26
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Structural Determinants of Binding the Seven-transmembrane Domain of the Glucagon-like Peptide-1 Receptor (GLP-1R)

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The glucagon-like peptide-1 receptor (GLP-1R) belongs to the secretin-like (class B) family of G protein-coupled receptors. Members of the class B family are distinguished by their large extracellular domain, which works cooperatively with the canonical seven-transmembrane (7TM) helical domain to signal in response to binding of various peptide hormones. We have combined structure-based site-specific mutational studies with molecular dynamics simulations of a full-length model of GLP-1R bound to multiple peptide ligand variants. Despite the high sequence similarity between GLP-1R and its closest structural homologue, the glucagon receptor (GCGR), nearly half of the 62 stably expressed mutants affected GLP-1R in a different manner than the corresponding mutants in GCGR. The molecular dynamics simulations of wild-type and mutant GLP-1R·ligand complexes provided molecular insights into GLP-1R-specific recognition mechanisms for the N terminus of GLP-1 by residues in the 7TM pocket and explained how glucagon-mimicking GLP-1 mutants restored binding affinity for (GCGR-mimicking) GLP-1R mutants. Structural analysis of the simulations suggested that peptide ligand binding mode variations in the 7TM binding pocket are facilitated by movement of the extracellular domain relative to the 7TM bundle. These differences in binding modes may account for the pharmacological differences between GLP-1 peptide variants.

          Related collections

          Most cited references44

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Canonical sampling through velocity-rescaling

          We present a new molecular dynamics algorithm for sampling the canonical distribution. In this approach the velocities of all the particles are rescaled by a properly chosen random factor. The algorithm is formally justified and it is shown that, in spite of its stochastic nature, a quantity can still be defined that remains constant during the evolution. In numerical applications this quantity can be used to measure the accuracy of the sampling. We illustrate the properties of this new method on Lennard-Jones and TIP4P water models in the solid and liquid phases. Its performance is excellent and largely independent on the thermostat parameter also with regard to the dynamic properties.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            GLP-1 receptor agonists for individualized treatment of type 2 diabetes mellitus.

            In healthy humans, the incretin glucagon-like peptide 1 (GLP-1) is secreted after eating and lowers glucose concentrations by augmenting insulin secretion and suppressing glucagon release. Additional effects of GLP-1 include retardation of gastric emptying, suppression of appetite and, potentially, inhibition of β-cell apoptosis. Native GLP-1 is degraded within ~2-3 min in the circulation; various GLP-1 receptor agonists have, therefore, been developed to provide prolonged in vivo actions. These GLP-1 receptor agonists can be categorized as either short-acting compounds, which provide short-lived receptor activation (such as exenatide and lixisenatide) or as long-acting compounds (for example albiglutide, dulaglutide, exenatide long-acting release, and liraglutide), which activate the GLP-1 receptor continuously at their recommended dose. The pharmacokinetic differences between these drugs lead to important differences in their pharmacodynamic profiles. The short-acting GLP-1 receptor agonists primarily lower postprandial blood glucose levels through inhibition of gastric emptying, whereas the long-acting compounds have a stronger effect on fasting glucose levels, which is mediated predominantly through their insulinotropic and glucagonostatic actions. The adverse effect profiles of these compounds also differ. The individual properties of the various GLP-1 receptor agonists might enable incretin-based treatment of type 2 diabetes mellitus to be tailored to the needs of each patient.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Generic GPCR residue numbers - aligning topology maps while minding the gaps.

              Generic residue numbers facilitate comparisons of, for example, mutational effects, ligand interactions, and structural motifs. The numbering scheme by Ballesteros and Weinstein for residues within the class A GPCRs (G protein-coupled receptors) has more than 1100 citations, and the recent crystal structures for classes B, C, and F now call for a community consensus in residue numbering within and across these classes. Furthermore, the structural era has uncovered helix bulges and constrictions that offset the generic residue numbers. The use of generic residue numbers depends on convenient access by pharmacologists, chemists, and structural biologists. We review the generic residue numbering schemes for each GPCR class, as well as a complementary structure-based scheme, and provide illustrative examples and GPCR database (GPCRDB) web tools to number any receptor sequence or structure.
                Bookmark

                Author and article information

                Journal
                Journal of Biological Chemistry
                J. Biol. Chem.
                American Society for Biochemistry & Molecular Biology (ASBMB)
                0021-9258
                1083-351X
                June 17 2016
                June 17 2016
                : 291
                : 25
                : 12991-13004
                Article
                10.1074/jbc.M116.721977
                4933217
                27059958
                568bd122-2ce4-46fe-9d3b-446743f38fcf
                © 2016
                History

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content1,386

                Cited by18

                Most referenced authors1,457