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Mapping interactions of gastric inhibitory polypeptide with GIPR N ‐terminus using NMR and molecular dynamics simulations
Author(s) -
Tikhele Sonali H.,
Pissurlenkar Raghuvir R. S.,
Srivastava Sudha,
Saran Anil,
Coutinho Evans C.
Publication year - 2010
Publication title -
journal of peptide science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.475
H-Index - 66
eISSN - 1099-1387
pISSN - 1075-2617
DOI - 10.1002/psc.1250
Subject(s) - gastric inhibitory polypeptide , molecular dynamics , chemistry , two dimensional nuclear magnetic resonance spectroscopy , incretin , peptide , n terminus , amino acid , crystallography , peptide sequence , biochemistry , stereochemistry , endocrinology , hormone , biology , glucagon , computational chemistry , diabetes mellitus , gene , type 2 diabetes
Abstract Glucose‐dependent insulinotropic polypeptide (gastric inhibitory polypeptide, or GIP), a 42‐amino acid incretin hormone, modulates insulin secretion in a glucose‐concentration‐dependent manner. Its insulinotropic action is highly dependent on glucose concentration that surmounts the hypoglycemia side effects associated with current therapy. In order to develop a GIP‐based anti‐diabetic therapy, it is essential to establish the 3D structure of the peptide and study its interaction with the GIP receptor (GIPR) in detail. This will give an insight into the GIP‐mediated insulin release process. In this article, we report the solution structure of GIP(1–42, human)NH 2 deduced by NMR and the interaction of the peptide with the N ‐terminus of GIPR using molecular modelling methods. The structure of GIP(1–42, human)NH 2 in H 2 O has been investigated using 2D‐NMR (DQF‐COSY, TOCSY, NOESY, 1 H‐ 13 C HSQC) experiments, and its conformation was built by constrained MD simulations with the NMR data as constraints. The peptide in H 2 O exhibits an α‐helical structure between residues Ser8 and Asn39 with some discontinuity at residues Gln29 to Asp35; the helix is bent at Gln29. This bent gives the peptide an ‘L’ shape that becomes more pronounced upon binding to the receptor. The interaction of GIP with the N ‐terminus of GIPR was modelled by allowing GIP to interact with the N ‐terminus of GIPR under a series of decreasing constraints in a molecular dynamics simulation, culminating with energy minimization without application of any constraints on the system. The canonical ensemble obtained from the simulation was subjected to a detailed energy analysis to identify the peptide–protein interaction patterns at the individual residue level. These interaction energies shed some light on the binding of GIP with the GIPR N ‐terminus in a quantitative manner. Copyright © 2010 European Peptide Society and John Wiley & Sons, Ltd.