首页> 外文会议>International Conference on Medical Biometrics(ICMB 2008); 20080104-05; Hong Kong(CN) >Predicting Protein Quaternary Structure with Multi-scale Energy of Amino Acid Factor Solution Scores and Their Combination
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Predicting Protein Quaternary Structure with Multi-scale Energy of Amino Acid Factor Solution Scores and Their Combination

机译:利用氨基酸因子溶液分数及其组合的多尺度能量预测蛋白质四级结构

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摘要

In the protein universe, many proteins are composed of two or more polypeptide chains, generally referred to as subunits, which associate through noncovalent interactions and, occasionally, disulfide bonds to form protein quaternary structures. It has been known for long that the functions of proteins are closely related to their quaternary structure. With the number of protein sequences entering into data banks rapidly increasing, it is highly desirable to predict protein quaternary structures automatically from their primary sequences. Here, multi-scale energy of factor solution scores and feature combination were employed to form various input feature vectors, and the multi-class support vector machine (SVM) classifier modules were adopted for predicting protein quaternary structures. The rates of correct identification suggest that the individual primary sequence of an oligomeric protein do contain the information of its quaternary structure. The results of multi-scale energy of Factor 1 solution scores indirectly prove that biologically relevant complex formation is driven predominantly by the hydrophobic effect. The current approach is quite promising and may at least play a complimentary role to the existing methods.
机译:在蛋白质领域,许多蛋白质由两条或更多条多肽链(通常称为亚基)组成,它们通过非共价相互作用以及偶而通过二硫键结合形成蛋白质四级结构。众所周知,蛋白质的功能与其四级结构密切相关。随着进入数据库的蛋白质序列的数量迅速增加,非常需要根据其一级序列自动预测蛋白质四级结构。在这里,因子解决方案分数和特征组合的多尺度能量被用来形成各种输入特征向量,并且采用多类支持向量机(SVM)分类器模块来预测蛋白质四级结构。正确识别的速率表明,寡聚蛋白的单个一级序列确实包含其四级结构的信息。因子1解分数的多尺度能量结果间接证明,生物学相关的复合物形成主要受疏水作用驱动。当前的方法是很有前途的,并且至少可以对现有方法起到补充作用。

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