PLoS ONE (Jan 2017)

CorNet: Assigning function to networks of co-evolving residues by automated literature mining.

  • Tom van den Bergh,
  • Giorgio Tamo,
  • Alberto Nobili,
  • Yifeng Tao,
  • Tianwei Tan,
  • Uwe T Bornscheuer,
  • Remko K P Kuipers,
  • Bas Vroling,
  • René M de Jong,
  • Kalyanasundaram Subramanian,
  • Peter J Schaap,
  • Tom Desmet,
  • Bernd Nidetzky,
  • Gert Vriend,
  • Henk-Jan Joosten

DOI
https://doi.org/10.1371/journal.pone.0176427
Journal volume & issue
Vol. 12, no. 5
p. e0176427

Abstract

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CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the functions associated with these groups and the residues in them. We used CorNet to analyse six enzyme super-families and found that groups of strongly co-evolving residues tend to consist of residues involved in a same function such as activity, specificity, co-factor binding, or enantioselectivity. This finding allows to assign a function to residues for which no data is available yet in the literature. A mutant library was designed to mutate residues observed in a group of co-evolving residues predicted to be involved in enantioselectivity, but for which no literature data is available yet. The resulting set of mutations indeed showed many instances of increased enantioselectivity.