Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.
PLoS One. 2012;7(7):e39993. doi: 10.1371/journal.pone.0039993. Epub 2012 Jul 9.
Experimental conditions or the presence of interacting components can lead to variations in the structural models of macromolecules. However, the role of these factors in conformational selection is often omitted by in silico methods to extract dynamic information from protein structural models. Structures of small peptides, considered building blocks for larger macromolecular structural models, can substantially differ in the context of a larger protein. This limitation is more evident in the case of modeling large multi-subunit macromolecular complexes using structures of the individual protein components. Here we report an analysis of variations in structural models of proteins with high sequence similarity. These models were analyzed for sequence features of the protein, the role of scaffolding segments including interacting proteins or affinity tags and the chemical components in the experimental conditions. Conformational features in these structural models could be rationalized by conformational selection events, perhaps induced by experimental conditions. This analysis was performed on a non-redundant dataset of protein structures from different SCOP classes. The sequence-conformation correlations that we note here suggest additional features that could be incorporated by in silico methods to extract dynamic information from protein structural models.
实验条件或相互作用成分的存在会导致生物大分子结构模型发生变化。然而，在从蛋白质结构模型中提取动态信息时，计算方法通常忽略了这些因素在构象选择中的作用。在较大的蛋白质环境中，被认为是较大生物大分子结构模型构建模块的小肽结构会有很大差异。在使用单个蛋白质成分的结构对大型多亚基大分子复合物进行建模的情况下，这种限制更为明显。在这里，我们报告了对具有高序列相似性的蛋白质结构模型变化的分析。我们分析了蛋白质的序列特征、支架片段（包括相互作用蛋白或亲和标签）的作用以及实验条件中的化学组成。这些结构模型中的构象特征可以通过构象选择事件来合理化，这些事件可能是由实验条件引起的。我们对来自不同 SCOP 类别的蛋白质结构的非冗余数据集进行了此分析。我们在这里注意到的序列-构象相关性表明，可以通过计算方法将其他特征纳入其中，以从蛋白质结构模型中提取动态信息。
