Dror Oranit, Lasker Keren, Nussinov Ruth, Wolfson Haim
School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel.
Acta Crystallogr D Biol Crystallogr. 2007 Jan;63(Pt 1):42-9. doi: 10.1107/S0907444906041059. Epub 2006 Dec 13.
Structural analysis of biological machines is essential for inferring their function and mechanism. Nevertheless, owing to their large size and instability, deciphering the atomic structure of macromolecular assemblies is still considered as a challenging task that cannot keep up with the rapid advances in the protein-identification process. In contrast, structural data at lower resolution is becoming more and more available owing to recent advances in cryo-electron microscopy (cryo-EM) techniques. Once a cryo-EM map is acquired, one of the basic questions asked is what are the folds of the components in the assembly and what is their configuration. Here, a novel knowledge-based computational method, named EMatch, towards tackling this task for cryo-EM maps at 6-10 A resolution is presented. The method recognizes and locates possible atomic resolution structural homologues of protein domains in the assembly. The strengths of EMatch are demonstrated on a cryo-EM map of native GroEL at 6 A resolution.
生物机器的结构分析对于推断其功能和机制至关重要。然而,由于其尺寸较大且不稳定,解析大分子组装体的原子结构仍然被认为是一项具有挑战性的任务,难以跟上蛋白质鉴定过程的快速发展。相比之下,由于低温电子显微镜(cryo-EM)技术的最新进展,低分辨率的结构数据越来越容易获得。一旦获得了cryo-EM图谱,一个基本问题就是组装体中各组分的折叠方式是什么以及它们的构型是怎样的。在此,提出了一种名为EMatch的基于知识的新型计算方法,用于处理分辨率为6-10埃的cryo-EM图谱的这一任务。该方法识别并定位组装体中蛋白质结构域可能的原子分辨率结构同源物。EMatch的优势在分辨率为6埃的天然GroEL的cryo-EM图谱上得到了证明。