Information theory provides a comprehensive framework for the evaluation of protein structure predictions.
Information theory provides a comprehensive framework for the evaluation of protein structure predictions.
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DOI：
10.1002/prot.22186
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发表时间：
2009-02-15
影响因子：
2.9
通讯作者：
Tsai, Jerry W.
中科院分区：
文献类型：
--
作者：
Swanson, Rosemarie;Vannucci, Marina;Tsai, Jerry W.
关键词：
蛋白质结构预测有许多重要的特设相似性措施，用于评估预测，但将受益于一个措施，能够提供一个共同的框架，广泛的比较。在这里，我们表明，一个互信息的措施，可以提供一个全面的框架，评估所有类型的蛋白质结构预测。我们讨论了信息的概念，它在二级结构中的应用，以及将其应用于三维结构的障碍。基于从二级结构的情况下的见解，我们提出了一种方法来解决3D的困难，并开发了一种方法来测量由3D结构预测提供的互信息。我们将所有类型的蛋白质结构预测的评估整合到一个单一的框架中，并比较各种预测方法提供的信息量，包括二级结构预测。在这个扩大的框架内，结构比序列在进化过程中更好地保存的想法是定量评估珠蛋白家族。珠蛋白家族中几乎完美的序列匹配对应于大约300比特的信息，而相同的两种蛋白质的几乎完美的结构匹配对应于大约2500比特的信息，其中比特的信息描述了偶然获得相似接近度的匹配的概率。互信息为评价结构相似性提供了理论基础，也为现有的相似性度量提供了一个解释性的环境。
Protein structure prediction has a number of important ad hoc similarity measures for evaluating predictions, but would benefit from a measure that is able to provide a common framework for a broad range of comparisons. Here we show that a mutual information-like measure can provide a comprehensive framework for evaluating protein structure prediction of all types. We discuss the concept of information, its application to secondary structure, and the obstacle to applying it to 3D structure. Based on insights from the secondary structure case, we present an approach to work around the 3D difficulties, and develop a method to measure the mutual information provided by a 3D structure prediction. We integrate the evaluation of all types of protein structure prediction into a single frame work, and compare the amount of information provided by various prediction methods, including secondary structure prediction. Within this broadened framework, the idea that structure is better preserved than sequence during evolution is evaluated quantitatively for the globin family. A nearly perfect sequence match in the globin family corresponds to about 300 bits of information, whereas a nearly perfect structural match for the same two proteins corresponds to about 2500 bits of information, where bits of information describes the probability of obtaining a match of similar closeness by chance. Mutual information provides both a theoretical basis for evaluating structure similarity and an explanatory surround for existing similarity measures.
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