Faculty of Chemistry, University of Warsaw, Warsaw, Poland.
Department of Pharmacognosy, Faculty of Pharmacy, Poznan University of Medical Sciences, Poznan, Poland.
PLoS One. 2019 Jan 25;14(1):e0210705. doi: 10.1371/journal.pone.0210705. eCollection 2019.
The prolonged use of many currently available drugs results in the severe side effect of the disruption of glucose metabolism leading to type 2 diabetes mellitus (T2DM. Gut hormone receptors including glucagon receptor (GCGR) and the incretin hormone receptors: glucagon-like peptide 1 receptor (GLP1R) and gastric inhibitory polypeptide receptor (GIPR) are important drug targets for the treatment of T2DM, as they play roles in the regulation of glucose and insulin levels and of food intake. In this study, we hypothesized that we could compensate for the negative influences of specific drugs on glucose metabolism by the positive incretin effect enhanced by the off-target interactions with incretin GPCR receptors. As a test case, we chose to examine beta-blockers because beta-adrenergic receptors and incretin receptors are expressed in a similar location, making off-target interactions possible. The binding affinity of drugs for incretin receptors was approximated by using two docking scoring functions of Autodock VINA (GUT-DOCK) and Glide (Schrodinger) and juxtaposing these values with the medical information on drug-induced T2DM. We observed that beta-blockers with the highest theoretical binding affinities for gut hormone receptors were reported as the least harmful to glucose homeostasis in clinical trials. Notably, a recently discovered beta-blocker compound 15 ([4-((2S)-3-(((S)-3-(3-bromophenyl)-1-(methylamino)-1-oxopropan-2-yl)amino)-2-(2-cyclohexyl-2-phenylacetamido)-3-oxopropyl)benzamide was among the top-scoring drugs, potentially supporting its use in the treatment of hypertension in diabetic patients. Our recently developed web service GUT-DOCK (gut-dock.miningmembrane.com) allows for the execution of similar studies for any drug-like molecule. Specifically, users can compute the binding affinities for various class B GPCRs, gut hormone receptors, VIPR1 and PAC1R.
目前许多可用药物的长期使用会导致葡萄糖代谢紊乱，从而引发 2 型糖尿病（T2DM）等严重副作用。胰高血糖素受体（GCGR）和肠降血糖素受体，包括胰高血糖素样肽 1 受体（GLP1R）和胃抑制多肽受体（GIPR）等肠道激素受体，是治疗 T2DM 的重要药物靶点，因为它们在调节血糖和胰岛素水平以及摄食方面发挥作用。在这项研究中，我们假设可以通过与肠降血糖素 GPCR 受体的非靶点相互作用增强的正肠降血糖素作用来补偿特定药物对葡萄糖代谢的负面影响。作为一个测试案例，我们选择了β-受体阻滞剂，因为β-肾上腺素能受体和肠降血糖素受体在相似的位置表达，这使得非靶点相互作用成为可能。我们使用 Autodock VINA（GUT-DOCK）和 Glide（Schrodinger）的两种对接评分函数来近似药物与肠降血糖素受体的结合亲和力，并将这些值与药物引起的 T2DM 的医学信息进行对比。我们观察到，与肠激素受体具有最高理论结合亲和力的β-受体阻滞剂在临床试验中被报告为对葡萄糖稳态危害最小的药物。值得注意的是，最近发现的β-受体阻滞剂化合物 15（[4-（（2S）-3-（（S）-3-（3-溴苯基）-1-（甲基氨基）-1-氧代丙-2-基）氨基）-2-（2-环己基-2-苯基乙酰氨基）-3-氧代丙基）苯甲酰胺）在得分最高的药物之列，这可能支持其在治疗糖尿病患者高血压方面的应用。我们最近开发的网络服务 GUT-DOCK（gut-dock.miningmembrane.com）允许对任何类药性分子执行类似的研究。具体来说，用户可以计算各种 B 类 GPCR、肠降血糖素受体、VIPR1 和 PAC1R 的结合亲和力。
