Advertisement

Improvements in the Chemical Synthesis of Insulin-Like Peptides

  • Panagiota Tsetseni
  • Aggeliki Karkantzou
  • Spyros Markos
  • Kostas Barlos
  • Dimitrios Gatos
  • Kleomenis Barlos
Part of the Advances in Experimental Medicine and Biology book series (volume 611)

Introduction

The synthesis of insulin and insulin-like peptides is performed by the selective combination of the independently synthesized A- and B-chains. The main strategy followed for the chain combination is to protect the side-chains of the cysteine residues by three different protecting groups of gradually increased acid and oxidative sensitivity. Before starting the chain combination, the intramolecular disulfide bond formation in A-chain is performed by treatment the thiol-free peptide with dipyridyldisulfide. The interchain combination is then performed again by using selective disulfide bond formation by activating one thiol function of the A-chain with pyridine sulfide and combining with the thiol free B-chain [1]. Although the method is theoretically straightforward, the reported yields during the chain synthesis and the interchain combination are very poor. In this study we report on the results of the synthesis of the A- and B-chains of human insulin and relaxin and the...

Keywords

Human Insulin Disulfide Bond Formation Correct Mass Step Synthesis Intramolecular Disulfide Bond 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The work was funded by CBL-Patras S.A.

References

  1. 1.
    Samuel, C. et al. Biochem. 46, 5374–5381 (2007).CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Panagiota Tsetseni
    • 1
  • Aggeliki Karkantzou
    • 1
  • Spyros Markos
    • 1
  • Kostas Barlos
    • 1
  • Dimitrios Gatos
    • 1
  • Kleomenis Barlos
    • 1
  1. 1.Department of ChemistryUniversity of PatrasPatrasGreece

Personalised recommendations