Department of Pharmaceutical Sciences, College of Pharmacy, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205, United States.
Department of Pharmacology and Toxicology, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205, United States.
ACS Chem Neurosci. 2020 Oct 21;11(20):3455-3463. doi: 10.1021/acschemneuro.0c00551. Epub 2020 Sep 30.
The cannabinoid (CB) receptors (CBR and CBR) represent a promising therapeutic target for several indications such as nociception and obesity. The ligands with nonselectivity can be traced to the high similarity in the binding sites of both cannabinoid receptors. Therefore, the need for selectivity, potency, and G-protein coupling bias has further complicated the design of desired compounds. The bias of currently studied cannabinoid agonists is seldom investigated, and agonists that do exhibit bias are typically nonselective. However, certain long-chain endocannabinoids represent a class of selective and potent CBR agonists. The binding mode for this class of compounds has remained elusive, limiting the implementation of its binding features to currently studied agonists. Hence, in the present study, the binding poses for these long-chain cannabinoids, along with other interesting ligands, with the receptors have been determined, by using a combination of molecular docking and molecular dynamics (MD) simulations along with molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations. The binding poses for the long-chain cannabinoids implicate that a site surrounded by the transmembrane (TM)2, TM7, and extracellular loop (ECL)2 is vital for providing the long-chain ligands with the selectivity for CBR, especially I267 of CBR (corresponding to L182 of CBR). Based on the obtained binding modes, the calculated relative binding free energies and selectivity are all in good agreement with the corresponding experimental data, suggesting that the determined binding poses are reasonable. The computational strategy used in this study may also prove fruitful in applications with other GPCRs or membrane-bound proteins.
大麻素(CB)受体(CBR 和 CBR)代表了多种适应症(如疼痛和肥胖)的有前途的治疗靶点。非选择性配体可追溯到两种大麻素受体结合位点的高度相似性。因此,对选择性、效力和 G 蛋白偶联偏倚的需求进一步使所需化合物的设计复杂化。目前研究的大麻素激动剂的偏倚很少被研究,而表现出偏倚的激动剂通常是非选择性的。然而,某些长链内源性大麻素代表了一类选择性和有效的 CBR 激动剂。这类化合物的结合模式仍然难以捉摸,限制了其结合特征在当前研究的激动剂中的应用。因此,在本研究中,通过使用分子对接和分子动力学(MD)模拟以及分子力学-泊松-玻尔兹曼表面积(MM-PBSA)结合自由能计算的组合,确定了这些长链大麻素以及其他有趣配体与受体的结合构象。长链大麻素的结合构象表明,由跨膜(TM)2、TM7 和细胞外环(ECL)2 包围的位点对于为长链配体提供 CBR 的选择性至关重要,特别是 CBR 的 I267(对应于 CBR 的 L182)。基于获得的结合模式,计算的相对结合自由能和选择性与相应的实验数据非常吻合,表明确定的结合构象是合理的。本研究中使用的计算策略也可能在其他 GPCR 或膜结合蛋白的应用中证明是富有成效的。