Song Guang, Jernigan Robert L
L.H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, Iowa 50011-3020, USA.
Proteins. 2006 Apr 1;63(1):197-209. doi: 10.1002/prot.20836.
Domain swapping is a process where two (or more) protein molecules form a dimer (or higher oligomer) by exchanging an identical domain. In this article, based on the observation that domains are rigid and hinge loops are highly flexible, we propose a new Elastic Network Model, domain-ENM, for domain-swapped proteins. In this model, the rigidity of domains is taken into account by using a larger spring constant for intradomain contacts. The large-scale transition of domain swapping is then novelly decomposed into the relative motion between the rigid domains (only 6 degrees of freedom) plus the internal fluctuations of each domain. Consequently, this approach has the potential to produce much more meaningful transition pathways than other simulation approaches that try to find pathways in a search space of large numbers of dimensions. In this article, we also propose a new way to define the overlap measure. Past approaches used an inappropriate comparison of the large-scale conformation displacement against the computed infinitesimal motions of modes. Here, we propose an infinitesimal version of the large-scale conformation change and then compare it with the modes of motions. As a result, we obtain much better overlap values. Using this new overlap definition, we are also able for the first time to give a clear, intuitive explanation why "open" forms tend to produce better overlap values than "closed" forms with traditional ENMs. Finally, as an application, we present a simple approach to show how domain-ENM can be used to generated transition pathways for domain-swapped proteins.
结构域交换是指两个(或更多)蛋白质分子通过交换相同的结构域形成二聚体(或更高阶寡聚体)的过程。在本文中,基于结构域是刚性的而铰链环具有高度灵活性这一观察结果,我们提出了一种用于结构域交换蛋白的新弹性网络模型——结构域弹性网络模型(domain-ENM)。在该模型中,通过对结构域内接触使用更大的弹簧常数来考虑结构域的刚性。然后,结构域交换的大规模转变被新颖地分解为刚性结构域之间的相对运动(仅6个自由度)加上每个结构域的内部波动。因此,与其他试图在大量维度的搜索空间中寻找路径的模拟方法相比,这种方法有可能产生更有意义的转变路径。在本文中,我们还提出了一种定义重叠度量的新方法。过去的方法对大规模构象位移与计算出的模式微小运动进行了不恰当的比较。在这里,我们提出了大规模构象变化的微小版本,然后将其与运动模式进行比较。结果,我们获得了更好的重叠值。使用这个新的重叠定义,我们还首次能够清晰、直观地解释为什么在传统弹性网络模型中,“开放”形式往往比“封闭”形式产生更好的重叠值。最后,作为一个应用,我们提出了一种简单的方法来展示如何使用结构域弹性网络模型为结构域交换蛋白生成转变路径。