School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada.
Proteins. 2015 Mar;83(3):497-516. doi: 10.1002/prot.24752. Epub 2015 Jan 31.
Recent studies have highlighted the role of coupled side-chain fluctuations alone in the allosteric behavior of proteins. Moreover, examination of X-ray crystallography data has recently revealed new information about the prevalence of alternate side-chain conformations (conformational polymorphism), and attempts have been made to uncover the hidden alternate conformations from X-ray data. Hence, new computational approaches are required that consider the polymorphic nature of the side chains, and incorporate the effects of this phenomenon in the study of information transmission and functional interactions of residues in a molecule. These studies can provide a more accurate understanding of the allosteric behavior. In this article, we first present a novel approach to generate an ensemble of conformations and an efficient computational method to extract direct couplings of side chains in allosteric proteins, and provide sparse network representations of the couplings. We take the side-chain conformational polymorphism into account, and show that by studying the intrinsic dynamics of an inactive structure, we are able to construct a network of functionally crucial residues. Second, we show that the proposed method is capable of providing a magnified view of the coupled and conformationally polymorphic residues. This model reveals couplings between the alternate conformations of a coupled residue pair. To the best of our knowledge, this is the first computational method for extracting networks of side chains' alternate conformations. Such networks help in providing a detailed image of side-chain dynamics in functionally important and conformationally polymorphic sites, such as binding and/or allosteric sites.
最近的研究强调了单独的侧链波动在蛋白质变构行为中的作用。此外,最近对 X 射线晶体学数据的检查揭示了关于侧链构象交替(构象多态性)出现的新信息,并尝试从 X 射线数据中揭示隐藏的交替构象。因此,需要考虑侧链多态性的新计算方法,并将这种现象的影响纳入对分子中残基信息传递和功能相互作用的研究中。这些研究可以提供对变构行为更准确的理解。在本文中,我们首先提出了一种生成构象集合的新方法和一种从变构蛋白质中提取侧链直接耦合的有效计算方法,并提供了耦合的稀疏网络表示。我们考虑了侧链构象多态性,并表明通过研究非活性结构的固有动力学,我们能够构建功能关键残基的网络。其次,我们表明所提出的方法能够提供耦合和构象多态性残基的放大视图。该模型揭示了耦合残基对的交替构象之间的耦合。据我们所知,这是提取侧链交替构象网络的第一种计算方法。这样的网络有助于提供功能重要和构象多态性位点(如结合和/或变构位点)中侧链动力学的详细图像。