Exploring the sequence, function, and evolutionary space of protein superfamilies using sequence similarity networks and phylogenetic reconstructions

Methods Enzymol. 2019:620:315-347. doi: 10.1016/bs.mie.2019.03.015. Epub 2019 Apr 17.

Abstract

Integrative computational methods can facilitate the discovery of new protein functions and enzymatic reactions by enabling the observation and investigation of complex sequence-structure-function and evolutionary relationships within protein superfamilies. Here, we highlight the use of sequence similarity networks (SSNs) and phylogenetic reconstructions to map the functional divergence and evolutionary history of protein superfamilies. We exemplify this approach using the nitroreductase (NTR) flavoenzyme superfamily, demonstrating that SSN investigations can provide a rapid and effective means to classify groups of proteins, expose sequence similarity relationships across the global scale of a protein superfamily, and efficiently support detailed phylogenetic analyses. Integration of such approaches with systematic experimental characterization will expand our understanding of the functional diversity of enzymes, their evolution, and their associated physiological roles.

Keywords: Divergence; Evolution; Functional diversity; Nitroreductase; Sequence similarity networks; Sequence-structure-function relationship.

MeSH terms

  • Computational Biology / methods*
  • Databases, Protein
  • Evolution, Molecular
  • Models, Molecular
  • Nitroreductases / chemistry*
  • Nitroreductases / genetics
  • Nitroreductases / metabolism
  • Phylogeny
  • Sequence Analysis, Protein

Substances

  • Nitroreductases