Navigating in the Protein Universe

Abstract

How are proteins related to each other? Which physicochemical considerations affect protein evolution, and how? Forming a global picture of the protein universe can help address these, and similar, questions. We study the evolutionary relationships among a representative set of 9,710 protein domains, taken from the SCOP database. We align all-against-all domains, searching for significantly-sized shared segments, referred to as motifs. These motifs have similar sequence and structure, and thus are indicative of evolutionary relationships among the proteins. The results are presented as a similarity network, in which edges connect domains that share a motif. Using reasonable similarity thresholds, the network manifests a large connected component, as well as many isolated ‘islands’, revealing the complex nature of protein space, which includes continuous and discrete regions. Overall SCOP domains of the all-alpha, all-beta and alpha+beta classes, in which alpha and beta elements do not mix, populate the discrete region, while alpha/beta domains, with their alternating alpha and beta elements, populate the continuous one. The network can be interpreted as a collection of evolutionary paths in protein space. The large amount of paths within the alpha/beta class suggests that it is particularly easy to add and delete motifs between them. Apparently, evolution took advantage of this property in order to design new proteins with novel functions. This is the first study that combines sequence and structural similarity between proteins within the context of a network to provide a bird's eye view of the protein universe. The network offers a natural way to organize and search in protein space; we provide tools to this end by integrating Cytoscape with PyMOL and other molecular viewers. They could be used to theorize about protein evolution, suggest evolutionary pathways between domains, and maybe also strategies for protein design.