Global view of the protein universe

Abstract

To explore protein space from a global perspective, we consider 9,710 SCOP (Structural Classification of Proteins) domains with up to 70% sequence identity and present all similarities among them as networks: In the "domain network," nodes represent domains, and edges connect domains that share "motifs," i.e., significantly sized segments of similar sequence and structure. We explore the dependence of the network on the thresholds that define the evolutionary relatedness of the domains. At excessively strict thresholds the network falls apart completely; for very lax thresholds, there are network paths between virtually all domains. Interestingly, at intermediate thresholds the network constitutes two regions that can be described as "continuous" versus "discrete." The continuous region comprises a large connected component, dominated by domains with alternating alpha and beta elements, and the discrete region includes the rest of the domains in isolated islands, each generally corresponding to a fold. We also construct the "motif network," in which nodes represent recurring motifs, and edges connect motifs that appear in the same domain. This network also features a large and highly connected component of motifs that originate from domains with alternating alpha/ beta elements (and some all-alpha domains), and smaller isolated islands. Indeed, the motif network suggests that nature reuses such motifs extensively. The networks suggest evolutionary paths between domains and give hints about protein evolution and the underlying biophysics. They provide natural means of organizing protein space, and could be useful for the development of strategies for protein search and design.protein cooccurrence networks | protein similarity networks H ow are proteins related to each other? Which physicochemical considerations affect protein evolution and how? A global view of the protein universe may shed light on these fundamental questions. It could also suggest new strategies for protein search and design (1-3). However, forming a global picture of the protein universe is difficult because we have to piece it together from the many local glimpses that our empirical data and computational tools provide. In other words, a global picture needs to portray the relationships among all proteins, yet we only have evidence of such relationships among several proteins, based on the similarity between their sequences, structures, and functions. The considerable size of the Protein Data Bank (4) also complicates this task.In particular, an intensely debated question is whether protein space is "discrete" or "continuous" (2, 3, 5-10). These terms are loosely defined. Discrete implies that the global picture consists of separate, island-like, structural entities. In the hierarchical protein domains Structural Classification of Proteins (SCOP) (11) these entities are termed "folds," and in the CATH database (12) they are called "topologies." Alternatively, "continuous" implies that the space between these entities is generally populated by...

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