title: Computational identification of novel natural inhibitors of glucagon receptor for checking type II diabetes mellitus.
abstract: BACKGROUND
  Interaction of the small peptide hormone glucagon with glucagon receptor (GCGR) stimulates the release of glucose from the hepatic cells during fasting; hence GCGR performs a significant function in glucose homeostasis. Inhibiting the interaction between glucagon and its receptor has been reported to control hepatic glucose overproduction and thus GCGR has evolved as an attractive therapeutic target for the treatment of type II diabetes mellitus.
  
  
  RESULTS
  In the present study, a large library of natural compounds was screened against 7 transmembrane domain of GCGR to identify novel therapeutic molecules that can inhibit the binding of glucagon with GCGR. Molecular dynamics simulations were performed to study the dynamic behaviour of the docked complexes and the molecular interactions between the screened compounds and the ligand binding residues of GCGR were analysed in detail. The top scoring compounds were also compared with already documented GCGR inhibitors- MK-0893 and LY2409021 for their binding affinity and other ADME properties. Finally, we have reported two natural drug like compounds PIB and CAA which showed good binding affinity for GCGR and are potent inhibitor of its functional activity.
  
  
  CONCLUSIONS
  This study contributes evidence for application of these compounds as prospective small ligand molecules against type II diabetes. Novel natural drug like inhibitors against the 7 transmembrane domain of GCGR have been identified which showed high binding affinity and potent inhibition of GCGR.
authors.forename: Sonam
authors.initials: S
authors.lastname: Grover
authors.forename: Jaspreet Kaur
authors.initials: JK
authors.lastname: Dhanjal
authors.forename: Sukriti
authors.initials: S
authors.lastname: Goyal
authors.forename: Abhinav
authors.initials: A
authors.lastname: Grover
authors.forename: Durai
authors.initials: D
authors.lastname: Sundar
mesh_terms: D001786:Blood Glucose / Q000032:analysis; D019295:Computational Biology / Q000379:methods*; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy* / Q000378:metabolism*; D005934:Glucagon / Q000037:antagonists & inhibitors* / Q000378:metabolism; D057166:High-Throughput Screening Assays; D006801:Humans; D008099:Liver / Q000187:drug effects / Q000378:metabolism; D056004:Molecular Dynamics Simulation; D019151:Peptide Library; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000378:metabolism*; D011485:Protein Binding / Q000187:drug effects; D011487:Protein Conformation; D011720:Pyrazoles / Q000494:pharmacology; D018027:Receptors, Glucagon / Q000037:antagonists & inhibitors* / Q000378:metabolism; D015091:beta-Alanine / Q000031:analogs & derivatives / Q000494:pharmacology; D009281:Naphthalenes
chemical_list: D001786:Blood Glucose; D005934:Glucagon; D019151:Peptide Library; D004364:Pharmaceutical Preparations; D011720:Pyrazoles; D018027:Receptors, Glucagon; D015091:beta-Alanine; C575263:N-((4-(1-(3-(3,5-dichlorophenyl)-5-(6-methoxynaphthalen-2-yl)-1H-pyrazol-1-yl)ethyl)phenyl)carbonyl)-beta-alanine; D009281:Naphthalenes