Glycosaminoglycans (GAGs) are long unbranched periodic and negatively charged polysaccharides. Each GAG with an exception of keratan sulfate consists of one uronic acid and one aminosugar and can be distinguished by their sulfation patterns known as sulfation code. GAGs are present in extracellular matrix of the cell in which they are involved in many relevant biological processes including angiogenesis, anticoagulation, adhesion, cell proliferation and signaling cascades by electrostatics-driven interactions with their protein targets.
Heparin (HE) is made up of a 2-O-sulfated iduronic acid and 6-O-sulfated N-sulfated glucosamine with a -4 net charge per disaccharide unit. Being a part of proteoglycans, HE binds its protein targets such as chemokines and growth factors and thus actively participates in multiple biochemical signaling pathways. The family of mammalian fibroblast growth factors (FGF), one of HE targets consists of 18 members. FGFs are involved in a wide spectrum of biochemical processes ranging from development and regenerative processes to metabolim and tissue homeostatis. The complex of FGF1-HE was mostly characterized both experimentally and computationally.
One has to know that application of experimental techniques alone might not be sufficient enough to gain a complete picture of protein-GAG interactions, hence theoretical approaches not only complement but also beneficially contribute to the understanding of the role of GAGs by bringing principally new and experimentally inaccessible details. However, computational analysis of GAG containing systems requires proper treatment and thus represents substantial challenge. The main reasons of that are: i) GAGs are characterized by their highly charged nature which leads to the importance of electrostatic-driven interactions and abundant solvent-mediated ones; ii) GAGs prefer to bind at solvent-exposed and spatially close but sequentially not necessarily successive positively charged aminoacid patches, made up of Lys or Arg residues and that possess long and flexible side chains, and they also contribute to the challenge in terms of how flexibility should be treated appropriately for these systems; iii) GAGs are very flexible in terms of their glycosidic linkage as well as pucker ring conformation.
When using computational methodology, protein-GAG systems are usually studied in nanosecond timescale simulations. However, performing calculations in a microsecond timescale leads to qualitatively different results including those corresponding to overall complex stability (free energy calculations) as well as those corresponding to complex structure (number of native and nonnative contacts, hydrogen bonds analysis).
The aims of this study involved: i) performing the rigorous conformational analysis of unbound HE, which involved clustering analysis of the structures observed in the MD simulation, and the analysis of conformational space of IdoA2S and GlcNS6S puckers along with conformational space of glycosidic linkages and H-bonding between these two monosaccharide units; ii) to characterize the interactions in the FGF1-HE system in a course of a 10 microsecond-long MD simulation; iii) to elucidate the mechanism of binding in this system; iv) to compare the performance of the previously described computational approaches for this system in the nanoscale and the presented microscale MD simulations in terms of complex free energy-based stability and the observed FGF binding impact on the HE conformational space. The results obtained in this analysis allowed us to define the applicability of the aforementioned methods. Moreover, our data provide a novel methodological view on the interactions within the FGF1-HE system, suggesting the bottlenecks and drawing the limitations in the applicability of the available tools for these challenging systems. This work contributes to the general understanding of protein-GAG interactions and is important to further decipher their significance for the cell signaling processes with their potential implementation in the field of regenerative medicine.