Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA.
PLoS One. 2012;7(12):e50186. doi: 10.1371/journal.pone.0050186. Epub 2012 Dec 31.
Recently available G-protein coupled receptor (GPCR) structures and biophysical studies suggest that the difference between the effects of various agonists and antagonists cannot be explained by single structures alone, but rather that the conformational ensembles of the proteins need to be considered. Here we use an elastic network model-guided molecular dynamics simulation protocol to generate an ensemble of conformers of a prototypical GPCR, β(2)-adrenergic receptor (β(2)AR). The resulting conformers are clustered into groups based on the conformations of the ligand binding site, and distinct conformers from each group are assessed for their binding to known agonists of β(2)AR. We show that the select ligands bind preferentially to different predicted conformers of β(2)AR, and identify a role of β(2)AR extracellular region as an allosteric binding site for larger drugs such as salmeterol. Thus, drugs and ligands can be used as "computational probes" to systematically identify protein conformers with likely biological significance.
最近获得的 G 蛋白偶联受体(GPCR)结构和生物物理研究表明,各种激动剂和拮抗剂的作用差异不能仅用单个结构来解释,而是需要考虑蛋白质的构象集合。在这里,我们使用弹性网络模型引导的分子动力学模拟方案来生成典型 GPCR,β(2)-肾上腺素能受体(β(2)AR)的构象集合。根据配体结合位点的构象,将得到的构象聚类成组,并评估每个组的不同构象与已知的β(2)AR 激动剂的结合情况。我们表明,选择性配体优先与β(2)AR 的不同预测构象结合,并确定β(2)AR 细胞外区域作为较大药物(如沙美特罗)的变构结合位点的作用。因此,药物和配体可以用作“计算探针”,以系统地识别具有可能生物学意义的蛋白质构象。