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Interaction of Glucagon G-Protein Coupled Receptor with Known Natural Antidiabetic Compounds: Multiscoring In Silico Approach.

ABSTRACT: Glucagon receptor (GCGR) is a secretin-like (class B) family of G-protein coupled receptors (GPCRs) in humans that plays an important role in elevating the glucose concentration in blood and has thus become one of the promising therapeutic targets for treatment of type 2 diabetes mellitus. GCGR based inhibitors for the treatment of type 2 diabetes are either glucagon neutralizers or small molecular antagonists. Management of diabetes without any side effects is still a challenge to the medical system, and the search for a new and effective natural GCGR antagonist is an important area for the treatment of type 2 diabetes. In the present study, a number of natural compounds containing antidiabetic properties were selected from the literature and their binding potential against GCGR was determined using molecular docking and other in silico approaches. Among all selected natural compounds, curcumin was found to be the most effective compound against GCGR followed by amorfrutin 1 and 4-hydroxyderricin. These compounds were rescored to confirm the accuracy of binding using another scoring function (x-score). The final conclusions were drawn based on the results obtained from the GOLD and x-score. Further experiments were conducted to identify the atomic level interactions of selected compounds with GCGR.

SUBMITTER: Baig MH

PROVIDER: S-EPMC4508340 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Interaction of Glucagon G-Protein Coupled Receptor with Known Natural Antidiabetic Compounds: Multiscoring In Silico Approach.

Baig M H MH Ahmad K K Hasan Q Q Khan M K A MK Rao N S NS Kamal M A MA Choi I I

Evidence-based complementary and alternative medicine : eCAM 20150706

Glucagon receptor (GCGR) is a secretin-like (class B) family of G-protein coupled receptors (GPCRs) in humans that plays an important role in elevating the glucose concentration in blood and has thus become one of the promising therapeutic targets for treatment of type 2 diabetes mellitus. GCGR based inhibitors for the treatment of type 2 diabetes are either glucagon neutralizers or small molecular antagonists. Management of diabetes without any side effects is still a challenge to the medical s ...[more]

PMID: 26236379

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Project description:BackgroundNatural extracts have played an important role in the prevention and treatment of diseases and are important sources for drug discovery. However, to be effectively used in these processes, natural extracts must be characterized through the identification of their active compounds and their modes of action.Methodology/principal findingsFrom an initial set of 29,779 natural products that are annotated with their natural source and using a previously developed virtual screening procedure (carefully validated experimentally), we have predicted as potential peroxisome proliferators-activated receptor gamma (PPAR?) partial agonists 12 molecules from 11 extracts known to have antidiabetic activity. Six of these molecules are similar to molecules with described antidiabetic activity but whose mechanism of action is unknown. Therefore, it is plausible that these 12 molecules could be the bioactive molecules responsible, at least in part, for the antidiabetic activity of the extracts containing them. In addition, we have also identified as potential PPAR? partial agonists 10 molecules from 16 plants with undescribed antidiabetic activity but that are related (i.e., they are from the same genus) to plants with known antidiabetic properties. None of the 22 molecules that we predict as PPAR? partial agonists show chemical similarity with a group of 211 known PPAR? partial agonists obtained from the literature.Conclusions/significanceOur results provide a new hypothesis about the active molecules of natural extracts with antidiabetic properties and their mode of action. We also suggest plants with undescribed antidiabetic activity that may contain PPAR? partial agonists. These plants represent a new source of potential antidiabetic extracts. Consequently, our work opens the door to the discovery of new antidiabetic extracts and molecules that can be of use, for instance, in the design of new antidiabetic drugs or functional foods focused towards the prevention/treatment of type 2 Diabetes Mellitus.

Project description:BackgroundToll-like receptor 9 (TLR9) recognises unmethylated CpG DNA and activates a signalling cascade, leading to the production of inflammatory cytokines such as TNF-α, IL-1, IL-6 and IL-12 via the adaptor protein MyD88. However, the specific sequence and structural requirements of the CpG DNA for the recognition of and binding to TLR9 are unknown. Moreover, the 3D structures of TLR9 and the TLR9-ODN complex have not been determined. In this study, we propose a reliable model of the interaction of the TLR9 ECD with CpG ODN using bioinformatics tools.ResultsThe three-dimensional structures of two TLR9 ECD-CpG ODN complexes were constructed using a homology modelling and docking strategy. Based on the models of these complexes, the TLR9 ECD-CpG ODN interaction patterns were calculated. The results showed that the interface between the human TLR9 and the CpG ODN molecule is geometrically complementary. The computed molecular interactions indicated that LRR11 is the main region of TLR9 that binds to CpG ODN and that five positively charged residues within LRR11 are involved in the binding of the TLR9 ECD to the CpG ODN. Observations in the close-up view of these interactions indicated that these five positively charged residues contribute differently to the binding region within the TLR9 ECD-CpG ODN complex. 337Arg and 338Lys reside in the binding sites of ODN, forming hydrogen bonds and direct contacts with the CpG ODN, whereas 347Lys, 348Arg, and 353His do not directly contact the CpG ODN. These results are in agreement with previously reported experimental data.ConclusionIn this study, we present two structural models for the human and mouse TLR9 ECD in a complex with CpG ODN. Some features predicted by this model are consistent with previously reported experimental data. This complex model may lead to a better understanding of the function of TLR9 and its interaction with CpG ODN and will improve our understanding of TLR9-ligand interaction in general.

Dataset Information

Interaction of Glucagon G-Protein Coupled Receptor with Known Natural Antidiabetic Compounds: Multiscoring In Silico Approach.

Publications

Interaction of Glucagon G-Protein Coupled Receptor with Known Natural Antidiabetic Compounds: Multiscoring In Silico Approach.

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