Kiel Christina, Foglierini Mathilde, Kuemmerer Nico, Beltrao Pedro, Serrano Luis
Structural and computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.
J Mol Biol. 2007 Jul 27;370(5):1020-32. doi: 10.1016/j.jmb.2007.05.015. Epub 2007 May 22.
Here using structural information and protein design tools we have drawn the network of interactions between 20 Ras subfamily proteins with 50 putative Ras binding domains. To validate this network we have cloned six poorly characterized Ras binding domains (RBD) and two Ras proteins (RERG, DiRas1). These, together with previously described RBD domains, Ras and Rap proteins have been analyzed in 70 pull-down experiments. Comparing our interaction network with these and previous pull-down experiments (total of 150 cases) shows a very high accuracy for distinguishing between binders and non-binders ( approximately 0.80). Bioinformatics information was integrated to distinguish those in vitro interactions that are more likely to be relevant in vivo. We proposed several new interactions between Ras family members and effector domains that are of relevance in understanding the physiological role of these proteins. More broadly our results demonstrate that (domain-domain) interaction specificities between members of protein families can be accurately predicted using structural information.
在此，我们利用结构信息和蛋白质设计工具绘制了20种Ras亚家族蛋白与50个假定的Ras结合结构域之间的相互作用网络。为了验证这个网络，我们克隆了6个特征描述较少的Ras结合结构域（RBD）和2个Ras蛋白（RERG、DiRas1）。这些蛋白与先前描述的RBD结构域、Ras和Rap蛋白一起，在70次下拉实验中进行了分析。将我们的相互作用网络与这些以及先前的下拉实验（总共150个案例）进行比较，结果显示在区分结合蛋白和非结合蛋白方面具有非常高的准确性（约为0.80）。整合生物信息学信息以区分那些在体内更可能相关的体外相互作用。我们提出了Ras家族成员与效应结构域之间的几种新相互作用，这对于理解这些蛋白质的生理作用具有重要意义。更广泛地说，我们的结果表明，利用结构信息可以准确预测蛋白质家族成员之间的（结构域-结构域）相互作用特异性。
