Studying specificity in protein-glycosaminoglycan recognition with umbrella sampling

Mateusz Marcisz, Sebastian Anila, Margrethe Gaardløs, Martin Zacharias, Sergey A. Samsonov

Research output: Contribution to journalArticlepeer-review


In the past few decades, glycosaminoglycan (GAG) research has been crucial for gaining insights into various physiological, pathological, and therapeutic aspects mediated by the direct interactions between the GAG molecules and diverse proteins. The structural and functional heterogeneities of GAGs as well as their ability to bind specific proteins are determined by the sugar composition of the GAG, the size of the GAG chains, and the degree and pattern of sulfation. A deep understanding of the interactions in protein-GAG complexes is essential to explain their biological functions. In this study, the umbrella sampling (US) approach is used to pull away a GAG ligand from the binding site and then pull it back in. We analyze the binding interactions between GAGs of three types (heparin, desulfated heparan sulfate, and chondroitin sulfate) with three different proteins (basic fibroblast growth factor, acidic fibroblast growth factor, and cathepsin K). The main focus of our study was to evaluate whether the US approach is able to reproduce experimentally obtained structures, and how useful it can be for getting a deeper understanding of GAG properties, especially protein recognition specificity and multipose binding. We found that the binding free energy landscape in the proximity of the GAG native binding pose is complex and implies the co-existence of several binding poses. The sliding of a GAG chain along a protein surface could be a potential mechanism of GAG particular sequence recognition by proteins.

Original languageEnglish
Pages (from-to)1933-1946
Number of pages14
JournalBeilstein Journal of Organic Chemistry
StatePublished - 2023
Externally publishedYes


  • glycosaminoglycan
  • molecular docking
  • protein-glycosaminoglycan interaction specificity
  • umbrella sampling


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