On the Evolution of Protein Folds: Are Similar Motifs in Different Protein Folds the Result of Convergence, Insertion, or Relics of an Ancient Peptide World?

Lupas, Andrei N.; Ponting, Chris P.; Russell, Robert B.

doi:10.1006/jsbi.2001.4393

Cited by 268 publications

(282 citation statements)

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“…These clusters lend support to a theory on the origin of folded proteins, which proposes that these structure-and sequencesimilar fragments seen in disparate molecular contexts represent remnants of an ancient peptide-RNA world, thus suggesting that today's domains have arisen by fusion, amplification, and divergence from a simpler set of peptide modules. [22][23][24] We do not observe some clusters that we expected from reported instances of remote homology. One reason is that many of these involve domains with few homologs of known structure.…”

Section: Resultsmentioning

confidence: 49%

“…Their evolutionary relationship has also been proposed previously. 14,23 A further cluster comprises the eukaryotic (Type-I) and the prokaryotic (Type-II) KH-domains, which are topologically distinct but homologous. 43 The similarity between these folds is limited to a baab motif.…”

Section: Resultsmentioning

confidence: 99%

“…[15][16][17] Occasionally, even the boundaries between folds have been broken either due to the discovery of homologous fold change [18][19][20][21] or due to the detection of conserved supersecondary structures, which may represent remnants of an ancient peptide-RNA world. [22][23][24] These findings suggest that proteins might not be as polyphyletic as hitherto assumed.…”

Section: Introductionmentioning

confidence: 82%

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A galaxy of folds

et al. 2009

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Many protein classification systems capture homologous relationships by grouping domains into families and superfamilies on the basis of sequence similarity. Superfamilies with similar 3D structures are further grouped into folds. In the absence of discernable sequence similarity, these structural similarities were long thought to have originated independently, by convergent evolution. However, the growth of databases and advances in sequence comparison methods have led to the discovery of many distant evolutionary relationships that transcend the boundaries of superfamilies and folds. To investigate the contributions of convergent versus divergent evolution in the origin of protein folds, we clustered representative domains of known structure by their sequence similarity, treating them as point masses in a virtual 2D space which attract or repel each other depending on their pairwise sequence similarities. As expected, families in the same superfamily form tight clusters. But often, superfamilies of the same fold are linked with each other, suggesting that the entire fold evolved from an ancient prototype. Strikingly, some links connect superfamilies with different folds. They arise from modular peptide fragments of between 20 and 40 residues that co-occur in the connected folds in disparate structural contexts. These may be descendants of an ancestral pool of peptide modules that evolved as cofactors in the RNA world and from which the first folded proteins arose by amplification and recombination. Our galaxy of folds summarizes, in a single image, most known and many yet undescribed homologous relationships between protein superfamilies, providing new insights into the evolution of protein domains.

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Section: Resultsmentioning

confidence: 49%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 82%

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A galaxy of folds

et al. 2009

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“…For example, genetic recombination can cause loss or duplication of parts of genes, entire genes, or even longer chromosomal regions; mobile genetic elements (DNA transposons and retro-transposons) can lead to duplication or deletions (26). It may be, however, as suggested by Lupas et al, that the basic unit is actually smaller than a domain (35). Our tools offer a way to further investigate this idea and demonstrate the abundance of mix-and-join events.…”

Section: The Motif Network Reveals the Ubiquitous Reuse Of Motifs In mentioning

confidence: 99%

“…Two alternative explanations for these properties of the alpha/ beta domains and motifs are (i) they existed in ancient evolutionary history, and were mixed from these entities (35,37), or (ii) their biophysical properties give them a selection advantage. Our observations do not help in determining which of the two explanations is more likely, and this remains a significant challenge.…”

Section: The Motif Network Reveals the Ubiquitous Reuse Of Motifs In mentioning

confidence: 99%

Global view of the protein universe

Nepomnyachiy

Ben‐Tal

Kolodny

2014

Proc. Natl. Acad. Sci. U.S.A.

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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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Structure Comparison and Alignment

Bourne

Shindyalov

2003

Structural Bioinformatics

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Since the 1970s, after the seminal work of Rossmann and Argos (1978) comparing binding sites of known enzyme structures, the comparison and alignment of protein structures has come to be a fundamental and widely used task in computational structure biology. Three main steps are needed for comparing two protein structures: first, the detection of their common similarities; second, the alignment of the structures based on such similarities; and third, a statistical measure of the similarity. Considering the first two steps, structure comparison refers to the analysis of the similarities and differences between two or more structures, and structure alignment refers to establishing which amino acid residues are equivalent between them. The majority of commonly used methods do a reasonably good job in recognizing obvious similarities between protein structures. However, the alignment of two or more structures is a more difficult task, and its accuracy may depend on the method or program used as well as what the user is trying to accomplish, which will be discussed subsequently. All programs that are briefly described in this chapter perform both steps and are commonly known as protein structure alignment methods.It is also important to immediately clear up any confusion between structure alignment and structure superposition since such terms are often interchanged in the literature. As mentioned above, structure alignment tries to identify the equivalences between pairs of amino acid residues from the structures to superpose, while structure superposition requires the previous knowledge of such equivalences. Thus, structure superposition tries to solve the simpler geometrical task of minimizing the distance between already known equivalent residues of the superimposed structures by finding a transformation that produces either the lowest root-mean-square deviation (RMSD) or the maximal equivalences within an

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On the Evolution of Protein Folds: Are Similar Motifs in Different Protein Folds the Result of Convergence, Insertion, or Relics of an Ancient Peptide World?

Cited by 268 publications

References 60 publications

A galaxy of folds

A galaxy of folds

Global view of the protein universe

Structure Comparison and Alignment

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