Instituto de Química, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Facultad de Química, Universidad Nacional Autónoma de México, Mexico City, Mexico.
J Comput Aided Mol Des. 2021 Nov;35(11):1081-1093. doi: 10.1007/s10822-021-00422-5. Epub 2021 Oct 29.
Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein biased agonists of the μ-opioid receptor (MOR) have shown safer therapeutic profiles than non-biased ligands. In this work, we performed extensive all-atom molecular dynamics simulations of two markedly biased ligands and a balanced reference molecule. From those simulations, we identified a protein-ligand interaction fingerprint that characterizes biased ligands. Then, we built and virtually screened a database containing 68,740 ligands with proven or potential GPCR agonistic activity. Exemplary molecules that fulfill the interacting pattern for biased agonism are showcased, illustrating the usefulness of this work for the search of biased MOR ligands and how this contributes to the understanding of MOR biased signaling.
阿片类药物是强效止痛药，然而，它们的治疗用途需要密切的医疗监测，以降低严重不良反应的风险。μ-阿片受体（MOR）的 G 蛋白偏向激动剂比非偏向配体显示出更安全的治疗谱。在这项工作中，我们对两种明显偏向激动剂和一种平衡参考分子进行了广泛的全原子分子动力学模拟。从这些模拟中，我们确定了一种可以表征偏向激动剂的蛋白-配体相互作用指纹。然后，我们构建并虚拟筛选了一个包含 68740 种具有已证明或潜在 GPCR 激动活性的配体的数据库。展示了符合偏向激动作用相互作用模式的典型分子，说明了这项工作对于寻找偏向 MOR 配体的有用性，以及这如何有助于理解 MOR 偏向信号。
