Representation of the Protein Universe using Classifications, Maps, and Networks

Nir Ben-Tal, Rachel Kolodny

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Pages (from-to)1286-1292
Number of pages7
JournalIsrael Journal of Chemistry
Issue number8-9
StatePublished - 2014


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