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FEBS J. 2006 Mar;273(6):1177-84.

Prediction of coenzyme specificity in dehydrogenases/reductases. A hidden Markov model-based method and its application on complete genomes.

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IFM Bioinformatics, Linköping University, Sweden.


Dehydrogenases and reductases are enzymes of fundamental metabolic importance that often adopt a specific structure known as the Rossmann fold. This fold, consisting of a six-stranded beta-sheet surrounded by alpha-helices, is responsible for coenzyme binding. We have developed a method to identify Rossmann folds and predict their coenzyme specificity (NAD, NADP or FAD) using only the amino acid sequence as input. The method is based upon hidden Markov models and sequence pattern analysis. The prediction sensitivity is 79% and the selectivity close to 100%. The method was applied on a set of 68 genomes, representing the three kingdoms archaea, bacteria and eukaryota. In prokaryotes, 3% of the genes were found to code for Rossmann-fold proteins, while the corresponding ratio in eukaryotes is only around 1%. In all genomes, NAD is the most preferred cofactor (41-49%), followed by NADP with 30-38%, while FAD is the least preferred cofactor (21%). However, the NAD preponderance over NADP is most pronounced in archaea, and least in eukaryotes. In all three kingdoms, only 3-8% of the Rossmann proteins are predicted to have more than one membrane-spanning segment, which is much lower than the frequency of membrane proteins in general. Analysis of the major protein types in eukaryotes reveals that the most common type (26%) of the Rossmann proteins are short-chain dehydrogenases/reductases. In addition, the identified Rossmann proteins were analyzed with respect to further protein types, enzyme classes and redundancy. The described method is available at, where the preferred coenzyme and its binding region are predicted given an amino acid sequence as input.

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