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Fine tuned exploration of evolutionary relationships within the protein universe

Gullotto Danilo ()
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Gullotto Danilo: Advanced Computational Biostructural Research Collaboratory, I-95019, Zafferana Etnea, Italy

Statistical Applications in Genetics and Molecular Biology, 2021, vol. 20, issue 1, 17-36

Abstract: In the regime of domain classifications, the protein universe unveils a discrete set of folds connected by hierarchical relationships. Instead, at sub-domain-size resolution and because of physical constraints not necessarily requiring evolution to shape polypeptide chains, networks of protein motifs depict a continuous view that lies beyond the extent of hierarchical classification schemes. A number of studies, however, suggest that universal sub-sequences could be the descendants of peptides emerged in an ancient pre-biotic world. Should this be the case, evolutionary signals retained by structurally conserved motifs, along with hierarchical features of ancient domains, could sew relationships among folds that diverged beyond the point where homology is discernable. In view of the aforementioned, this paper provides a rationale where a network with hierarchical and continuous levels of the protein space, together with sequence profiles that probe the extent of sequence similarity and contacting residues that capture the transition from pre-biotic to domain world, has been used to explore relationships between ancient folds. Statistics of detected signals have been reported. As a result, an example of an emergent sub-network that makes sense from an evolutionary perspective, where conserved signals retrieved from the assessed protein space have been co-opted, has been discussed.

Keywords: closed loop; co-independent evolutionary sites; intra-domain interactions; LUCA; protein network; sequence profile (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1515/sagmb-2019-0039

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