Mas J M, Aloy P, Martí-Renom M A, Oliva B, de Llorens R, Avilés F X, Querol E
Institut de Biologia Fonamental i Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Spain.
J Comput Aided Mol Des. 2001 May;15(5):477-87. doi: 10.1023/a:1011164224144.
The preferential occurrence of certain disulphide-bridge topologies in proteins has prompted us to design a method and a program, KNOT-MATCH, for their classification. The program has been applied to a database of proteins with less than 65% homology and more than two disulphide bridges. We have investigated whether there are topological preferences that can be used to group proteins and if these can be applied to gain insight into the structural or functional relationships among them. The classification has been performed by Density Search and Hierarchical Clustering Techniques, yielding thirteen main protein classes from the superimposition and clustering process. It is noteworthy that besides the disulphide bridges, regular secondary structures and loops frequently become correctly aligned. Although the lack of significant sequence similarity among some clustered proteins precludes the easy establishment of evolutionary relationships, the program permits us to find out important structural or functional residues upon the superimposition of two protein structures apparently unrelated. The derived classification can be very useful for finding relationships among proteins which would escape detection by current sequence or topology-based analytical algorithms.
蛋白质中某些二硫键拓扑结构的优先出现促使我们设计了一种方法和一个程序KNOT - MATCH,用于对它们进行分类。该程序已应用于同源性低于65%且含有两个以上二硫键的蛋白质数据库。我们研究了是否存在可用于对蛋白质进行分组的拓扑偏好,以及这些偏好是否可用于深入了解它们之间的结构或功能关系。分类是通过密度搜索和层次聚类技术进行的,在叠加和聚类过程中产生了13个主要的蛋白质类别。值得注意的是,除了二硫键外,规则的二级结构和环常常也能正确对齐。尽管一些聚类蛋白质之间缺乏显著的序列相似性,难以轻易建立进化关系,但该程序使我们能够在两个明显不相关的蛋白质结构叠加时找出重要的结构或功能残基。所得分类对于发现蛋白质之间的关系非常有用,而这些关系可能会逃过当前基于序列或拓扑的分析算法的检测。