Laboratory of Molecular Neuropharmacology and Bioinformatics, Unitat de Bioestadística and Institut de Neurociències, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.
Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain.
Int J Mol Sci. 2020 Dec 27;22(1):187. doi: 10.3390/ijms22010187.
G protein-coupled Receptors (GPCRs) play a central role in many physiological processes and, consequently, constitute important drug targets. In particular, the search for allosteric drugs has recently drawn attention, since they could be more selective and lead to fewer side effects. Accordingly, computational tools have been used to estimate the druggability of allosteric sites in these receptors. In spite of many successful results, the problem is still challenging, particularly the prediction of hydrophobic sites in the interface between the protein and the membrane. In this work, we propose a complementary approach, based on dynamical correlations. Our basic hypothesis was that allosteric sites are strongly coupled to regions of the receptor that undergo important conformational changes upon activation. Therefore, using ensembles of experimental structures, normal mode analysis and molecular dynamics simulations we calculated correlations between internal fluctuations of different sites and a collective variable describing the activation state of the receptor. Then, we ranked the sites based on the strength of their coupling to the collective dynamics. In the β2 adrenergic (β2AR), glucagon (GCGR) and M2 muscarinic receptors, this procedure allowed us to correctly identify known allosteric sites, suggesting it has predictive value. Our results indicate that this dynamics-based approach can be a complementary tool to the existing toolbox to characterize allosteric sites in GPCRs.
G 蛋白偶联受体（GPCRs）在许多生理过程中发挥着核心作用，因此成为了重要的药物靶点。特别是，近年来人们对别构药物的研究引起了关注，因为它们可能具有更高的选择性，并导致更少的副作用。因此，计算工具被用于估计这些受体中别构位点的成药性。尽管已经取得了许多成功的结果，但这个问题仍然具有挑战性，特别是预测蛋白质和膜之间界面的疏水性位点。在这项工作中，我们提出了一种基于动力学相关性的互补方法。我们的基本假设是，别构位点与受体中在激活时经历重要构象变化的区域强烈耦合。因此，我们使用实验结构的集合、正常模式分析和分子动力学模拟，计算了不同位点的内部波动与描述受体激活状态的集体变量之间的相关性。然后，我们根据它们与集体动力学的耦合强度对这些位点进行了排序。在β2 肾上腺素能（β2AR）、胰高血糖素（GCGR）和 M2 毒蕈碱受体中，该方法能够正确识别已知的别构位点，表明它具有预测价值。我们的结果表明，这种基于动力学的方法可以作为现有工具包的补充工具，用于表征 GPCRs 中的别构位点。
