Complex evolutionary footprints revealed in an analysis of reused protein segments of diverse lengths

Abstract

Proteins share similar segments with one another. Such "reused parts"-which have been successfully incorporated into other proteins-are likely to offer an evolutionary advantage over de novo evolved segments, as most of the latter will not even have the capacity to fold. To systematically explore the evolutionary traces of segment "reuse" across proteins, we developed an automated methodology that identifies reused segments from protein alignments. We search for "themes"-segments of at least 35 residues of similar sequence and structure-reused within representative sets of 15,016 domains [Evolutionary Classification of Protein Domains (ECOD) database] or 20,398 chains [Protein Data Bank (PDB)]. We observe that theme reuse is highly prevalent and that reuse is more extensive when the length threshold for identifying a theme is lower. Structural domains, the best characterized form of reuse in proteins, are just one of many complex and intertwined evolutionary traces. Others include long themes shared among a few proteins, which encompass and overlap with shorter themes that recur in numerous proteins. The observed complexity is consistent with evolution by duplication and divergence, and some of the themes might include descendants of ancestral segments. The observed recursive footprints, where the same amino acid can simultaneously participate in several intertwined themes, could be a useful concept for protein design. Data are available at http://trachel-srv.cs.haifa.ac.il/rachel/ppi/themes/.

Keywords: ancestral segments; protein evolutionary patterns; protein function annotation; protein space.

Fig. 1.

(A) The most reused themes in a protein P are derived from the set of meaningful alignments of P and other proteins: in this example, proteins 1–4. For any possible theme (for example, theme T that spans residues s-e), we can consider the parts in the alignments that are restricted to these residues, which are marked here by black rectangles. (B) We assign a score for every theme within the protein P based on the scores of these restricted parts, which is the sum over the BLOSUM-62 scores for the aligned parts. (C) Our goal is to identify the largest set of nonoverlapping themes (for example, theme_A and theme_B), such that the sum of these scores is optimal. Rather than exhaustively scoring all possible theme end points to find the optimal one, we find it more efficiently using dynamic programming (SI Appendix, Methods has details).

Fig. 2.

Usage of the protein themes. Log–log plot of the number of themes vs. theme size [i.e., number of variations per theme for the PDB datasets (for ECOD dataset see SI Appendix, Fig. S1A)]. Results for themes of different minimal lengths are presented using different colors. In all cases, we see that there are many themes with a small size and few large-sized themes; we also see that reuse increases as the minimal theme length decreases.

Fig. 3.

Recursive reuse of parts of e2xyiA1 in the ECOD dataset. Reuse manifests a Russian nested dolls effect (in sequence; not to be confused with the structural one described in refs. and 9). The themes are marked on the e2xyiA1 domain. The shortest theme, shown in purple, appears in the largest set of domains (listed within the purple box). A longer (encompassing) theme, shown in blue, appears in fewer domains. Similarly, increasingly longer themes of e2xyiA1, shown in light blue, green, yellow, orange, and red, are found in increasingly smaller sets of domains. This example manifests the complexity of the reuse pattern in evolution, where the same amino acid can appear in more than one theme, and shows that, to accurately describe reuse of a domain, we must consider a per residue resolution.

Fig. 4.

Reuse in protein space is greater when considering sets of themes of increasingly shorter minimal lengths. Reuse in the ECOD (A and B) and PDB (C and D) datasets. (A and C) The number of recurring residues (i.e., amino acids that appear in any theme) (Eq. 1) using different sets of themes. (B and D) The number of unique residues (Eq. 2) obtained using sets of themes with different minimal lengths.