Chou Kuo-Chen
Gordon Life Science Institute, San Diego, California 92130, USA.
Curr Protein Pept Sci. 2005 Oct;6(5):423-36. doi: 10.2174/138920305774329368.
The structural class is an important attribute used to characterize the overall folding type of a protein or its domain. Since the concept of protein structural class was developed about 3 decades ago based on a visual inspection of polypeptide chain topologies in a dataset of only 31 gloular proteins, the number of structure-known proteins has been increased rapidly. For example, as of 12-July-2005, the entries deposited into RCSB PDB Protein Data Bank for proteins, peptides, and viruses whose 3-dimensional structures were determined by X-ray and NMR techniques have been increased to 28,920. To properly cover more and more structure-known proteins, some modification and expansion from the original structural classification scheme have been developed. Meanwhile, many different approaches have been proposed for predicting the structural class of proteins. In this review, the new classification schemes are briefly introduced. The attention is focused on the progress in structural class prediction and its impact in stimulating the development of identifying the other attributes of proteins. It is interesting to point out that the development of the latter has actually in turn greatly enriched the power of the former. Also, some promising approaches for the further development of protein structural class prediction are also addressed.
结构类别是用于表征蛋白质或其结构域整体折叠类型的一个重要属性。自从大约30年前基于对仅31种球状蛋白质数据集的多肽链拓扑结构进行目视检查而提出蛋白质结构类别的概念以来，已知结构的蛋白质数量迅速增加。例如，截至2005年7月12日，通过X射线和核磁共振技术确定了三维结构的蛋白质、肽和病毒存入RCSB蛋白质数据银行（PDB）的条目已增加到28920个。为了恰当地涵盖越来越多已知结构的蛋白质，人们对原始结构分类方案进行了一些修改和扩展。同时，已经提出了许多不同的方法来预测蛋白质的结构类别。在这篇综述中，简要介绍了新的分类方案。重点关注结构类别预测的进展及其在推动识别蛋白质其他属性发展方面的影响。有趣的是，指出后者的发展实际上反过来极大地丰富了前者的能力。此外，还讨论了蛋白质结构类别预测进一步发展的一些有前景的方法。
