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:10.1371/journal.pone.0176427

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

PLoS One. 2017 May 18;12(5):e0176427. doi: 10.1371/journal.pone.0176427. eCollection 2017.

Authors

Tom van den Bergh^{1

2}, Giorgio Tamo¹, Alberto Nobili³, Yifeng Tao^{3

4}, Tianwei Tan⁴, Uwe T Bornscheuer³, Remko K P Kuipers¹, Bas Vroling¹, René M de Jong⁵, Kalyanasundaram Subramanian², Peter J Schaap², Tom Desmet⁶, Bernd Nidetzky⁷, Gert Vriend⁸, Henk-Jan Joosten^{1

8}

Affiliations

¹ Bio-Prodict, Nijmegen, The Netherlands.
² Laboratory of Systems and Synthetic Biology, Wageningen University, Wageningen, The Netherlands.
³ Institute of Biochemistry, Department of Biotechnology & Enzyme Catalysis, Greifswald University, Greifswald, Germany.
⁴ Beijing Key Lab of Bioprocess, Beijing University of Chemical Technology, Chaoyang, Beijing, China.
⁵ DSM Biotechnology Center, Delft, The Netherlands.
⁶ Centre for Industrial Biotechnology and Biocatalysis, Ghent University, Ghent, Belgium.
⁷ Institute of Biotechnology and Biochemical Engineering, Graz University of Technology, Graz, Austria.
⁸ CMBI, Radboudumc, Nijmegen, The Netherlands.

Abstract

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.

MeSH terms

Automation
Computational Biology / methods*
Data Mining*
Evolution, Molecular*
Internet*
Models, Molecular
Mutation
Protein Conformation
Proteins / chemistry*
Proteins / genetics
Proteins / metabolism*
Sequence Alignment / methods*

Substances

Proteins

Grants and funding

This research was supported and funded in part by the Technology Foundation, the Applied Science Division (STW) of the Netherlands Organization for Scientific Research (NWO), project number 11319 (www.stw.nl) of which K.S. is the principal receiver. This research was co-funded by the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no: 289646 (KYROBIO). This research was co-funded by the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no: 289350 (NewProt). This research was co-funded by the European Union's Seventh Framework Programme (FP7/2013-2017) under grant agreement no: 613633 (SuSy). T. Tan and Y. Tao thank the financial support from the National Basic Research Program of China (973 program: 2013CB733600), the National Nature Science Foundation of China (21106005) and China Scholarship Council. Bio-Prodict provided support in the form of salaries for authors TB, RK, BV, HJ, and was involved in the study design, data collection and analysis, decision to publish, and preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.