Potential for assessing quality of protein structure based on contact number prediction
Potential for assessing quality of protein structure based on contact number prediction
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DOI：
10.1002/prot.21047
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发表时间：
2006-09-01
影响因子：
2.9
通讯作者：
Shimizu, Kentaro
中科院分区：
文献类型：
--
作者：
Ishida, Takashi;Nakamura, Shugo;Shimizu, Kentaro
我们开发了一种新的基于知识的残基环境潜力，用于在蛋白质结构预测中评估蛋白质结构的质量。该势使用蛋白质结构中残基的接触数和根据其氨基酸序列使用基于支持向量回归(SVR)的新预测方法预测的残基的绝对接触数。蛋白质结构中氨基酸残基的接触数由给定残基周围的残基数量定义。首先，使用支持向量机从目标蛋白质的氨基酸序列中预测每个残基的接触数。然后，根据预测的天然接触数的概率分布来计算蛋白质结构的势。将该势的性能与使用诱饵结构的其他得分函数进行了比较，以区分本地结构与其他结构以及近本地结构与非本地结构。这种潜力不仅提高了区分天然结构和其他结构的能力，而且提高了区分近天然结构和非天然结构的能力。
We developed a novel knowledge-based residue environment potential for assessing the quality of protein structures in protein structure prediction. The potential uses the contact number of residues in a protein structure and the absolute contact number of residues predicted from its amino acid sequence using a new prediction method based on a support vector regression (SVR). The contact number of an amino acid residue in a protein structure is defined by the number of residues around a given residue. First, the contact number of each residue is predicted using SVR from an amino acid sequence of a target protein. Then, the potential of the protein structure is calculated from the probability distribution of the native contact numbers corresponding to the predicted ones. The performance of this potential is compared with other score functions using decoy structures to identify both native structure from other structures and near-native structures from nonnative structures. This potential improves not only the ability to identify native structures from other structures but also the ability to discriminate near-native structures from nonnative structures.