Computational analysis of interactions in structurally available protein-glycosaminoglycan complexes

Benchmarking Water Models in Molecular Dynamics of Protein-Glycosaminoglycan Complexes

Glycosaminoglycans (GAGs) made of repeating disaccharide units intricately engage with proteins, playing a crucial role in the spatial organization of the extracellular matrix (ECM) and the transduction of biological signals in cells to modulate a number of biochemical processes. Exploring protein-GAG interactions reveals several challenges for their analysis, namely, the highly charged and periodic nature of GAGs, their multipose binding, and the abundance of the interfacial water molecules in the protein-GAG complexes. Most of the studies on protein-GAG interactions are conducted using the TIP3P water model, and there are no data on the effect of various water models on the results obtained in molecular dynamics (MD) simulations of protein-GAG complexes. Hence, it is essential to perform a systematic analysis of different water models in MD simulations for these systems. In this work, we aim to evaluate the properties of the protein-GAG complexes in MD simulations using different explicit: TIP3P, SPC/E, TIP4P, TIP4PEw, OPC, and TIP5P and implicit: IGB = 1, 2, 5, 7, and 8 water models to find out which of them are best suited to study the dynamics of protein-GAG complexes. The FF14SB and GLYCAM06 force fields were used for the proteins and GAGs, respectively. The interactions of several GAG types, such as heparin, chondroitin sulfate, and hyaluronic acid with basic fibroblast growth factor, cathepsin K, and CD44 receptor, respectively, are investigated. The observed variations in different descriptors used to study the binding in these complexes emphasize the relevance of the choice of water models for the MD simulation of these complexes.

Studying specificity in protein-glycosaminoglycan recognition with umbrella sampling

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.

Extension of the SUGRES-1P Coarse-Grained Model of Polysaccharides to Heparin

Heparin is an unbranched periodic polysaccharide composed of negatively charged monomers and involved in key biological processes, including anticoagulation, angiogenesis, and inflammation. Its structure and dynamics have been studied extensively using experimental as well as theoretical approaches. The conventional approach of computational chemistry applied to the analysis of biomolecules is all-atom molecular dynamics, which captures the interactions of individual atoms by solving Newton's equation of motion. An alternative is molecular dynamics simulations using coarse-grained models of biomacromolecules, which offer a reduction of the representation and consequently enable us to extend the time and size scale of simulations by orders of magnitude. In this work, we extend the UNIfied COarse-gRaiNed (UNICORN) model of biological macromolecules developed in our laboratory to heparin. We carried out extensive tests to estimate the optimal weights of energy terms of the effective energy function as well as the optimal Debye-Hückel screening factor for electrostatic interactions. We applied the model to study unbound heparin molecules of polymerization degree ranging from 6 to 68 residues. We compare the obtained coarse-grained heparin conformations with models obtained from X-ray diffraction studies of heparin. The SUGRES-1P force field was able to accurately predict the general shape and global characteristics of heparin molecules.

Docking and Molecular Dynamics Simulations Clarify Binding Sites for Interactions of Novel Marine Sulfated Glycans with SARS-CoV-2 Spike Glycoprotein

The entry of SARS-CoV-2 into the host cell is mediated by its S-glycoprotein (SGP). Sulfated glycans bind to the SGP receptor-binding domain (RBD), which forms a ternary complex with its receptor angiotensin converting enzyme 2. Here, we have conducted a thorough and systematic computational study of the binding of four oligosaccharide building blocks from novel marine sulfated glycans (isolated from Pentacta pygmaea and Isostichopus badionotus) to the non-glycosylated and glycosylated RBD. Blind docking studies using three docking programs identified five potential cryptic binding sites. Extensive site-targeted docking and molecular dynamics simulations using two force fields confirmed only two binding sites (Sites 1 and 5) for these novel, highly charged sulfated glycans, which were also confirmed by previously published reports. This work showed the structural features and key interactions driving ligand binding. A previous study predicted Site 2 to be a potential binding site, which was not observed here. The use of several molecular modeling approaches gave a comprehensive assessment. The detailed comparative study utilizing multiple modeling approaches is the first of its kind for novel glycan-SGP interaction characterization. This study provided insights into the key structural features of these novel glycans as they are considered for development as potential therapeutics.

In silico insights into procathepsin S maturation mediated by glycosaminoglycans

Procathepsins, inactive precursors of cathepsins are present in the extracellular matrix (ECM) and in lysosomes. Their active forms are involved in a number of biologically relevant processes, including bone resorption, intracellular proteolysis and regulation of programmed cell death. These processes might be mediated by glycosaminoglycans (GAGs), long unbranched periodic negatively charged polysaccharides. GAGs are also present in ECM and play important role in anticoagulation, angiogenesis and tissue regeneration. GAGs not only mediate the enzymatic activity of cathepsins but can also regulate the process of procathepsin maturation, as it was shown for procathepsin B and S. In this study, we propose the molecular mechanism underlying the biological role of GAGs in procathepsin S maturation and compare our findings with computational data obtained for procathepsin B. We rigorously analyse procathepsin S-GAG complexes in terms of their dynamics, free energy and potential allosteric regulation. We conclude that the GAG binding region might have an effect on the dynamics of procathepsin S structure and so affect its maturation by two different mechanisms.

Computational modeling of the molecular basis for the calcium-dependence of the mannuronan C-5 epimerase AvAlgE6 from Azotobacter vinelandii

The mannuronan C-5 epimerases catalyze epimerization of β-d-mannuronic acid to α-l-guluronic acid in alginate polymers. The seven extracellular Azotobacter vinelandii epimerases (AvAlgE1-7) are calcium-dependent, and calcium is essential for the structural integrity of their carbohydrate binding R-modules. Ca²⁺ is also found in the crystal structures of the A-modules, where it is suggested to play a structural role. In this study, the structure of the catalytic A-module of the A. vinelandii mannuronan C-5 epimerase AvAlgE6 is used to investigate the role of this Ca²⁺. Molecular dynamics (MD) simulations with and without calcium reveal the possible importance of the bound Ca²⁺ in the hydrophobic packing of β-sheets. In addition, a putative calcium binding site is found in the active site, indicating a potential direct role of this calcium in the catalysis. According to the literature, two of the residues coordinating calcium in this site are essential for the activity. MD simulations of the interaction with bound substrate indicate that the presence of a calcium ion in this binding site increases the binding strength. Further, explicit calculations of the substrate dissociation pathways with umbrella sampling simulations show and energetically higher dissociation barrier when calcium is present. The present study eludes to a putative catalytic role of calcium in the charge neutralizing first step of the enzymatic reaction. In addition to the importance for understanding these enzymes' molecular mechanisms, this could have implications for engineering strategies of the epimerases in industrial alginate processing.

Understanding Conformational Properties and Role of Hydrogen Bonds in Glycosaminoglycans-Interleukin8 Complexes in Aqueous Medium by Molecular Dynamics Simulation

Atomistic molecular dynamics simulations were performed under ambient conditions to explore the conformational features and binding affinities of hexameric glycosaminoglycans (GAGs) with chemokine Interleukin8 (IL8) in an aqueous medium. We tried to understand the role of hydrogen bonds (HBs) involving conserved water in mediating the interactions. The Luzar-Chandler model was adopted to study the kinetics of HB breaking and formation concerning different water-mediated HBs. The conformational flexibilities of bound GAGs are due to the flexible glycosidic linkages than the occasional/rare ring pucker conformation. The free energy landscape constructed with ϕ, and ψ, depicted that different conformational minima associated with the glycosidic linkage flexibility of the GAGs in bound states are separated by energy barriers. The binding affinities of IL8 towards GAGs are favored through the electrostatic and non-polar solvation interactions. 4-different types of conserved water were explored in the solvent-mediated binding of GAGs with IL8. The average lifetime of the IL8-GAG direct HB pairs was ∼ten times less than the IL8-GAG-shared water HBs. This is due to the rapid establishment of HB breaking and reformation kinetics involving water of a shared layer. We find that despite the highly negatively charged surface of GAGs, the IL8 surface populated by non-cationic amino acids could serve as a promising binding site in addition to the cationic surface of the protein.

PI3K/mTOR Dual Inhibitor Pictilisib Stably Binds to Site I of Human Serum Albumin as Observed by Computer Simulation, Multispectroscopic, and Microscopic Studies

Pictilisib (GDC-0941) is a well-known dual inhibitor of class I PI3K and mTOR and is presently undergoing phase 2 clinical trials for cancer treatment. The present work investigated the dynamic behaviors and interaction mechanism between GDC-0941 and human serum albumin (HSA). Molecular docking and MD trajectory analyses revealed that GDC-0941 bound to HSA and that the binding site was positioned in subdomain IIA at Sudlow’s site I of HSA. The fluorescence intensity of HSA was strongly quenched by GDC-0941, and results showed that the HSA–GDC-0941 interaction was a static process caused by ground-state complex formation. The association constant of the HSA–GDC-0941 complex was approximately 10⁵ M⁻¹, reflecting moderate affinity. Thermodynamic analysis conclusions were identical with MD simulation results, which revealed that van der Waals interactions were the vital forces involved in the binding process. CD, synchronous, and 3D fluorescence spectroscopic results revealed that GDC-0941 induced the structural change in HSA. Moreover, the conformational change of HSA affected its molecular sizes, as evidenced by AFM. This work provides a useful research strategy for exploring the interaction of GDC-0941 with HSA, thus helping in the understanding of the transport and delivery of dual inhibitors in the blood circulation system.

Explicit solvent repulsive scaling replica exchange molecular dynamics (RS-REMD) in molecular modeling of protein-glycosaminoglycan complexes

Glycosaminoglcyans (GAGs), linear anionic periodic polysaccharides, are crucial for many biologically relevant functions in the extracellular matrix. By interacting with proteins GAGs mediate processes such as cancer development, cell proliferation and the onset of neurodegenerative diseases. Despite this eminent importance of GAGs, they still represent a limited focus for the computational community in comparison to other classes of biomolecules. Therefore, there is a lack of modeling tools designed specifically for docking GAGs. One has to rely on existing docking software developed mostly for small drug molecules substantially differing from GAGs in their basic physico-chemical properties. In this study, we present an updated protocol for docking GAGs based on the Repulsive Scaling Replica Exchange Molecular Dynamics (RS-REMD) that includes explicit solvent description. The use of this water model improved docking performance both in terms of its accuracy and speed. This method represents a significant computational progress in GAG-related research.

Multifaceted Computational Modeling in Glycoscience

Glycoscience assembles all the scientific disciplines involved in studying various molecules and macromolecules containing carbohydrates and complex glycans. Such an ensemble involves one of the most extensive sets of molecules in quantity and occurrence since they occur in all microorganisms and higher organisms. Once the compositions and sequences of these molecules are established, the determination of their three-dimensional structural and dynamical features is a step toward understanding the molecular basis underlying their properties and functions. The range of the relevant computational methods capable of addressing such issues is anchored by the specificity of stereoelectronic effects from quantum chemistry to mesoscale modeling throughout molecular dynamics and mechanics and coarse-grained and docking calculations. The Review leads the reader through the detailed presentations of the applications of computational modeling. The illustrations cover carbohydrate-carbohydrate interactions, glycolipids, and N- and O-linked glycans, emphasizing their role in SARS-CoV-2. The presentation continues with the structure of polysaccharides in solution and solid-state and lipopolysaccharides in membranes. The full range of protein-carbohydrate interactions is presented, as exemplified by carbohydrate-active enzymes, transporters, lectins, antibodies, and glycosaminoglycan binding proteins. A final section features a list of 150 tools and databases to help address the many issues of structural glycobioinformatics.

Biglycan Interacts with Type I Insulin-like Receptor (IGF-IR) Signaling Pathway to Regulate Osteosarcoma Cell Growth and Response to Chemotherapy

Simple Summary

Osteosarcoma (OS) is an aggressive, primary bone cancer. OS cells produce altered osteoid whose components participate in signaling correlated to the development of this cancer. Biglycan (BGN), a proteoglycan, is correlated to aggressive OS type and resistance to chemotherapy. A constitutive signaling of insulin-like growth factor receptor I (IGF-IR) signaling in sarcoma progression was established. We showed that biglycan binds IGF-IR resulting in prolonged IGF-IR activation, nuclear translocation, and growth response of the poorly-differentiated MG63 cells correlated to increased aggressiveness markers expression and enhanced chemoresistance. This mechanism is not valid in moderately and well-differentiated, biglycan non-expressing U-2OS and Saos-2 OS cells.

Abstract

Osteosarcoma (OS) is a mesenchymally derived, aggressive bone cancer. OS cells produce an aberrant nonmineralized or partly mineralized extracellular matrix (ECM) whose components participate in signaling pathways connected to specific pathogenic phenotypes of this bone cancer. The expression of biglycan (BGN), a secreted small leucine-rich proteoglycan (SLRP), is correlated to aggressive OS phenotype and resistance to chemotherapy. A constitutive signaling of IGF-IR signaling input in sarcoma progression has been established. Here, we show that biglycan activates the IGF-IR signaling pathway to promote MG63 biglycan-secreting OS cell growth by forming a complex with the receptor. Computational models of IGF-IR and biglycan docking suggest that biglycan binds IGF-IR dimer via its concave surface. Our binding free energy calculations indicate the formation of a stable complex. Biglycan binding results in prolonged IGF-IR activation leading to protracted IGF-IR-dependent cell growth response of the poorly-differentiated MG63 cells. Moreover, biglycan facilitates the internalization (p ≤ 0.01, p ≤ 0.001) and sumoylation-enhanced nuclear translocation of IGF-IR (p ≤ 0.05) and its DNA binding in MG63 cells (p ≤ 0.001). The tyrosine kinase activity of the receptor mediates this mechanism. Furthermore, biglycan downregulates the expression of the tumor-suppressor gene, PTEN (p ≤ 0.01), and increases the expression of endothelial–mesenchymal transition (EMT) and aggressiveness markers vimentin (p ≤ 0.01) and fibronectin (p ≤ 0.01) in MG63 cells. Interestingly, this mechanism is not valid in moderately and well-differentiated, biglycan non-expressing U-2OS and Saos-2 OS cells. Furthermore, biglycan exhibits protective effects against the chemotherapeutic drug, doxorubicin, in MG63 OS cells (p ≤ 0.01). In conclusion, these data indicate a potential direct and adjunct therapeutical role of biglycan in osteosarcoma.

Aqueous Molecular Dynamics for Understanding Glycosaminoglycan Recognition by Proteins

Glycosaminoglycans (GAGs) are biopolymers that exist in most organisms. GAGs are known to bind to hundreds of proteins and partake in multiple biological processes such as growth, morphogenesis, inflammation, infection, and others. Their intrinsic structural heterogeneity and conformational variability introduce major challenges in experimental studies. On the other hand, recent advances in force field development and computational technology have yielded phenomenal opportunity to study thousands of GAG sequences simultaneously to understand recognition of target protein(s). Here, we describe experimental setup for conventional molecular dynamics simulations of GAGs to position an experimental biologist favorably in performance, analysis and interpretation of stability, specificity, and conformational properties of GAGs, while also elucidating their interactions with amino acid residues of a protein at an atomistic level in presence of water.

Pyranose Ring Puckering Thermodynamics for Glycan Monosaccharides Associated with Vertebrate Proteins

The conformational properties of carbohydrates can contribute to protein structure directly through covalent conjugation in the cases of glycoproteins and proteoglycans and indirectly in the case of transmembrane proteins embedded in glycolipid-containing bilayers. However, there continue to be significant challenges associated with experimental structural biology of such carbohydrate-containing systems. All-atom explicit-solvent molecular dynamics simulations provide a direct atomic resolution view of biomolecular dynamics and thermodynamics, but the accuracy of the results depends on the quality of the force field parametrization used in the simulations. A key determinant of the conformational properties of carbohydrates is ring puckering. Here, we applied extended system adaptive biasing force (eABF) all-atom explicit-solvent molecular dynamics simulations to characterize the ring puckering thermodynamics of the ten common pyranose monosaccharides found in vertebrate biology (as represented by the CHARMM carbohydrate force field). The results, along with those for idose, demonstrate that the CHARMM force field reliably models ring puckering across this diverse set of molecules, including accurately capturing the subtle balance between 4C1 and 1C4 chair conformations in the cases of iduronate and of idose. This suggests the broad applicability of the force field for accurate modeling of carbohydrate-containing vertebrate biomolecules such as glycoproteins, proteoglycans, and glycolipids.

Modeling Protein-Glycosaminoglycan Complexes: Does the Size Matter?

Docking glycosaminoglycans (GAGs) has been challenging because of the complex nature of these long periodic linear and negatively charged polysaccharides. Although standard docking tools like Autodock3 are successful when docking GAGs up to hexameric length, they experience challenges to properly dock longer GAGs. Similar limitations concern other docking approaches typically developed for docking ligands of limited size to proteins. At the same time, most of more advanced docking approaches are challenging for a user who is inexperienced with complex in silico methodologies. In this work, we evaluate the binding energies of complexes with different lengths of GAGs using all-atom molecular dynamics simulations. Based on this analysis, we propose a new docking protocol for long GAGs that consists of conventional docking of short GAGs and further elongation with the use of a coarse-grained representation of the GAG parts not being in direct contact with its protein receptor. This method automated by a simple script is straightforward to use within the Autodock3 framework but also useful in combination with other standard docking tools. We believe that this method with some minor case-specific modifications could also be used for docking other linear charged polymers.

Advanced Molecular Dynamics Approaches to Model a Tertiary Complex APRIL/TACI with Long Glycosaminoglycans

Glycosaminoglycans (GAGs) are linear anionic periodic polysaccharides participating in a number of biologically relevant processes in the extracellular matrix via interactions with their protein targets. Due to their periodicity, conformational flexibility, pseudo-symmetry of the sulfation pattern, and the key role of electrostatics, these molecules are challenging for both experimental and theoretical approaches. In particular, conventional molecular docking applied for GAGs longer than 10-mer experiences severe difficulties. In this work, for the first time, 24- and 48-meric GAGs were docked using all-atomic repulsive-scaling Hamiltonian replica exchange molecular dynamics (RS-REMD), a novel methodology based on replicas with van der Waals radii of interacting molecules being scaled. This approach performed well for proteins complexed with oligomeric GAGs and is independent of their length, which distinguishes it from other molecular docking approaches. We built a model of long GAGs in complex with a proliferation-inducing ligand (APRIL) prebound to its receptors, the B cell maturation antigen and the transmembrane activator and calcium modulator and cyclophilin ligand interactor (TACI). Furthermore, the prediction power of the RS-REMD for this tertiary complex was evaluated. We conclude that the TACI–GAG interaction could be potentially amplified by TACI’s binding to APRIL. RS-REMD outperformed Autodock3, the docking program previously proven the best for short GAGs.

Theory and Practice of Coarse-Grained Molecular Dynamics of Biologically Important Systems

Molecular dynamics with coarse-grained models is nowadays extensively used to simulate biomolecular systems at large time and size scales, compared to those accessible to all-atom molecular dynamics. In this review article, we describe the physical basis of coarse-grained molecular dynamics, the coarse-grained force fields, the equations of motion and the respective numerical integration algorithms, and selected practical applications of coarse-grained molecular dynamics. We demonstrate that the motion of coarse-grained sites is governed by the potential of mean force and the friction and stochastic forces, resulting from integrating out the secondary degrees of freedom. Consequently, Langevin dynamics is a natural means of describing the motion of a system at the coarse-grained level and the potential of mean force is the physical basis of the coarse-grained force fields. Moreover, the choice of coarse-grained variables and the fact that coarse-grained sites often do not have spherical symmetry implies a non-diagonal inertia tensor. We describe selected coarse-grained models used in molecular dynamics simulations, including the most popular MARTINI model developed by Marrink's group and the UNICORN model of biological macromolecules developed in our laboratory. We conclude by discussing examples of the application of coarse-grained molecular dynamics to study biologically important processes.

The potential role of glycosaminoglycans in serum amyloid A fibril formation by in silico approaches

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SAA dimer binds GAGs stronger than its monomer.

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Due to its net negative charge SAA prefers to bind short GAG sequences.

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GAG binding by SAA is electrostatics-driven and rather unspecific.

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GAG binding site is constituted predominantly by the N-terminal helix residues.

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GAG binding could potenitally attenuate unfolding of the N-terminal helix.

Serum amyloid A (SAA) is actively involved in such pathological processes as atherosclerosis, rheumatoid arthritis, cancer and Alzheimer's disease by its aggregation. One of the factors that can attenuate its aggregation and so affects its physiological role is its interactions with glycosminoglycans (GAGs), linear anionic periodic polysaccharides. These molecules located in the extracellular matrix of the cell are highly variable in their chemical composition and sulfation patterns. Despite the available experimental evidence of SAA-GAG interactions, no mechanistic details at atomic level have been reported for these systems so far. In our work we aimed to apply diverse computational tools to characterize SAA-GAG complexes formation and to answer questions about their potential specificity, energetic patterns, particular SAA residues involved in these interactions, favourable oligomeric state of the protein and the potential influence of GAGs on SAA aggregation. Molecular docking, conventional and replica exchange molecular dynamics approaches were applied to corroborate the experimental knowledge and to propose the corresponding molecular models. SAA-GAG complex formation was found to be electrostatics-driven and rather unspecific of a GAG sulfation pattern, more favorable for the dimer than for the monomer when binding to a short GAG oligosaccharide through its N-terminal helix, potentially contributing to the unfolding of this helix, which could lead to the promotion of the protein aggregation. The data obtained add to the specific knowledge on SAA-GAG systems and deepen the general understanding of protein-GAG interactions that is of a considerable value for the development of GAG-based approaches in a broad theurapeutic context.

Structural insights into the modulation of PDGF/PDGFR-β complexation by hyaluronan derivatives

Angiogenesis is an important physiological process playing a crucial role in wound healing and cancer progression. Vascular endothelial growth factor (VEGF) and platelet derived growth factor (PDGF) are key players in angiogenesis. Based on previous findings regarding the modulation of VEGF activity by glycosaminoglycans (GAG), here we explore the interaction of hyaluronan (HA)-based GAG with PDGF and its receptor PDGFR-β by applying molecular modeling and dynamics simulations in combination with surface plasmon resonance (SPR). Computational analysis on the interaction of oligo-hyaluronan derivatives with different sulfation pattern and functionalization shows that these GAG interact with PDGF in relevant regions for receptor recognition, and that high sulfation as well as modification with the TAMRA group convey stronger binding. On the other hand, the studied oligo-hyaluronan derivatives are predicted to scarcely recognize PDGFR-β. SPR results are in line with the computational predictions regarding the binding pattern of HA tetrasaccharide (HA4) derivatives to PDGF and PDGFR-β. Furthermore, our experimental results also show that the complexation of PDGF to PDGFR-β can be modulated by HA4 derivatives. The results found open the path for considering HA4 derivatives as potential candidates to be exploited for modulation of the PDGF/PDGFR-β signaling system in angiogenesis and related disease conditions.

A Bittersweet Computational Journey among Glycosaminoglycans

Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the “bitter” and “sweet” aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.

Investigation of the structure of regulatory proteins interacting with glycosaminoglycans by combining NMR spectroscopy and molecular modeling - the beginning of a wonderful friendship

The interaction of regulatory proteins with extracellular matrix or cell surface-anchored glycosaminoglycans (GAGs) plays important roles in molecular recognition, wound healing, growth, inflammation and many other processes. In spite of their high biological relevance, protein-GAG complexes are significantly underrepresented in structural databases because standard tools for structure determination experience difficulties in studying these complexes. Co-crystallization with subsequent X-ray analysis is hampered by the high flexibility of GAGs. NMR spectroscopy experiences difficulties related to the periodic nature of the GAGs and the sparse proton network between protein and GAG with distances that typically exceed the detection limit of nuclear Overhauser enhancement spectroscopy. In contrast, computer modeling tools have advanced over the last years delivering specific protein-GAG docking approaches successfully complemented with molecular dynamics (MD)-based analysis. Especially the combination of NMR spectroscopy in solution providing sparse structural constraints with molecular docking and MD simulations represents a useful synergy of forces to describe the structure of protein-GAG complexes. Here we review recent methodological progress in this field and bring up examples where the combination of new NMR methods along with cutting-edge modeling has yielded detailed structural information on complexes of highly relevant cytokines with GAGs.

Insights into the roles of charged residues in substrate binding and mode of action of mannuronan C-5 epimerase AlgE4

Mannuronan C-5 epimerases catalyse the epimerization of monomer residues in the polysaccharide alginate, changing the physical properties of the biopolymer. The enzymes are utilized to tailor alginate to numerous biological functions by alginate-producing organisms. The underlying molecular mechanisms that control the processive movement of the epimerase along the substrate chain is still elusive. To study this, we have used an interdisciplinary approach combining molecular dynamics simulations with experimental methods from mutant studies of AlgE4, where initial epimerase activity and product formation were addressed with NMR spectroscopy, and characteristics of enzyme-substrate interactions were obtained with isothermal titration calorimetry and optical tweezers. Positive charges lining the substrate-binding groove of AlgE4 appear to control the initial binding of poly-mannuronate, and binding also seems to be mediated by both electrostatic and hydrophobic interactions. After the catalytic reaction, negatively charged enzyme residues might facilitate dissociation of alginate from the positive residues, working like electrostatic switches, allowing the substrate to translocate in the binding groove. Molecular simulations show translocation increments of two monosaccharide units before the next productive binding event resulting in MG-block formation, with the epimerase moving with its N-terminus towards the reducing end of the alginate chain. Our results indicate that the charge pair R343-D345 might be directly involved in conformational changes of a loop that can be important for binding and dissociation. The computational and experimental approaches used in this study complement each other, allowing for a better understanding of individual residues' roles in binding and movement along the alginate chains.

Evaluation of replica exchange with repulsive scaling approach for docking glycosaminoglycans

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.

Further analyses of APRIL/APRIL-Receptor/Glycosaminoglycan interactions by biochemical assays linked to computational studies

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.

A Systems View of the Heparan Sulfate Interactome

Heparan sulfate proteoglycans consist of a small family of proteins decorated with one or more covalently attached heparan sulfate glycosaminoglycan chains. These chains have intricate structural patterns based on the position of sulfate groups and uronic acid epimers, which dictate their ability to engage a large repertoire of heparan sulfate-binding proteins, including extracellular matrix proteins, growth factors and morphogens, cytokines and chemokines, apolipoproteins and lipases, adhesion and growth factor receptors, and components of the complement and coagulation system. This review highlights recent progress in the characterization of the so-called "heparan sulfate interactome," with a major focus on systems-wide strategies as a tool for discovery and characterization of this subproteome. In addition, we compiled all heparan sulfate-binding proteins reported in the literature to date and grouped them into a few major functional classes by applying a networking approach.

Computational insights into the role of calcium ions in protein–glycosaminoglycan systems

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

GAG-DB, the New Interface of the Three-Dimensional Landscape of Glycosaminoglycans

Glycosaminoglycans (GAGs) are complex linear polysaccharides. GAG-DB is a curated database that classifies the three-dimensional features of the six mammalian GAGs (chondroitin sulfate, dermatan sulfate, heparin, heparan sulfate, hyaluronan, and keratan sulfate) and their oligosaccharides complexed with proteins. The entries are structures of GAG and GAG-protein complexes determined by X-ray single-crystal diffraction methods, X-ray fiber diffractometry, solution NMR spectroscopy, and scattering data often associated with molecular modeling. We designed the database architecture and the navigation tools to query the database with the Protein Data Bank (PDB), UniProtKB, and GlyTouCan (universal glycan repository) identifiers. Special attention was devoted to the description of the bound glycan ligands using simple graphical representation and numerical format for cross-referencing to other databases in glycoscience and functional data. GAG-DB provides detailed information on GAGs, their bound protein ligands, and features their interactions using several open access applications. Binding covers interactions between monosaccharides and protein monosaccharide units and the evaluation of quaternary structure. GAG-DB is freely available.

GlycoTorch Vina: Docking Designed and Tested for Glycosaminoglycans

Glycosaminoglycans (GAGs) are a family of anionic carbohydrates that play an essential role in the physiology and pathology of all eukaryotic life forms. Experimental determination of GAG-protein complexes is challenging due to their difficult isolation from biological sources, natural heterogeneity, and conformational flexibility-including possible ring puckering of sulfated iduronic acid from ¹C₄ to ²S_O conformation. To overcome these challenges, we present GlycoTorch Vina (GTV), a molecular docking tool based on the carbohydrate docking program VinaCarb (VC). Our program is unique in that it contains parameters to model ²S_O sugars while also supporting glycosidic linkages specific to GAGs. We discuss how crystallographic models of carbohydrates can be biased by the choice of refinement software and structural dictionaries. To overcome these variations, we carefully curated 12 of the best available GAG and GAG-like crystal structures (ranging from tetra- to octasaccharides or longer) obtained from the PDB-REDO server and refined using the same protocol. Both GTV and VC produced pose predictions with a mean root-mean-square deviation (RMSD) of 3.1 Å from the native crystal structure-a statistically significant improvement when compared to AutoDock Vina (4.5 Å) and the commercial software Glide (5.9 Å). Examples of how real-space correlation coefficients can be used to better assess the accuracy of docking pose predictions are given. Comparisons between statistical distributions of empirical "salt bridge" interactions, relevant to GAGs, were compared to density functional theory (DFT) studies of model salt bridges, and water-mediated salt bridges; however, there was generally a poor agreement between these data. Water bridges appear to play an important, yet poorly understood, role in the structures of GAG-protein complexes. To aid in the rapid prototyping of future pose scoring functions, we include a module that allows users to include their own torsional and nonbonded parameters.

The abnormal accumulation of heparan sulfate in patients with mucopolysaccharidosis prevents the elastolytic activity of cathepsin V

Mucopolysaccharidosis (MPS) are rare inherited diseases characterized by accumulation of lysosomal glycosaminoglycans, including heparan sulfate (HS). Patients exhibit progressive multi-visceral dysfunction and shortened lifespan mainly due to a severe cardiac/respiratory decline. Cathepsin V (CatV) is a potent elastolytic protease implicated in extracellular matrix (ECM) remodeling. Whether CatV is inactivated by HS in lungs from MPS patients remained unknown. Herein, CatV colocalized with HS in MPS bronchial epithelial cells. HS level correlated positively with the severity of respiratory symptoms and negatively to the overall endopeptidase activity of cysteine cathepsins. HS bound tightly to CatV and impaired its activity. Withdrawal of HS by glycosidases preserved exogenous CatV activity, while addition of Surfen, a HS antagonist, restored elastolytic CatV-like activity in MPS samples. Our data suggest that the pathophysiological accumulation of HS may be deleterious for CatV-mediated ECM remodeling and for lung tissue homeostasis, thus contributing to respiratory disorders associated to MPS diseases.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

Conformational Dynamics of Nonenveloped Circovirus Capsid to the Host Cell Receptor

Circovirus, comprising one capsid protein, is the smallest nonenveloped virus and induces lymphopenia. Circovirus can be used to explore the cell adhesion mechanism of nonenveloped viruses. We developed a single-molecule fluorescence resonance energy transfer (smFRET) assay to directly visualize the capsid's conformational feature. The capsid underwent reversible dynamic transformation between three conformations. The cell surface receptor heparan sulfate (HS) altered the dynamic equilibrium of the capsid to the high-FRET state, revealing the HS-binding region. Neutralizing antibodies restricted capsid transition to a low-FRET state, masking the HS-binding domain. The lack of positively charged amino acids in the HS-binding site reduced cell surface affinity and attenuated virus infectivity via conformational changes. These intrinsic characteristics of the capsid suggested that conformational dynamics is critical for the structural changes occurring upon cell surface receptor binding, supporting a dynamics-based mechanism of receptor binding.

GAG positioning on IL-1RI; A mechanism regulated by dual effect of glycosylation

IL-1RI is the signaling receptor for the IL-1 family of cytokines that are involved in establishment of the innate and acquired immune systems. Glycosylated extracellular (EC) domain of the IL-1RI binds to agonist such as IL-1β or antagonist ligands and the accessory protein to form the functional signaling complex. Dynamics and ligand binding of the IL-1RI is influenced by presence of the glycosaminoglycans (GAGs) of the EC matrix. Here a combination of molecular dockings and molecular dynamics simulations of the unglycosylated, partially N-glycosylated and fully N-glycosylated IL-1RI EC domain in the apo, GAG-bound and IL-1β-bound states were carried out to explain the co-occurring dynamical effect of receptor's glycosylation and GAGs. It was shown that the IL-1RI adopts two types of "extended" and "locked" conformations in its dynamical pattern, and glycosylation maintains the receptor in the latter form. Maintaining the receptor in the locked conformation disfavors IL-1β binding by burying its two binding site on the IL-1RI EC domain. Glycosylation disfavors GAG binding to the extended IL-1RI EC domain by sterically limiting the GAGs degrees of freedom in targeting its binding site, while it favors GAG binding to the locked IL-1RI by favorable packing interactions.

Role of Glycosaminoglycans in Procathepsin B Maturation: Molecular Mechanism Elucidated by a Computational Study

Procathepsins are an inactive, immature form of cathepsins, predominantly cysteine proteases present in the extracellular matrix (ECM) and in lysosomes that play a key role in various biological processes such as bone resorption or intracellular proteolysis. The enzymatic activity of cathepsins can be mediated by glycosaminoglycans (GAGs), long unbranched periodic negatively charged polysaccharides found in ECM that take part in many biological processes such as anticoagulation, angiogenesis, and tissue regeneration. In addition to the known effects on mature cathepsins, GAGs can mediate the maturation process of procathepsins, in particular, procathepsin B. However, the detailed mechanism of this mediation at the molecular level is still unknown. In this study, for the first time, we aimed to unravel the role of GAGs in this process using computational approaches. We rigorously analyzed procathepsin B–GAG complexes in terms of their dynamics, energetics, and potential allosteric regulation. We revealed that GAGs can stabilize the conformation of the procathepsin B structure with the active site accessible for the substrate and concluded that GAGs most probably bind to procathepsin B once the zymogen adopts the enzymatically active conformation. Our data provided a novel mechanistic view of the maturation process of procathepsin B, while the approaches elaborated here might be useful to study other procathepsins. Furthermore, our data can serve as a rational guide for experimental work on procathepsin–GAG systems that are not characterized in vivo and in vitro yet.

The current structural glycome landscape and emerging technologies

Carbohydrates represent one of the building blocks of life, along with nucleic acids, proteins and lipids. Although glycans are involved in a wide range of processes from embryogenesis to protein trafficking and pathogen infection, we are still a long way from deciphering the glycocode. In this review, we aim to present a few of the challenges that researchers working in the area of glycobiology can encounter and what strategies can be utilised to overcome them. Our goal is to paint a comprehensive picture of the current saccharide landscape available in the Protein Data Bank (PDB). We also review recently updated repositories relevant to the topic proposed, the impact of software development on strategies to structurally solve carbohydrate moieties, and state-of-the-art molecular and cellular biology methods that can shed some light on the function and structure of glycans.

Sulfated Non-Saccharide Glycosaminoglycan Mimetics as Novel Drug Discovery Platform for Various Pathologies

Glycosaminoglycans (GAGs) are very complex, natural anionic polysaccharides. They are polymers of repeating disaccharide units of uronic acid and hexosamine residues. Owing to their template-free, spatiotemporally-controlled, and enzyme-mediated biosyntheses, GAGs possess enormous polydispersity, heterogeneity, and structural diversity which often translate into multiple biological roles. It is well documented that GAGs contribute to physiological and pathological processes by binding to proteins including serine proteases, serpins, chemokines, growth factors, and microbial proteins. Despite advances in the GAG field, the GAG-protein interface remains largely unexploited by drug discovery programs. Thus, Non-Saccharide Glycosaminoglycan Mimetics (NSGMs) have been rationally developed as a novel class of sulfated molecules that modulate GAG-protein interface to promote various biological outcomes of substantial benefit to human health. In this review, we describe the chemical, biochemical, and pharmacological aspects of recently reported NSGMs and highlight their therapeutic potentials as structurally and mechanistically novel anti-coagulants, anti-cancer agents, anti-emphysema agents, and anti-viral agents. We also describe the challenges that complicate their advancement and describe ongoing efforts to overcome these challenges with the aim of advancing the novel platform of NSGMs to clinical use.

Meglumine acridone acetate, the ionic salt of CMA and N-methylglucamine, induces apoptosis in human PBMCs via the mitochondrial pathway

Meglumine acridone acetate (MA) is used in Russia for the treatment of influenza and other acute respiratory viral infections. It was assumed, until recently, that its antiviral effect was associated with its potential ability to induce type I interferon. Advanced studies, however, have shown the failure of 10-carboxymethyl-9-acridanone (CMA) to activate human STING. As such, MA’s antiviral properties are still undergoing clarification. To gain insight into MA’s mechanisms of action, we carried out RNA-sequencing analysis of global transcriptomes in MA-treated (MA+) human peripheral blood mononuclear cells (PBMCs). In response to treatment, approximately 1,223 genes were found to be differentially expressed, among which 464 and 759 were identified as either up- or down-regulated, respectively. To clarify the cellular and molecular processes taking place in MA+ cells, we performed a functional analysis of those genes. We have shown that evident MA subcellular localizations are: at the nuclear envelope; inside the nucleus; and diffusely in perinuclear cytoplasm. Postulating that MA may be a nuclear receptor agonist, we carried out docking simulations with PPARα and RORα ligand binding domains including prediction and molecular dynamics-based analysis of potential MA binding poses. Finally, we confirmed that MA treatment enhanced nuclear apoptosis in human PBMCs. The research presented here, in our view, indicates that: (i) MA activity is mediated by nuclear receptors; (ii) MA is a possible PPARα and/or RORα agonist; (iii) MA has an immunosuppressive effect; and (iv) MA induces apoptosis through the mitochondrial signaling pathway.

Analysis of Procollagen C-Proteinase Enhancer-1/Glycosaminoglycan Binding Sites and of the Potential Role of Calcium Ions in the Interaction

In this study, we characterize the interactions between the extracellular matrix protein, procollagen C-proteinase enhancer-1 (PCPE-1), and glycosaminoglycans (GAGs), which are linear anionic periodic polysaccharides. We applied molecular modeling approaches to build a structural model of full-length PCPE-1, which is not experimentally available, to predict GAG binding poses for various GAG lengths, types and sulfation patterns, and to determine the effect of calcium ions on the binding. The computational data are analyzed and discussed in the context of the experimental results previously obtained using surface plasmon resonance binding assays. We also provide experimental data on PCPE-1/GAG interactions obtained using inhibition assays with GAG oligosaccharides ranging from disaccharides to octadecasaccharides. Our results predict the localization of GAG-binding sites at the amino acid residue level onto PCPE-1 and is the first attempt to describe the effects of ions on protein-GAG binding using modeling approaches. In addition, this study allows us to get deeper insights into the in silico methodology challenges and limitations when applied to GAG-protein interactions.

NMR and molecular modeling reveal specificity of the interactions between CXCL14 and glycosaminoglycans

CXCL14, chemokine (C-X-C motif) ligand 14, is a novel highly conserved chemokine with unique features. Despite exhibiting the typical chemokine fold, it has a very short N-terminus of just two amino acid residues responsible for chemokine receptor activation. CXCL14 actively participates in homeostatic immune surveillance of skin and mucosae, is linked to metabolic disorders and fibrotic lung diseases and possesses strong anti-angiogenic properties in early tumor development. In this work, we investigated the interaction of CXCL14 with various glycosaminoglycans (GAGs) by nuclear magnetic resonance spectroscopy, microscale thermophoresis, analytical heparin (HE) affinity chromatography and in silico approaches to understand the molecular basis of GAG-binding. We observed different GAG-binding modes specific for the GAG type used in the study. In particular, the CXCL14 epitope for HE suggests a binding pose distinguishable from the ones of the other GAGs investigated (hyaluronic acid, chondroitin sulfate-A/C, −D, dermatan sulfate). This observation is also supported by computational methods that included molecular docking, molecular dynamics and free energy calculations. Based on our results, we suggest that distinct GAG sulfation patterns confer specificity beyond simple electrostatic interactions usually considered to represent the driving forces in protein–GAG interactions. The CXCL14–GAG system represents a promising approach to investigate the specificity of GAG–protein interactions, which represents an important topic for developing the rational approaches to novel strategies in regenerative medicine.

Docking software performance in protein-glycosaminoglycan systems

We present a benchmarking study for protein-glycosaminoglycan systems with eight docking programs: Dock, rDock, ClusPro, PLANTS, HADDOCK, Hex, SwissDock and ATTRACT. We used a non-redundant representative dataset of 28 protein-glycosaminoglycan complexes with experimentally available structures, where a glycosaminoglycan ligand was longer than a trimer. Overall, the ligand binding poses could be correctly predicted in many cases by the tested docking programs, however the ranks of the docking poses are often poorly assigned. Our results suggest that Dock program performs best in terms of the pose placement, has the most suitable scoring function, and its performance did not depend on the ligand size. This suggests that the implementation of the electrostatics as well as the shape complementarity procedure in Dock are the most suitable for docking glycosaminoglycan ligands. We also analyzed how free energy patterns of the benchmarking complexes affect the performance of the evaluated docking software.

Modeling large protein-glycosaminoglycan complexes using a fragment-based approach

Glycosaminoglycans (GAGs), a major constituent of the extracellular matrix, participate in cell-signaling by binding specific proteins. Structural data on protein-GAG interactions are crucial to understand and modulate these signaling processes, with potential applications in regenerative medicine. However, experimental and theoretical approaches used to study GAG-protein systems are challenged by GAGs high flexibility limiting the conformational sampling above a certain size, and by the scarcity of GAG-specific docking tools compared to protein-protein or protein-drug docking approaches. We present for the first time an automated fragment-based method for docking GAGs on a protein binding site. In this approach, trimeric GAG fragments are flexibly docked to the protein, assembled based on their spacial overlap, and refined by molecular dynamics. The method appeared more successful than the classical full-ligand approach for most of 13 tested complexes with known structure. The approach is particularly promising for docking of long GAG chains, which represents a bottleneck for classical docking approaches applied to these systems. © 2019 Wiley Periodicals, Inc.

Protein-Ligand Interaction Energy-Based Entropy Calculations: Fundamental Challenges For Flexible Systems

Entropy calculations represent one of the most challenging steps in obtaining the binding free energy in biomolecular systems. A novel computationally effective approach (IE) was recently proposed to calculate the entropy based on the computation of protein-ligand interaction energy directly from molecular dynamics (MD) simulations. We present a study focused on the application of this method to flexible molecular systems and compare its performance with well-established normal mode (NM) and quasiharmonic (QH) entropy calculation approaches. Our results demonstrated that the IE method is intended for calculating entropy change for binding partners in fixed conformations, as by the original definition of IE, and is not applicable to the molecular complexes in which the interacting partners undergo significant conformational changes during the binding process.

Insights into the structure and dynamics of lysyl oxidase propeptide, a flexible protein with numerous partners

Lysyl oxidase (LOX) catalyzes the oxidative deamination of lysine and hydroxylysine residues in collagens and elastin, which is the first step of the cross-linking of these extracellular matrix proteins. It is secreted as a proenzyme activated by bone morphogenetic protein-1, which releases the LOX catalytic domain and its bioactive N-terminal propeptide. We characterized the recombinant human propeptide by circular dichroism, dynamic light scattering, and small-angle X-ray scattering (SAXS), and showed that it is elongated, monomeric, disordered and flexible (D_max: 11.7 nm, R_g: 3.7 nm). We generated 3D models of the propeptide by coarse-grained molecular dynamics simulations restrained by SAXS data, which were used for docking experiments. Furthermore, we have identified 17 new binding partners of the propeptide by label-free assays. They include four glycosaminoglycans (hyaluronan, chondroitin, dermatan and heparan sulfate), collagen I, cross-linking and proteolytic enzymes (lysyl oxidase-like 2, transglutaminase-2, matrix metalloproteinase-2), a proteoglycan (fibromodulin), one growth factor (Epidermal Growth Factor, EGF), and one membrane protein (tumor endothelial marker-8). This suggests new roles for the propeptide in EGF signaling pathway.

So you think computational approaches to understanding glycosaminoglycan-protein interactions are too dry and too rigid? Think again!

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.