Glycosaminoglycans (GAGs) play key roles in virtually all biologic responses through their interaction with proteins. A major challenge in understanding these roles is their massive structural complexity. Computational approaches are extremely useful in navigating this bottleneck and, in some cases, the only avenue to gain comprehensive insight. We discuss the state-of-the-art on computational approaches and present a flowchart to help answer most basic, and some advanced, questions on GAG-protein interactions. For example, firstly, does my protein bind to GAGs?; secondly, where does the GAG bind?; thirdly, does my protein preferentially recognize a particular GAG type?; fourthly, what is the most optimal GAG chain length?; fifthly, what is the structure of the most favored GAG sequence?; and finally, is my GAG-protein system 'specific', 'non-specific', or a combination of both? Recent advances show the field is now poised to enable a non-computational researcher perform advanced experiments through the availability of various tools and online servers.

Chemokines, a large family of highly versatile small soluble proteins, play crucial roles in defining innate and adaptive immune responses by regulating the trafficking of leukocytes, and also play a key role in various aspects of human physiology. Chemokines share the characteristic feature of reversibly existing as monomers and dimers, and their functional response is intimately coupled to interaction with glycosaminoglycans (GAGs). Currently, nothing is known regarding the structural basis or molecular mechanisms underlying CXCL5-GAG interactions. To address this missing knowledge, we characterized the interaction of a panel of heparin oligosaccharides to CXCL5 using solution NMR, isothermal titration calorimetry, and molecular dynamics simulations. NMR studies indicated that the dimer is the high-affinity GAG binding ligand and that lysine residues from the N-loop, 40s turn, β3 strand, and C-terminal helix mediate binding. Isothermal titration calorimetry indicated a stoichiometry of two oligosaccharides per CXCL5 dimer. NMR-based structural models reveal that these residues form a contiguous surface within a monomer and, interestingly, that the GAG-binding domain overlaps with the receptor-binding domain, indicating that a GAG-bound chemokine cannot activate the receptor. Molecular dynamics simulations indicate that the roles of the individual lysines are not equivalent and that helical lysines play a more prominent role in determining binding geometry and affinity. Further, binding interactions and GAG geometry in CXCL5 are novel and distinctly different compared with the related chemokines CXCL1 and CXCL8. We conclude that a finely tuned balance between the GAG-bound dimer and free soluble monomer regulates CXCL5-mediated receptor signaling and function.

Glycosaminoglycans (GAGs) are key natural biopolymers that exhibit a range of biological functions including growth and differentiation. Despite this multiplicity of function, natural GAG sequences have not yielded drugs because of problems of heterogeneity and synthesis. Recently, several homogenous non-saccharide glycosaminoglycan mimetics (NSGMs) have been reported as agents displaying major therapeutic promise. Yet, it remains unclear whether sulfated NSGMs structurally mimic sulfated GAGs. To address this, we developed a three-step molecular dynamics (MD)-based algorithm to compare sulfated NSGMs with GAGs. In the first step of this algorithm, parameters related to the range of conformations sampled by the two highly sulfated molecules as free entities in water were compared. The second step compared identity of binding site geometries and the final step evaluated comparable dynamics and interactions in the protein-bound state. Using a test case of interactions with fibroblast growth factor-related proteins, we show that this three-step algorithm effectively predicts the GAG structure mimicking property of NSGMs. Specifically, we show that two unique dimeric NSGMs mimic hexameric GAG sequences in the protein-bound state. In contrast, closely related monomeric and trimeric NSGMs do not mimic GAG in either the free or bound states. These results correspond well with the functional properties of NSGMs. The results show for the first time that appropriately designed sulfated NSGMs can be good structural mimetics of GAGs and the incorporation of a MD-based strategy at the NSGM library screening stage can identify promising mimetics of targeted GAG sequences.

Keratinocyte-derived chemokine (KC or mCXCL1) and macrophage inflammatory protein 2 (MIP2 or mCXCL2) play nonredundant roles in trafficking blood neutrophils to sites of infection and injury. The functional responses of KC and MIP2 are intimately coupled to their interactions with glycosaminoglycans (GAGs). GAG interactions orchestrate chemokine concentration gradients and modulate receptor activity, which together regulate neutrophil trafficking. Here, using NMR, molecular dynamics (MD) simulations, and isothermal titration calorimetry (ITC), we characterized the molecular basis of KC and MIP2 binding to the GAG heparin. Both chemokines reversibly exist as monomers and dimers, and the NMR analysis indicates that the dimer binds heparin with higher affinity. The ITC experiments indicate a stoichiometry of two GAGs per KC or MIP2 dimer and that the enthalpic and entropic contributions vary significantly between the two chemokine-heparin complexes. NMR-based structural models of heparin-KC and heparin-MIP2 complexes reveal that different combinations of residues from the N-loop, 40s turn, ␤ 3-strand, and C-terminal helix form a binding surface within a monomer and that both conserved residues and residues unique to a particular chemokine mediate the binding interactions. MD simulations indicate significant residue-specific differences in their contribution to binding and affinity for a given chemokine and between chemokines. On the basis of our observations that KC and MIP2 bind to GAG via distinct molecular interactions, we propose that the differences in these GAG interactions lead to differences in neutrophil recruitment and play nonoverlapping roles in resolution of inflammation. Chemokines, a large family of small molecular weight proteins, play crucial roles in the pathophysiology of infectious and inflammatory diseases (1-3). Common to these diverse func-This work was supported by National Institutes of Health Grants P01 HL107152, R21AI124681, and S10OD023576. The authors declare that they have no conflicts of interest with the contents of this article. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This article contains Figs. S1-S3 and Movies S1 and S2.

Chemokines promote directional cell migration through binding to G-protein-coupled receptors, and as such are involved in a large array of developmental, homeostatic and pathological processes. They also interact with heparan sulfate (HS), the functional consequences of which depend on the respective location of the receptor- and the HS-binding sites, a detail that remains elusive for most chemokines. Here, to set up a biochemical framework to investigate how HS can regulate CXCL13 activity, we solved the solution structure of CXCL13. We showed that it comprises an unusually long and disordered C-terminal domain, appended to a classical chemokine-like structure. Using three independent experimental approaches, we found that it displays a unique association mode to HS, involving two clusters located in the α-helix and the C-terminal domain. Computational approaches were used to analyse the HS sequences preferentially recognized by the protein and gain atomic-level understanding of the CXCL13 dimerization induced upon HS binding. Starting with four sets of 254 HS tetrasaccharides, we identified 25 sequences that bind to CXCL13 monomer, among which a single one bound to CXCL13 dimer with high consistency. Importantly, we found that CXCL13 can be functionally presented to its receptor in a HS-bound form, suggesting that it can promote adhesion-dependent cell migration. Consistently, we designed CXCL13 mutations that preclude interaction with HS without affecting CXCR5-dependent cell signalling, opening the possibility to unambiguously demonstrate the role of HS in the biological function of this chemokine.

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Glycosaminoglycans (GAGs) represent a formidable frontier for chemists, biochemists, biologists, medicinal chemists, and drug delivery specialists because of massive structural complexity. GAGs are arguably the most complex, natural linear biopolymers with theoretical diversity orders of magnitude higher than proteins and nucleic acids. Yet, this diversity remains generally untapped. Computational approaches offer major routes to understand GAG structure and dynamics so as to enable novel applications of these biopolymers. In fact, computational algorithms, softwares, online tools, and techniques have reached a level of sophistication that help understand atomistic details of conformational variation and protein recognition of individual GAG sequences. This review describes current approaches and challenges in computational study of GAGs. It presents a history of major findings since the earliest mention of GAGs (the 1960s), the development of parameters and force fields specific for GAGs, and the application of these tools in understanding GAG structure–function relationship. This review also presents a section on how to perform simulation of GAGs, which is directed toward researchers interested in entering this promising field with potential to impact therapy. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Molecular Structures

Heparin/heparan sulfates (H/HS) are ubiquitous biopolymers that interact with many proteins to induce a range of biological functions. Unfortunately, how these biopolymers recognize their preferred protein targets remain poorly understood. It is suggested that computational simulations offer attractive avenues but a number of challenges, e.g., difficulty of selecting a comprehensive force field, few simple tools to interpret data, among others, remain. This work addresses several such challenges so as to help ease the implementation and analysis of computational experiments. First, this work presents a rigorous comparison of two different recent force fields, CHARMM36 and GLYCAM06, for H/HS studies. Second, it introduces two new straightforward parameters, i.e., end-to-end distance and minimum volume enclosing ellipsoid, to understand the myriad conformational forms of oligosaccharides that evolve over time in water. Third, it presents an application to elucidate the number and nature of inter and intramolecular, nondirect bridging water molecules, which help stabilize unique forms of H/HS. The results show that nonspecialists can use either CHARMM36 or GLYCAM06 force fields because both gave comparable results, albeit with small differences. The comparative study shows that the HS hexasaccharide samples a range of conformations with nearly equivalent energies, which could be the reason for its recognition by different proteins. Finally, analysis of the nondirect water bridges across the dynamics trajectory shows their importance in stabilization of certain conformational forms, which may become important for protein recognition. Overall, the work aids nonspecialists employ computational studies for understanding the solution behavior of H/HS.