Barker Jonathan A, Thornton Janet M
European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
Bioinformatics. 2003 Sep 1;19(13):1644-9. doi: 10.1093/bioinformatics/btg226.
Structural templates consisting of a few atoms in a specific geometric conformation provide a powerful tool for studying the relationship between protein structure and function. Current methods for template searching constrain template syntax and semantics by their design. Hence there is a need for a more flexible core algorithm upon which to build more sophisticated tools. Statistical analysis of structural similarity is still in its infancy when compared with its analogue in sequence alignment. In the context of template matching, there is an urgent need for normalization of scores so that results from templates with differing sensitivity may be compared directly.
We introduce Jess, a fast and flexible algorithm for searching protein structures for small groups of atoms under arbitrary constraints on geometry and chemistry. We apply the algorithm to a set of manually derived enzyme active site templates, and derive an empirical measure for estimating the relative significance of hits encountered using differing templates.
由处于特定几何构象的少数原子组成的结构模板为研究蛋白质结构与功能之间的关系提供了一个强大的工具。当前的模板搜索方法在设计上限制了模板的语法和语义。因此，需要一种更灵活的核心算法，以便构建更复杂的工具。与序列比对中的类似方法相比，结构相似性的统计分析仍处于起步阶段。在模板匹配的背景下，迫切需要对得分进行归一化处理，以便能够直接比较具有不同灵敏度的模板的结果。
我们引入了Jess，这是一种快速且灵活的算法，用于在几何和化学的任意约束下搜索蛋白质结构中的小原子组。我们将该算法应用于一组手动推导的酶活性位点模板，并得出一种经验度量，用于估计使用不同模板遇到的命中结果的相对显著性。
