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Maps of protein structure space reveal a fundamental relationship between protein structure and function.
Osadchy, Margarita; Kolodny, Rachel.
Affiliation
  • Osadchy M; Department of Computer Science, University of Haifa, Mount Carmel, Haifa 31905, Israel. rita@cs.haifa.ac.il
Proc Natl Acad Sci U S A ; 108(30): 12301-6, 2011 Jul 26.
Article in En | MEDLINE | ID: mdl-21737750
ABSTRACT
To study the protein structure-function relationship, we propose a method to efficiently create three-dimensional maps of structure space using a very large dataset of > 30,000 Structural Classification of Proteins (SCOP) domains. In our maps, each domain is represented by a point, and the distance between any two points approximates the structural distance between their corresponding domains. We use these maps to study the spatial distributions of properties of proteins, and in particular those of local vicinities in structure space such as structural density and functional diversity. These maps provide a unique broad view of protein space and thus reveal previously undescribed fundamental properties thereof. At the same time, the maps are consistent with previous knowledge (e.g., domains cluster by their SCOP class) and organize in a unified, coherent representation previous observation concerning specific protein folds. To investigate the function-structure relationship, we measure the functional diversity (using the Gene Ontology controlled vocabulary) in local structural vicinities. Our most striking finding is that functional diversity varies considerably across structure space The space has a highly diverse region, and diversity abates when moving away from it. Interestingly, the domains in this region are mostly alpha/beta structures, which are known to be the most ancient proteins. We believe that our unique perspective of structure space will open previously undescribed ways of studying proteins, their evolution, and the relationship between their structure and function.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Proteins Type of study: Prognostic_studies Language: En Year: 2011 Type: Article

Full text: 1 Database: MEDLINE Main subject: Proteins Type of study: Prognostic_studies Language: En Year: 2011 Type: Article