title: Function-based assessment of structural similarity measurements using metal co-factor orientation.
abstract: Structure comparison is widely used to quantify protein relationships. Although there are several approaches to calculate structural similarity, specifying significance thresholds for similarity metrics is difficult due to the inherent likeness of common secondary structure elements. In this study, metal co-factor location is used to assess the biological relevance of structural alignments. The distance between the centroids of bound co-factors adds a chemical and function-relevant constraint to the structural superimposition of two proteins. This additional dimension can be used to define cut-off values for discriminating valid and spurious alignments in large alignment sets. The hypothesis underlying our approach is that metal coordination sites constrain structural evolution, thus revealing functional relationships between distantly related proteins. A comparison of three related nitrogenases shows the sequence and fold constraints imposed on the protein structures up to 18 Å away from the centers of their bound metal clusters.
authors.affiliation: Environmental Biophysics and Molecular Ecology Program, Institute of Marine and Coastal Sciences, Rutgers University, New Brunswick, New Jersey, 08901.
authors.forename: Stefan
authors.initials: S
authors.lastname: Senn
authors.forename: Vikas
authors.initials: V
authors.lastname: Nanda
authors.forename: Paul
authors.initials: P
authors.lastname: Falkowski
authors.forename: Yana
authors.initials: Y
authors.lastname: Bromberg
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D019943:Amino Acid Substitution; D060833:Cellular Microenvironment; D019295:Computational Biology; D008667:Metalloproteins / Q000737:chemistry* / Q000648:ultrastructure*; D008670:Metals / Q000737:chemistry*; D008958:Models, Molecular; D017510:Protein Folding; D017433:Protein Structure, Secondary; D016415:Sequence Alignment
chemical_list: D008667:Metalloproteins; D008670:Metals
keywords: computational biology; metalloproteins; structural bioinformatics; structural evolution; structure comparison