INTERLEUKIN-8 INTERACTIONS WITH GLYCOSAMINOGLYCANS: MERGING COMPUTATIONAL AND EXPERIMENTAL APPROACHES

Sergey Samsonov 1 Karoline Nordsieck 2 Annelie Pichert 3 Kristin Möbius 3 Lars Thomas 3 Christian Berger 3 Jürgen Schiller 3 Annette Beck-Sickinger 2 Daniel Huster 3 M. Teresa Pisabarro 1
1Structural Bioinformatics, Biotechnology Center, Technical University of Dresden, Dresden
2Institute of Biochemistry, University of Leipzig, Leipzig
3Institute of Medical Physics and Biophysics, University of Leipzig, Leipzig

Interactions of glycosaminoglycans (GAGs) with their protein targets, such as chemokines and growth factors, are crucial for cell communication processes1. Therefore, an elaborate characterization of these interactions is of a great interest for developing strategies for engineering novel biomaterials for tissue regeneration. There is experimental evidence that the function of interleukin-8 (IL-8) is strongly influenced by interactions with GAGs. However, molecular mechanisms underlying IL-8/GAG interactions are unknown, and no experimental structures of IL-8/GAG complexes are available. We use computational approaches (docking, molecular dynamics, free energy calculations) linked to experimental techniques (NMR, mutagenesis, surface plasmon resonance, fluorescence) to elucidate details of molecular mechanisms underlying IL-8/GAG recognition. We have predicted and analyzed the binding pose of different GAGs to IL-8. Our predictions have been confirmed by NMR2. We have used use our theoretical models to determine the energetic impact of individual IL-8 residues for GAG binding and to propose experiments to determine the role of those residues. We have designed a mutant IL-8E75K, for which we have identified a new GAG binding pose that is not favourable for the wild type and that agrees with our NMR data3. We have designed N- and C-terminally truncated IL-8 variants and analyzed them in terms of their abilities to dimerize and bind GAGs. Our data assist in a better understanding of the IL-8/GAG interactions exhibiting an example of how computational and experimental techniques can benefit from each other in analysis of protein/GAG interactions.

    References:

  1. Gesslbauer B. et al., Expert Rev Proteomics., 2013, 10, 77-95.

  2. Pichert A. et al., Glycobiology, 2012, 22, 134-145.

  3. Nordsieck K. et al., ChemBioChem, 2012, 13, 2558-2566.








 




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