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Classification and recognition of Rossmann-fold protein

机译:Rossmann-Fold蛋白的分类和识别

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Fold recognition is an important issue in protein structure research. The Rossmann-fold protein that has typical structure is a common kind of α/β protein. The training set, selected from 22 families, is constituted of 79 Rossmann-fold proteins which have less than 25% sequence identity with each other. The hierarchical clustering method according to RMSD is applied and a profile-HMM based on structure alignment is built for each cluster. Testing on 9505 proteins with less than 95% sequence identity from Astrall.65, the sensitivity, specificity and MCC are 93.9%, 82.1% and 0.876 respectively. The result shows that building profile-HMMs after classification could reach precise fold recognition while a unified one cannot be built due to there are too many members in training set.
机译:折叠识别是蛋白质结构研究的重要问题。具有典型结构的Rossmann-Fold蛋白是一种常见的α/β蛋白。从22个家庭中选择的培训集由79个rossmann-fold蛋白组成,彼此具有小于25%的序列同一性。应用了根据RMSD的分层聚类方法,并且为每个群集构建了基于结构对齐的配置文件-HMM。从Astllall.65的序列同一性低于9505蛋白的测试,敏感性,特异性和MCC分别为93.9%,82.1%和0.876。结果表明,在分类后建立配置文件-HMM可以达到精确的折叠识别,而统一的折叠识别可能由于训练集中有太多成员而构建。

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