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Construction of a Sequence- and Backbone-Dependent Rotamer Library by Hidden-Markov Model

机译:用隐马尔可夫模型构造依赖于序列和骨干的转子库

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Sidechain prediction is an important subproblem of protein design and structure prediction. Construction of rotamer library is the basis for protein sidechain prediction because it provides the basic searching space for prediction. However, the state-of-the-art rotamer libraries focus on the statistical information of individual amino acids, ignoring the direct affection of its adjacent amino acids. This article presents a sequence- and backbone-dependent rotamer library. Both the conformation information of adjacent amino acids and torsion angle of the current residue are taken into account to construct a sequence- and backbone-dependent library by HMM. Evaluation on all 13 free modeling targets of CASP8 based on our rotamer library is conducted. Comparing with side-chain prediction based on the state-of-the-art rotamer library, our library outperforms the sidechain prediction accuracy on all the test targets to a certain extent.
机译:侧链预测是蛋白质设计和结构预测的重要子问题。旋转异构体文库的构建是蛋白质侧链预测的基础,因为它提供了预测的基本搜索空间。但是,最新的旋转异构体库专注于单个氨基酸的统计信息,而忽略了其相邻氨基酸的直接影响。本文介绍了依赖序列和骨架的旋转异构体文库。通过HMM构建相邻氨基酸的构象信息和当前残基的扭转角,以构建序列和骨架依赖性文库。根据我们的rotamer库对CASP8的所有13个免费建模目标进行了评估。与基于最新rotamer库的侧链预测相比,我们的库在所有测试目标上均优于侧链预测精度。

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