Nemoto Wataru, Saito Akira, Oikawa Hayato
Division of Life Science and Engineering, School of Science and Engineering, Tokyo Denki University (TDU), Ishizaka, Hatoyama-cho, Hiki-gun, Saitama, 350-0394, Japan.
Comput Struct Biotechnol J. 2013 Dec 5;8:e201308007. doi: 10.5936/csbj.201308007. eCollection 2013.
Structural genomics projects have solved many new structures with unknown functions. One strategy to investigate the function of a structure is to computationally find the functionally important residues or regions on it. Therefore, the development of functional region prediction methods has become an important research subject. An effective approach is to use a method employing structural and evolutionary information, such as the evolutionary trace (ET) method. ET ranks the residues of a protein structure by calculating the scores for relative evolutionary importance, and locates functionally important sites by identifying spatial clusters of highly ranked residues. After ET was developed, numerous ET-like methods were subsequently reported, and many of them are in practical use, although they require certain conditions. In this mini review, we first introduce the remaining problems and the recent improvements in the methods using structural and evolutionary information. We then summarize the recent developments of the methods. Finally, we conclude by describing possible extensions of the evolution- and structure-based methods.
结构基因组学项目已经解析出了许多功能未知的新结构。研究结构功能的一种策略是通过计算找到其上功能重要的残基或区域。因此，功能区域预测方法的开发已成为一个重要的研究课题。一种有效的方法是使用一种结合结构和进化信息的方法，比如进化踪迹（ET）方法。ET通过计算相对进化重要性得分对蛋白质结构的残基进行排序，并通过识别高排名残基的空间簇来定位功能重要位点。ET方法提出后，随后报道了许多类似ET的方法，其中许多方法都在实际应用中，尽管它们需要一定条件。在本综述中，我们首先介绍使用结构和进化信息的方法中存在的遗留问题和近期改进。然后我们总结这些方法的最新进展。最后，我们通过描述基于进化和结构的方法可能的扩展来得出结论。
