An in silico structure-based approach to map the druggable allosteric space of membrane receptors

膜受体使细胞能够对化学和物理信号做出反应，激活细胞内一系列复杂的生物事件，最终导致细胞生物学的变化。G蛋白偶联受体(GPCRs)、配体和电压门控离子通道受体以及酪氨酸激酶受体是目前临床上使用的近60%药物的有效靶点。受体的生物状态可以通过作用于空间上不同的变构结合部位的小分子配体来调节，从而产生比靶向正构部位的药物更具选择性和更安全的药物。最近的研究指出了变构调节的共同机制，并发现了针对这些受体家族的合成变构调节剂。然而，变构位点和调节剂的发现在很大程度上是偶然的，是通过高通量筛选实现的。最近结构生物学的一项突破揭示了几个与变构调节剂结合的GPCR的晶体结构，为在膜受体中发现变构药物提供了预测计算方法的机会。我们的目标是开发一种通用的基于结构的计算方法来寻找膜受体中的变构结合部位。由于新获得的GPCR-变构调节剂复合体的晶体结构显示了变构部位的不同位置，我们的目标是开发计算程序来绘制受体内部的变构部位，以及受体外部与脂质双层的界面上的变构部位。我们的方法将依赖于对现实细胞环境中受体动力学的研究，以及精心选择的有机溶剂的存在。有机溶剂将被用作寻找结合位点的探针。我们将首先开发方法，其中我们预测具有受体-变构配体复合体(训练集)的可用晶体结构的受体的变构位置，然后探索开发的预测新受体的变构位置的计算程序(测试集)，并进一步验证突变和化合物筛选中的预测结果。生物胺、多肽和核苷酸受体将用于开发该方法。我们将结合我们的受体案例研究和序列方法来预测GPCRs中变构位点位置的一般分子基础。我们的计算方法将促进开发新的治疗方法，用于治疗与GPCR相关的疾病，如炎症、不孕不育、代谢和神经疾病、病毒感染和癌症。为一种膜受体家族开发的计算策略将使其应用于其他受体家族。

Membrane receptors enable cells to respond to chemical and physical signals, activate a complex chain of biological events inside the cell and ultimately lead to a change in cell biology. The G protein-coupled receptors (GPCRs), ligand- and voltage-gated ion channel receptors and tyrosine kinase receptors are effective targets of nearly 60 % of the medicines currently used in clinics. The receptor biological state can be modulated by small molecule ligands acting on spatially distinct allosteric binding sites that result in more selective and safer medicines than those targeting orthosteric sites. Recent studies point to common mechanisms of allosteric regulation and the discovery of synthetic allosteric modulators for these receptor families. However, the discovery of allosteric sites and modulators has been largely serendipitous, achieved through high-throughput screening. A recent breakthrough in structural biology disclosed the crystal structures of several GPCRs bounded to allosteric modulators providing opportunities to develop predictive computational methodologies for allosteric medicine discovery in the membrane receptors. We aim to develop a general structure-based computational methodology to search for allosteric binding sites in the membrane receptors. Since the newly available crystal structures of GPCR-allosteric modulator complexes indicate a diverse location of allosteric sites, we aim to develop computational procedures to map allosteric sites inside of the receptors; and outside of the receptor at the interface with the lipid bilayer. Our methodology will rely on the study of receptor dynamics in realistic cellular environment with the presence of carefully selected organic solvents. The organic solvents will be used as probes to search for binding sites. We will initially develop the methodology, where we predict allosteric sites for the receptors with the available crystal structures of a receptor-allosteric ligand complex (the training set) and then explore developed computational procedures predicting allosteric sites for new receptors (the test set) with further validation of the results of prediction in mutagenesis and compound screening. The bioamine, peptide and nucleotide receptors will be used to develop the methodology. We will use our receptor case studies together with sequence approaches to predict a general molecular basis of allosteric site location in GPCRs. Our computational methodology will facilitate the development of new therapies for the treatment of GPCR-related diseases such as inflammation, infertility, metabolic and neurological disorders, viral infections and cancer. The computational strategy developed for one membrane receptor family will enable its applications to other receptor families.