Pellegrini-Calace Marialuisa, Thornton Janet M
European Bioinformatics Institute, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD, UK.
Nucleic Acids Res. 2005 Apr 14;33(7):2129-40. doi: 10.1093/nar/gki349. Print 2005.
In this work, we analyse the potential for using structural knowledge to improve the detection of the DNA-binding helix-turn-helix (HTH) motif from sequence. Starting from a set of DNA-binding protein structures that include a functional HTH motif and have no apparent sequence similarity to each other, two different libraries of hidden Markov models (HMMs) were built. One library included sequence models of whole DNA-binding domains, which incorporate the HTH motif, the second library included shorter models of 'partial' domains, representing only the fraction of the domain that corresponds to the functionally relevant HTH motif itself. The libraries were scanned against a dataset of protein sequences, some containing the HTH motifs, others not. HMM predictions were compared with the results obtained from a previously published structure-based method and subsequently combined with it. The combined method proved more effective than either of the single-featured approaches, showing that information carried by motif sequences and motif structures are to some extent complementary and can successfully be used together for the detection of DNA-binding HTHs in proteins of unknown function.
在这项工作中，我们分析了利用结构知识来改进从序列中检测DNA结合螺旋-转角-螺旋（HTH）基序的潜力。从一组包含功能性HTH基序且彼此无明显序列相似性的DNA结合蛋白结构出发，构建了两个不同的隐马尔可夫模型（HMM）库。一个库包含整个DNA结合结构域的序列模型，其中包含HTH基序，第二个库包含“部分”结构域的较短模型，仅代表与功能相关的HTH基序本身对应的结构域部分。将这些库与蛋白质序列数据集进行比对，其中一些序列含有HTH基序，另一些则没有。将HMM预测结果与先前发表的基于结构的方法所获得的结果进行比较，随后将二者结合。结果表明，这种组合方法比任何一种单一特征方法都更有效，这表明基序序列和基序结构所携带的信息在一定程度上是互补的，并且可以成功地一起用于检测未知功能蛋白质中的DNA结合HTH基序。
