons of the active sites of the structurally characterized members of the superfamily illustrate how all have retained common structural characteristics to facilitate a hydride transfer between pyridine nucleotide and FAD, despite wide divergence in overall functions. Conserved aspects of chemical mechanism have also imposed constraints on the binding configuration of cofactors in the active sites, resulting in overall structural similarities and modes of protein‐protein interaction. Funding: PhRMA postdoctoral fellowship in informatics to SO and NIH GM60595 to PCB