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首页> 外文期刊>The FEBS journal >Prediction of coenzyme specificity in dehydrogenases/reductases - A hidden Markov model-based method and its application on complete genomes
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Prediction of coenzyme specificity in dehydrogenases/reductases - A hidden Markov model-based method and its application on complete genomes

机译：脱氢酶/还原酶中辅酶特异性的预测-基于隐马尔可夫模型的方法及其在完整基因组中的应用

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摘要

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 http://www.ifm.liu.se/bioinfo, where the preferred coenzyme and its binding region are predicted given an amino acid sequence as input.
机译：脱氢酶和还原酶是具有基本代谢重要性的酶，通常采用称为Rossmann折叠的特定结构。该折叠由被α-螺旋包围的六链β-折叠组成，负责辅酶的结合。我们已经开发出一种方法，仅使用氨基酸序列作为输入即可识别Rossmann折叠并预测其辅酶特异性（NAD，NADP或FAD）。该方法基于隐马尔可夫模型和序列模式分析。预测灵敏度为79％，选择性接近100％。该方法应用于一组68个基因组，分别代表古细菌，细菌和真核生物的三个王国。在原核生物中，发现3％的基因编码Rossmann-fold蛋白，而在真核生物中相应的比例仅为1％左右。在所有基因组中，NAD是最优选的辅因子（41-49％），其次是NADP，占30-38％，而FAD是最不优选的辅因子（21％）。但是，NAD在NADP上的优势在古细菌中最为明显，而在真核生物中则最不明显。在所有三个王国中，只有3-8％的Rossmann蛋白被预测具有一个以上的跨膜片段，该片段比一般的膜蛋白的频率低得多。对真核生物中主要蛋白质类型的分析表明，罗斯曼蛋白质中最常见的类型（26％）是短链脱氢酶/还原酶。此外，还对鉴定出的罗斯曼蛋白进行了进一步的蛋白类型，酶类别和冗余分析。所述方法可在http://www.ifm.liu.se/bioinfo获得，其中在给定氨基酸序列作为输入的情况下预测了优选的辅酶及其结合区。

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