Potential off-target effects of beta-blockers on gut hormone receptors: In silico study including GUT-DOCK-A web service for small-molecule docking.

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

The GPCRM modeling pipeline.

<p>A human intervention is possible in the ‘Advanced’ user mode at the steps indicated by asterisks.</p

Antagonist docking to GPCRM-generated homology models versus self-docking: β1AR receptor (A) and D3R receptor (B).

<p>Structures of complexes with indicated polar contacts obtained by crystallography are shown in grey, while the docked structures are depicted in yellow. GPCRM-generated homology models are shown in green. Left panels show the best poses obtained in the docking to corresponding protein homology models. Right panels show results of self-docking to crystallographic structures (PDB id: 2VT4 and 3PBL). All polar contacts were preserved, except one hydrogen bond with Ser211 (A).</p

Comparison of various methods for the alignment generation in GPCRM.

<p>Here, we plotted ClustalW2 identity scores versus the alignment accuracy (the upper plot) or versus the difference between the accuracy provided by profile-profile alignment and PSA or MSA (the lower plot). The ClustalW2 score and PDB id for both the target and template proteins are provided on the right panel.</p

Multiple template modeling of A2AR.

<p>The model (green) was generated by GPCRM and is superposed on the crystal structure (blue) and templates used in the model building: the β1AR adrenergic receptor (grey) and the histamine H1R (pink). The bulge observed in TMH4 in β1AR is properly transferred to the A2AR model. Additionally, incorporation of the second template (H1R) improves the kink of TMH1 in the A2A model. The TMH4 bulge can be examined in details in pictures taken from different angles presented on the left.</p

Comparison of the GPCRM model building procedure based on one, two and three template structures.

1<p>Here, we computed heavy-atoms RMSD of the best model. The binding site area is defined as a set of residues which are in the 5 Å sphere around the ligand in the reference crystal structure.</p>2<p>ClustalW2 scores (normalized to 100) indicating sequence identity are provided in brackets.</p

Towards Improved Quality of GPCR Models by Usage of Multiple Templates and Profile-Profile Comparison

<div><p>G-protein coupled receptors (GPCRs) are targets of nearly one third of the drugs at the current pharmaceutical market. Despite their importance in many cellular processes the crystal structures are available for less than 20 unique GPCRs of the Rhodopsin-like class. Fortunately, even though involved in different signaling cascades, this large group of membrane proteins has preserved a uniform structure comprising seven transmembrane helices that allows quite reliable comparative modeling. Nevertheless, low sequence similarity between the GPCR family members is still a serious obstacle not only in template selection but also in providing theoretical models of acceptable quality. An additional level of difficulty is the prediction of kinks and bulges in transmembrane helices. Usage of multiple templates and generation of alignments based on sequence profiles may increase the rate of success in difficult cases of comparative modeling in which the sequence similarity between GPCRs is exceptionally low. Here, we present GPCRM, a novel method for fast and accurate generation of GPCR models using averaging of multiple template structures and profile-profile comparison. In particular, GPCRM is the first GPCR structure predictor incorporating two distinct loop modeling techniques: Modeller and Rosetta together with the filtering of models based on the Z-coordinate. We tested our approach on all unique GPCR structures determined to date and report its performance in comparison with other computational methods targeting the Rhodopsin-like class. We also provide a database of precomputed GPCR models of the human receptors from that class.</p> <p>Availability</p><p>GPCRM server and database: <a href="http://gpcrm.biomodellab.eu" target="_blank">http://gpcrm.biomodellab.eu</a></p> </div

Benchmark results of GPCRM in structure modeling and small molecule docking.

1<p>Here, we provided as a reference results of self-docking to crystal structures of GPCRs.</p>2<p>The binding site area is defined as a set of residues which are inside the 5Å sphere around the ligand.</p

A scheme of 7TMH fold of Rhodopsin-like class of GPCRs.

<p>Here, we superposed crystal structures of three GPCRs of varied loop conformations: chemokine CXCR4 (PDB id: 3ODU), adrenergic β2AR (2RH1) and adenosine A2AR receptors (2YDV). Except for variety of loop conformations, GPCR structures differ by kinks in TM helices, e.g., in TMH1 (dark blue) and TMH5 (orange), and the length of TM helices, e.g., of TMH7 (dark red).</p