Glycosaminoglycans (GAGs), long linear periodic anionic polysaccharides, are key molecules in the extracellular matrix (ECM). Therefore, deciphering their role in the biologically relevant context is important for fundamental understanding of the processes ongoing in ECM and for establishing new strategies in the regenerative medicine. Although GAGs represent a number of computational challenges, molecular docking is a powerful tool for analysis of their interactions. Despite the recent development of GAG‐specific docking approaches, there is plenty of room for improvement. Here, replica exchange molecular dynamics with repulsive scaling (REMD‐RS) recently proved to be a successful approach for protein–protein complexes, was applied to dock GAGs. In this method, effective pairwise radii are increased in different Hamiltonian replicas. REMD‐RS is shown to be an attractive alternative to classical docking approaches for GAGs. This work contributes to setting up of GAG‐specific computational protocols and provides new insights into the nature of these biological systems.

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A proliferation-inducing ligand (APRIL) is a member of the tumor necrosis factor superfamily. APRIL is quite unique in this superfamily for at least for two reasons: i) it binds to glycosaminoglycans (GAGs) via its positively charged N-terminus; ii) one of its signaling receptor, the transmembrane activator CAML interactor (TACI) was also reported to bind GAGs. Here, as provided by biochemical evidences with the use of an APRIL deletion mutant linked to computational studies, APRIL-GAG interaction involved other regions than the APRIL N-terminus. Preferential interaction of APRIL with heparin followed by chondroitin sulfate E were confirmed by in silico analysis. Both computational and experimental approaches did not reveal heparan sulfate binding to TACI. Together, computational results corroborated experiments contributing with atomistic details to the knowledge on this biologically relevant trimolecular system. Additionally, a high-throughput rigorous analysis of the free energy calculations data was performed to critically evaluate the applied computational methodologies.

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The prediction power of computational methodologies for studying the role of ions in protein–glycosaminoglycan interactions was critically assessed.