Proteoglycans and their heterogeneous glycosaminoglycans at the atomic scale

Coarse-Grained Model of Glycosaminoglycans for Biomolecular Simulations

Proteoglycans contain glycosaminoglycans (GAGs) which are negatively charged linear polymers made of repeating disaccharide units of uronic acid and hexosamine units. They play vital roles in numerous physiological and pathological processes, particularly in governing cellular communication and attachment. Depending on their sulfonation state, acetylation, and glycosidic linkages, GAGs belong to different families. The high molecular weight, heterogeneity, and flexibility of GAGs hamper their characterization at atomic resolution, but this may be circumvented via coarse-grained (CG) approaches. In this work, we report a CG model for a library of common GAG types in their isolated or proteoglycan-linked states compatible with version 2.2 (v2.2) of the widely popular CG Martini force field. The model reproduces conformational and thermodynamic properties for a wide variety of GAGs, as well as matching structural and binding data for selected proteoglycan test systems. The parameters developed here may thus be employed to study a range of GAG-containing biomolecular systems, thereby benefiting from the efficiency and broad applicability of the Martini framework.

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.

Chemoenzymatic synthesis of sulfur-linked sugar polymers as heparanase inhibitors

Complex carbohydrates (glycans) are major players in all organisms due to their structural, energy, and communication roles. This last essential role involves interacting and/or signaling through a plethora of glycan-binding proteins. The design and synthesis of glycans as potential drug candidates that selectively alter or perturb metabolic processes is challenging. Here we describe the first reported sulfur-linked polysaccharides with potentially altered conformational state(s) that are recalcitrant to digestion by heparanase, an enzyme important in human health and disease. An artificial sugar donor with a sulfhydryl functionality is synthesized and enzymatically incorporated into polysaccharide chains utilizing heparosan synthase. Used alone, this donor adds a single thio-sugar onto the termini of nascent chains. Surprisingly, in chain co-polymerization reactions with a second donor, this thiol-terminated heparosan also serves as an acceptor to form an unnatural thio-glycosidic bond ('S-link') between sugar residues in place of a natural 'O-linked' bond. S-linked heparan sulfate analogs are not cleaved by human heparanase. Furthermore, the analogs act as competitive inhibitors with > ~200-fold higher potency than expected; as a rationale, molecular dynamic simulations suggest that the S-link polymer conformations mimic aspects of the transition state. Our analogs form the basis for future cancer therapeutics and modulators of protein/sugar interactions.

Atomic-Resolution Experimental Structural Biology and Molecular Dynamics Simulations of Hyaluronan and Its Complexes

This review summarizes the atomic-resolution structural biology of hyaluronan and its complexes available in the Protein Data Bank, as well as published studies of atomic-resolution explicit-solvent molecular dynamics simulations on these and other hyaluronan and hyaluronan-containing systems. Advances in accurate molecular mechanics force fields, simulation methods and software, and computer hardware have supported a recent flourish in such simulations, such that the simulation publications now outnumber the structural biology publications by an order of magnitude. In addition to supplementing the experimental structural biology with computed dynamic and thermodynamic information, the molecular dynamics studies provide a wealth of atomic-resolution information on hyaluronan-containing systems for which there is no atomic-resolution structural biology either available or possible. Examples of these summarized in this review include hyaluronan pairing with other hyaluronan molecules and glycosaminoglycans, with ions, with proteins and peptides, with lipids, and with drugs and drug-like molecules. Despite limitations imposed by present-day computing resources on system size and simulation timescale, atomic-resolution explicit-solvent molecular dynamics simulations have been able to contribute significant insight into hyaluronan's flexibility and capacity for intra- and intermolecular non-covalent interactions.

3-O-Sulfation induces sequence-specific compact topologies in heparan sulfate that encode a dynamic sulfation code

Heparan sulfate (HS) is arguably the most diverse linear biopolymer that is known to modulate hundreds of proteins. Whereas the configurational and conformational diversity of HS is well established in terms of varying sulfation patterns and iduronic acid (IdoA) puckers, a linear helical topology resembling a cylindrical rod is the only topology thought to be occupied by the biopolymer. We reasoned that 3-O-sulfation, a rare modification in natural HS, may induce novel topologies that contribute to selective recognition of proteins. In this work, we studied a library of 24 distinct HS hexasaccharides using molecular dynamics (MD). We discovered novel compact (C) topologies that are populated significantly by a unique group of 3-O-sulfated sequences containing IdoA residues. 3-O-sulfated sequences containing glucuronic acid (GlcA) residue and sequences devoid of 3-O-sulfate groups did not exhibit high levels of the C topology and primarily exhibited only the canonical linear (L) form. The C topology arises under dynamical conditions due to rotation around an IdoA → GlcN glycosidic linkage, especially in psi (Ψ) torsion. At an atomistic level, the L → C transformation is a multi-factorial phenomenon engineered to reduce like-charge repulsion, release one or more HS-bound water molecules, and organize a bi-dentate "IdoA-cation-IdoA" interaction. These forces also drive an L → C transformation in a 3-O-sulfated octasaccharide, which has shown evidence of the unique C topology in the co-crystallized state. The 3-O-sulfate-based generation of unique, sequence-specific, compact topologies indicate that natural HS encodes a dynamic sulfation code that could be exploited for selective recognition of target proteins.

Impact of calcium ions on the structural and dynamic properties of heparin oligosaccharides by computational analysis

Heparin (HP) belongs to glycosaminoglycans (GAGs), anionic linear polysaccharides composed of repetitive disaccharide units. They are key players in many biological processes occurring in the extracellular matrix and at the cell surface. GAGs are challenging molecules for computational research due to their high chemical heterogeneity, flexibility, periodicity, pseudosymmetry, predominantly electrostatics-driven nature of interactions with their protein partners and potential multipose binding. The molecular mechanisms underlying GAG interactions mediated by divalent ions, which are important for GAG binding to several proteins, are not well understood. The goal of this study was to characterize the binding of Ca²⁺ to two HP oligosaccharides of different lengths (dp10 and dp18, dp: degree of polymerization) and their impact on HP conformational space and their dynamic behavior with the use of molecular dynamics (MD)-based approaches with two Ca²⁺ parameter sets. MD data suggested that the flexibility of the monosaccharides, the glycosidic linkages and ring puckering were not affected by the presence of Ca²⁺, in contrast to H-bond propensities and the calculated R_g for a fraction of the oligosaccharide populations in both dp10 and dp18. Moreover, the essential differences in the data obtained by using two Ca²⁺ parameter sets were reported.

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.

In-Depth Molecular Dynamics Study of All Possible Chondroitin Sulfate Disaccharides Reveals Key Insight into Structural Heterogeneity and Dynamism

GAGs exhibit a high level of conformational and configurational diversity, which remains untapped in terms of the recognition and modulation of proteins. Although GAGs are suggested to bind to more than 800 biologically important proteins, very few therapeutics have been designed or discovered so far. A key challenge is the inability to identify, understand and predict distinct topologies accessed by GAGs, which may help design novel protein-binding GAG sequences. Recent studies on chondroitin sulfate (CS), a key member of the GAG family, pinpointing its role in multiple biological functions led us to study the conformational dynamism of CS building blocks using molecular dynamics (MD). In the present study, we used the all-atom GLYCAM06 force field for the first time to explore the conformational space of all possible CS building blocks. Each of the 16 disaccharides was solvated in a TIP3P water box with an appropriate number of counter ions followed by equilibration and a production run. We analyzed the MD trajectories for torsional space, inter- and intra-molecular H-bonding, bridging water, conformational spread and energy landscapes. An in-house phi and psi probability density analysis showed that 1→3-linked sequences were more flexible than 1→4-linked sequences. More specifically, phi and psi regions for 1→4-linked sequences were held within a narrower range because of intra-molecular H-bonding between the GalNAc O5 atom and GlcA O3 atom, irrespective of sulfation pattern. In contrast, no such intra-molecular interaction arose for 1→3-linked sequences. Further, the stability of 1→4-linked sequences also arose from inter-molecular interactions involving bridged water molecules. The energy landscape for both classes of CS disaccharides demonstrated increased ruggedness as the level of sulfation increased. The results show that CS building blocks present distinct conformational dynamism that offers the high possibility of unique electrostatic surfaces for protein recognition. The fundamental results presented here will support the development of algorithms that help to design longer CS chains for protein recognition.

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.

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.

Sulfation and Calcium Favor Compact Conformations of Chondroitin in Aqueous Solutions

The effects of sulfation and calcium cations (Ca²⁺) on the atomic-resolution conformational properties of chondroitin carbohydrate polymers in aqueous solutions are not well studied owing to experimental challenges. Here, we compare all-atom explicit-solvent molecular dynamics simulations results for pairs of O-type (nonsulfated) and A-type (GlcNAc 4-O-sulfated) chondroitin 20-mers in 140 mM NaCl with and without Ca²⁺ and find that both sulfation and Ca²⁺ favor more compact polymer conformations. We also show that subtle differences in force-field parametrization can have dramatic effects on Ca²⁺ binding to chondroitin carboxylate and sulfate functional groups and thereby determine Ca²⁺-mediated intra- and interstrand association. In addition to providing an atomic-resolution picture of the interaction of Ca²⁺ with sulfated and nonsulfated chondroitin polymers, the molecular dynamics data emphasize the importance of careful force-field parametrization to balance ion-water and ion-chondroitin interactions and suggest additional parametrization efforts to tune interactions involving sulfate.

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.

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.

Constructing 3-Dimensional Atomic-Resolution Models of Nonsulfated Glycosaminoglycans with Arbitrary Lengths Using Conformations from Molecular Dynamics

Glycosaminoglycans (GAGs) are the linear carbohydrate components of proteoglycans (PGs) and are key mediators in the bioactivity of PGs in animal tissue. GAGs are heterogeneous, conformationally complex, and polydisperse, containing up to 200 monosaccharide units. These complexities make studying GAG conformation a challenge for existing experimental and computational methods. We previously described an algorithm we developed that applies conformational parameters (i.e., all bond lengths, bond angles, and dihedral angles) from molecular dynamics (MD) simulations of nonsulfated chondroitin GAG 20-mers to construct 3-D atomic-resolution models of nonsulfated chondroitin GAGs of arbitrary length. In the current study, we applied our algorithm to other GAGs, including hyaluronan and nonsulfated forms of dermatan, keratan, and heparan and expanded our database of MD-generated GAG conformations. Here, we show that individual glycosidic linkages and monosaccharide rings in 10- and 20-mers of hyaluronan and nonsulfated dermatan, keratan, and heparan behave randomly and independently in MD simulation and, therefore, using a database of MD-generated 20-mer conformations, that our algorithm can construct conformational ensembles of 10- and 20-mers of various GAG types that accurately represent the backbone flexibility seen in MD simulations. Furthermore, our algorithm efficiently constructs conformational ensembles of GAG 200-mers that we would reasonably expect from MD simulations.

Glycosaminoglycan-Protein Interactions: The First Draft of the Glycosaminoglycan Interactome

The six mammalian glycosaminoglycans (GAGs), chondroitin sulfate, dermatan sulfate, heparin, heparan sulfate, hyaluronan, and keratan sulfate, are linear polysaccharides. Except for hyaluronan, they are sulfated to various extent, and covalently attached to proteins to form proteoglycans. GAGs interact with growth factors, morphogens, chemokines, extracellular matrix proteins and their bioactive fragments, receptors, lipoproteins, and pathogens. These interactions mediate their functions, from embryonic development to extracellular matrix assembly and regulation of cell signaling in various physiological and pathological contexts such as angiogenesis, cancer, neurodegenerative diseases, and infections. We give an overview of GAG-protein interactions (i.e., specificity and chemical features of GAG- and protein-binding sequences), and review the available GAG-protein interaction networks. We also provide the first comprehensive draft of the GAG interactome composed of 832 biomolecules (827 proteins and five GAGs) and 932 protein-GAG interactions. This network is a scaffold, which in the future should integrate structures of GAG-protein complexes, quantitative data of the abundance of GAGs in tissues to build tissue-specific interactomes, and GAG interactions with metal ions such as calcium, which plays a major role in the assembly of the extracellular matrix and its interactions with cells. This contextualized interactome will be useful to identify druggable GAG-protein interactions for therapeutic purpose.

Extending the Martini Coarse-Grained Force Field to N-Glycans

Glycans play a vital role in a large number of cellular processes. Their complex and flexible nature hampers structure-function studies using experimental techniques. Molecular dynamics (MD) simulations can help in understanding dynamic aspects of glycans if the force field parameters used can reproduce key experimentally observed properties. Here, we present optimized coarse-grained (CG) Martini force field parameters for N-glycans, calibrated against experimentally derived binding affinities for lectins. The CG bonded parameters were obtained from atomistic (ATM) simulations for different glycan topologies including high mannose and complex glycans with various branching patterns. In the CG model, additional elastic networks are shown to improve maintenance of the overall conformational distribution. Solvation free energies and octanol-water partition coefficients were also calculated for various N-glycan disaccharide combinations. When using standard Martini nonbonded parameters, we observed that glycans spontaneously aggregated in the solution and required down-scaling of their interactions for reproduction of ATM model radial distribution functions. We also optimized the nonbonded interactions for glycans interacting with seven lectin candidates and show that a relatively modest scaling down of the glycan-protein interactions can reproduce free energies obtained from experimental studies. These parameters should be of use in studying the role of glycans in various glycoproteins and carbohydrate binding proteins as well as their complexes, while benefiting from the efficiency of CG sampling.

Efficient Construction of Atomic-Resolution Models of Non-Sulfated Chondroitin Glycosaminoglycan Using Molecular Dynamics Data

Glycosaminoglycans (GAGs) are linear, structurally diverse, conformationally complex carbohydrate polymers that may contain up to 200 monosaccharides. These characteristics present a challenge for studying GAG conformational thermodynamics at atomic resolution using existing experimental methods. Molecular dynamics (MD) simulations can overcome this challenge but are only feasible for short GAG polymers. To address this problem, we developed an algorithm that applies all conformational parameters contributing to GAG backbone flexibility (i.e., bond lengths, bond angles, and dihedral angles) from unbiased all-atom explicit-solvent MD simulations of short GAG polymers to rapidly construct models of GAGs of arbitrary length. The algorithm was used to generate non-sulfated chondroitin 10- and 20-mer ensembles which were compared to MD-generated ensembles for internal validation. End-to-end distance distributions in constructed and MD-generated ensembles have minimal differences, suggesting that our algorithm produces conformational ensembles that mimic the backbone flexibility seen in simulation. Non-sulfated chondroitin 100- and 200-mer ensembles were constructed within a day, demonstrating the efficiency of the algorithm and reduction in time and computational cost compared to simulation.

Perspective on computational simulations of glycosaminoglycans

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.

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.

Glycosaminoglycans in extracellular matrix organisation: are concepts from soft matter physics key to understanding the formation of perineuronal nets?

Conventional wisdom has it that proteins fold and assemble into definite structures, and that this defines their function. Glycosaminoglycans (GAGs) are different. In most cases the structures they form have a low degree of order, even when interacting with proteins. Here, we discuss how physical features common to all GAGs-hydrophilicity, charge, linearity and semi-flexibility-underpin the overall properties of GAG-rich matrices. By integrating soft matter physics concepts (e.g. polymer brushes and phase separation) with our molecular understanding of GAG-protein interactions, we can better comprehend how GAG-rich matrices assemble, what their properties are, and how they function. Taking perineuronal nets (PNNs)-a GAG-rich matrix enveloping neurons-as a relevant example, we propose that microphase separation determines the holey PNN anatomy that is pivotal to PNN functions.

Multiscale modeling of glycosaminoglycan structure and dynamics: current methods and challenges

Glycosaminoglycans are long unbranched and complex polysaccharides that are an essential component of mammalian extracellular matrices. Characterization of their molecular structure, dynamics and interactions are essential to understand important biological phenomena in health and disease, and will lead to novel therapeutics and medical devices. However, this has proven to be a challenge experimentally and theoretical techniques are needed to develop new hypotheses, and interpret experiments. This review aims to examine the current theoretical (rather than experimental) methods used by researchers to investigate glycosaminoglycan structure, dynamics and interactions, from the monosaccharide to the macromolecular scale. It will consider techniques such as quantum mechanics, molecular mechanics, molecular dynamics, coarse graining and docking.

Computational drill down on FGF1-heparin interactions through methodological evaluation

Glycosaminoglycans (GAGs) exhibit a key role in cellular communication processes through interactions with target proteins of the extracellular matrix (ECM). The sandwich-like interaction established between Fibroblast growth factor (FGF) and heparin (HE) represents quite a peculiar protein-GAG-protein system, which has been both structurally and functionally intensively studied. The molecular recognition characteristics of this system have been exploited in various computational studies in order to deepen understanding of GAG-protein interactions. Here, we drill down on the interactions established in this peculiar macromolecular complex by analyzing the applicability of docking techniques and molecular dynamics (MD)-based approaches, and we dissect the molecular recognition properties exhibited by FGF towards a series of HE derivatives. We examine the sensitivity of MM-GBSA free energy calculations in terms of receptor conformational space sampling and changes in the ligand structures. Furthermore, we investigate its predictive power in combination with other computational methods, namely the well-established Autodock3 (AD3) and dynamic molecular docking (DMD), a targeted MD-based docking method specifically developed to account for flexibility and solvent in computer simulations of protein-GAG systems. Our results show that a site-mapping approach can be effectively combined with AD3 and DMD calculations to accurately reproduce available experimental data and, furthermore, to determine specific GAG recognition patterns. This study deepens our understanding of the applicability of available theoretical approaches to the investigation of molecular recognition in protein-GAG systems.

Rigidity and flexibility in the tetrasaccharide linker of proteoglycans from atomic-resolution molecular simulation

Proteoglycans (PGs) are covalent conjugates between protein and carbohydrate (glycosaminoglycans). Certain classes of glycosaminoglycans such as chondroitin sulfate/dermatan sulfate and heparan sulfate utilize a specific tetrasaccharide linker for attachment to the protein component: GlcAβ1-3Galβ1-3Galβ1-4Xylβ1-O-Ser. Toward understanding the conformational preferences of this linker, the present work used all-atom explicit-solvent molecular dynamics (MD) simulations combined with Adaptive Biasing Force (ABF) sampling to determine high-resolution, high-precision conformational free energy maps ΔG(φ, ψ) for each glycosidic linkage between constituent disaccharides, including the variant where GlcA is substituted with IdoA. These linkages are characterized by single, predominant (> 97% occupancy), and broad (45° × 60° for ΔG(φ, ψ) < 1 kcal/mol) free-energy minima, while the Xyl-Ser linkage has two such minima similar in free-energy, and additional flexibility from the Ser sidechain dihedral. Conformational analysis of microsecond-scale standard MD on the complete tetrasaccharide-O-Ser conjugate is consistent with ABF data, suggesting (φ, ψ) probabilities are independent of the linker context, and that the tetrasaccharide acts as a relatively rigid unit whereas significant conformational heterogeneity exists with respect to rotation about bonds connecting Xyl to Ser. © 2017 Wiley Periodicals, Inc.

Chondroitinase C Selectively Degrades Chondroitin Sulfate Glycosaminoglycans that Inhibit Axonal Growth within the Endoneurium of Peripheral Nerve

The success of peripheral nerve regeneration is highly dependent on the regrowth of axons within the endoneurial basal lamina tubes that promote target-oriented pathfinding and appropriate reinnervation. Restoration of nerve continuity at this structural level after nerve transection injury by direct repair and nerve grafting remains a major surgical challenge. Recently, biological approaches that alter the balance of growth inhibitors and promoters in nerve have shown promise to improve appropriate axonal regeneration and recovery of peripheral nerve function. Chondroitin sulfate proteoglycans (CSPGs) are known inhibitors of axonal growth. This growth inhibition is mainly associated with a CSPG's glycosaminoglycan chains. Enzymatic degradation of these chains with chondroitinase eliminates this inhibitory activity and, when applied in vivo, can improve the outcome of nerve repair. To date, these encouraging findings were obtained with chondroitinase ABC (a pan-specific chondroitinase). The aim of this study was to examine the distribution of CSPG subtypes in rodent, rabbit, and human peripheral nerve and to test more selective biological enzymatic approaches to improve appropriate axonal growth within the endoneurium and minimize aberrant growth. Here we provide evidence that the endoneurium, but not the surrounding epineurium, is rich in CSPGs that have glycosaminoglycan chains readily degraded by chondroitinase C. Biochemical studies indicate that chondroitinase C has degradation specificity for 6-sulfated glycosaminoglycans found in peripheral nerve. We found that chondroitinase C degrades and inactivates inhibitory CSPGs within the endoneurium but not so much in the surrounding nerve compartments. Cryoculture bioassays (neurons grown on tissue sections) show that chondroitinase C selectively and significantly enhanced neuritic growth associated with the endoneurial basal laminae without changing growth-inhibiting properties of the surrounding epineurium. Interestingly, chondroitinase ABC treatment increased greatly the growth-promoting properties of the epineurial tissue whereas chondroitinase C had little effect. Our evidence indicates that chondroitinase C effectively degrades and inactivates inhibitory CSPGs present in the endoneurial Schwann cell basal lamina and does so more specifically than chondroitinase ABC. These findings are discussed in the context of improving nerve repair and regeneration and the growth-promoting properties of processed nerve allografts.

Role of Chondroitin Sulfate (CS) Modification in the Regulation of Protein-tyrosine Phosphatase Receptor Type Z (PTPRZ) Activity: PLEIOTROPHIN-PTPRZ-A SIGNALING IS INVOLVED IN OLIGODENDROCYTE DIFFERENTIATION

Protein-tyrosine phosphatase receptor type Z (PTPRZ) is predominantly expressed in the developing brain as a CS proteoglycan. PTPRZ has long (PTPRZ-A) and short type (PTPRZ-B) receptor forms by alternative splicing. The extracellular CS moiety of PTPRZ is required for high-affinity binding to inhibitory ligands, such as pleiotrophin (PTN), midkine, and interleukin-34; however, its functional significance in regulating PTPRZ activity remains obscure. We herein found that protein expression of CS-modified PTPRZ-A began earlier, peaking at approximately postnatal days 5-10 (P5-P10), and then that of PTN peaked at P10 at the developmental stage corresponding to myelination onset in the mouse brain. Ptn-deficient mice consistently showed a later onset of the expression of myelin basic protein, a major component of the myelin sheath, than wild-type mice. Upon ligand application, PTPRZ-A/B in cultured oligodendrocyte precursor cells exhibited punctate localization on the cell surface instead of diffuse distribution, causing the inactivation of PTPRZ and oligodendrocyte differentiation. The same effect was observed with the removal of CS chains with chondroitinase ABC but not polyclonal antibodies against the extracellular domain of PTPRZ. These results indicate that the negatively charged CS moiety prevents PTPRZ from spontaneously clustering and that the positively charged ligand PTN induces PTPRZ clustering, potentially by neutralizing electrostatic repulsion between CS chains. Taken altogether, these data indicate that PTN-PTPRZ-A signaling controls the timing of oligodendrocyte precursor cell differentiation in vivo, in which the CS moiety of PTPRZ receptors maintains them in a monomeric active state until its ligand binding.

Computational analysis of interactions in structurally available protein-glycosaminoglycan complexes

Glycosaminoglycans represent a class of linear anionic periodic polysaccharides, which play a key role in a variety of biological processes in the extracellular matrix via interactions with their protein targets. Computationally, glycosaminoglycans are very challenging due to their high flexibility, periodicity and electrostatics-driven nature of the interactions with their protein counterparts. In this work, we carry out a detailed computational characterization of the interactions in protein-glycosaminoglycan complexes from the Protein Data Bank (PDB), which are split into two subsets accounting for their intrinsic nature: non-enzymatic-protein-glycosaminoglycan and enzyme-glycosaminoglycan complexes. We apply molecular dynamics to analyze the differences in these two subsets in terms of flexibility, retainment of the native interactions in the simulations, free energy components of binding and contributions of protein residue types to glycosaminoglycan binding. Furthermore, we systematically demonstrate that protein electrostatic potential calculations, previously found to be successful for glycosaminoglycan binding sites prediction for individual systems, are in general very useful for proposing protein surface regions as putative glycosaminoglycan binding sites, which can be further used for local docking calculations with these particular polysaccharides. Finally, the performance of six different docking programs (Autodock 3, Autodock Vina, MOE, eHiTS, FlexX and Glide), some of which proved to perform well for particular protein-glycosaminoglycan complexes in previous work, is evaluated on the complete protein-glycosaminoglycan data set from the PDB. This work contributes to widen our knowledge of protein-glycosaminoglycan molecular recognition and could be useful to steer a choice of the strategies to be applied in theoretical studies of these systems.