Journal article
Cofactory: Sequence-based prediction of cofactor specificity of Rossmann folds : Cofactor Specificity Prediction
Department of Systems Biology, Technical University of Denmark1
Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark2
Metagenomics, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark3
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark4
Novozymes A/S5
iLoop, Translational Management, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark6
Network Reconstruction in Silico Biology, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark7
Functional Human Variation, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark8
Integrative Systems Biology, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark9
Obtaining optimal cofactor balance to drive production is a challenge metabolically engineered microbial strains. To facilitate identification of heterologous enzymes with desirable altered cofactor requirements from native content, we have developed Cofactory, a method for prediction of enzyme cofactor specificity using only primary amino acid sequence information.
The algorithm identifies potential cofactor binding Rossinann folds and predicts the specificity for the cofactors FAD(H2), NAD(H), and NADP(H) The Rossmann fold sequence search is carried out using hidden Markov models whereas artificial neural networks are used for specificity prediction. Training was carried out using experimental data from protein cofactor structure complexes.
The overall performance was benchmarked against an independent evaluation set obtaining Matthews correlation coefficients of 0.94, 0.79, and 0.65 for FAD(112), NAD(H), and NADP(H), respectively. The Cofactory method is made publicly available at http://www.cbs.dtu.dldservices/Cofactory.
Language: | English |
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Year: | 2014 |
Pages: | 1819-1828 |
ISSN: | 08873585 and 10970134 |
Types: | Journal article |
DOI: | 10.1002/prot.24536 |
ORCIDs: | 0000-0003-0316-5866 , Blom, Nikolaj , Feist, Adam and Petersen, Thomas Nordahl |