1. CorNet: Assigning function to networks of co-evolving residues by automated literature mining
- Author
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Bergh, T. van den, Tamo, G., Nobili, A., Tao, Y., Tan, T., Bornscheuer, U.T., Kuipers, R.K.P., Vroling, B., Jong, R.M. de, Subramanian, K., Schaap, P.J., Desmet, T., Nidetzky, B., Vriend, G., Joosten, H.J., Bergh, T. van den, Tamo, G., Nobili, A., Tao, Y., Tan, T., Bornscheuer, U.T., Kuipers, R.K.P., Vroling, B., Jong, R.M. de, Subramanian, K., Schaap, P.J., Desmet, T., Nidetzky, B., Vriend, G., and Joosten, H.J.
- Abstract
Contains fulltext : 174131.pdf (publisher's version ) (Open Access), 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.
- Published
- 2017