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Evolution of networks of protein domain organization.
Aziz, M Fayez; Caetano-Anollés, Gustavo.
Afiliación
  • Aziz MF; Evolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, IL, 61801, USA.
  • Caetano-Anollés G; Evolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, IL, 61801, USA. gca@illinois.edu.
Sci Rep ; 11(1): 12075, 2021 06 08.
Article en En | MEDLINE | ID: mdl-34103558
Domains are the structural, functional and evolutionary units of proteins. They combine to form multidomain proteins. The evolutionary history of this molecular combinatorics has been studied with phylogenomic methods. Here, we construct networks of domain organization and explore their evolution. A time series of networks revealed two ancient waves of structural novelty arising from ancient 'p-loop' and 'winged helix' domains and a massive 'big bang' of domain organization. The evolutionary recruitment of domains was highly modular, hierarchical and ongoing. Domain rearrangements elicited non-random and scale-free network structure. Comparative analyses of preferential attachment, randomness and modularity showed yin-and-yang complementary transition and biphasic patterns along the structural chronology. Remarkably, the evolving networks highlighted a central evolutionary role of cofactor-supporting structures of non-ribosomal peptide synthesis pathways, likely crucial to the early development of the genetic code. Some highly modular domains featured dual response regulation in two-component signal transduction systems with DNA-binding activity linked to transcriptional regulation of responses to environmental change. Interestingly, hub domains across the evolving networks shared the historical role of DNA binding and editing, an ancient protein function in molecular evolution. Our investigation unfolds historical source-sink patterns of evolutionary recruitment that further our understanding of protein architectures and functions.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Evolución Molecular / Biología Computacional / Dominios Proteicos Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sci Rep Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Evolución Molecular / Biología Computacional / Dominios Proteicos Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sci Rep Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido