Representation of the Protein Universe using Classifications, Maps, and Networks. Issue 8 (18th August 2014)

• Record Type: Journal Article
• Authors: Ben‐Tal, Nir; Kolodny, Rachel
• Is Part Of: Israel journal of chemistry. Volume 54:Issue 8/9(2014)
• Page Start: 1286
• Page End: 1292
• Publication Date: 2014-08-18
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1002/ijch.201400001
• Languages: English
• ISSNs: 0021-2148

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>Abstract</title> <p>A meaningful and coherent global picture of the protein universe is needed to better understand protein evolution and the underlying biophysics. We survey the studies that tackled this fundamental challenge, providing a glimpse of the protein space. A global picture represents all known local relationships among proteins, and needs to do so in a comprehensive and accurate manner. Three types of global representations can be used: classifications, maps, and networks. In these, the local relationships are derived, based on the similarity of the proteins′ sequences, structures, or functions (or a combination of these). Alternatively, the local relationships can be co‐occurrences of elements in the protein universe. The representations can be based on different objects: full polypeptide chains, fragments, such as structural domains, or even smaller motifs. Different protein qualities were revealed in each study; many point out the uniqueness of domains of the alpha/beta SCOP (structural classification of proteins) class.</p> </abstract>