Abstract
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.
Highlights
The number of diabetic patients is rapidly increasing, reaching 425 million cases in 2018 [1]
The docking scores for Autodock VINA and Glide are based on different scoring functions but both of them were successfully used in virtual screening (VS) studies [42, 59, 60]
We hypothesized that off-target interactions of specificdrugs with gut hormone receptors glucagon-like peptide-1 receptor (GLP1R), gastric inhibitory polypeptide receptor (GIPR) and glucagon receptor (GCGR) could be a way to compensate for the negative influence of each on glucose homeostasis leading to drug-induced diabetes
Summary
The number of diabetic patients is rapidly increasing, reaching 425 million cases in 2018 [1]. The molecular mechanism underlying drug-induced T2DM, including potential off-target interactions [5], is still not fully understood and certainly varies from one drug class to another [3, 6, 7]. Additional details on T2DM induced by various drug classes have recently been described in a recent manuscript that is complementary to the current study [4]. This previous study mainly describes T2DM induced by diuretics, steroids and other drugs that were deposited in the SIDER database. The current study is focused only on the beta-blockers drug class
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