Glycosaminoglycans (GAGs) represent a class of linear anionic periodic polysaccharides comprised of disaccharide units containing an amino sugar and an uronic acid. They have different sulfation patterns contributing to their structural variety and molecular recognition. GAGs play a key role in many biological processes in the extracellular matrix via interactions with their protein targets such as chemokines and growth factors and so actively participate in cell signalling. Both naturally occuring and synthetic GAGs with modified sulfation patterns represent promising targets in artificial matrix engineering for potential applications in regenerative medicine. Despite the recently increased interest for protein-GAG systems within the theoretical chemistry community, there is still a lack of computational approaches developed specifically for GAGs because of many challenges originated from their molecular properties. First, in comparison to the available structural data for other biomolecules, the data on protein-GAG complexes are limited. Second, due to the highly charged nature of GAGs, appropriate treatment of electrostatics and solvent-mediated interactions for those systems is required. The periodic nature, linearity and fuctional groups disposition of GAGs render them difficult targets for distinguishing and scoring different binding poses when these molecules are bound at the protein surface. The fact that GAGs in the extracellular matrix are long polymers hinders the appliction of many classical computational tools developed for small molecules and make coarse-grained models attractive for those systems. Last but not least, while being inaccessible for convenient molecular dynamics (MD) time scales, pucker conformational space of uronic acid derivatives within GAGs can impose a crucial effect on their binding properties. Molecular docking approaches applied to GAG ligands also experience challenges due to 1. poor geometric complementarity in GAG binding site; 2. important role of water molecules for binding; 3. flexibility of long positively charged residue side-chains participating in GAG binding; 4. lack of specifically developed scoring schemes often requiring additional experimental data-based constraints.