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

Identification of an Unnatural Sulfated Monosaccharide as a High-Affinity Ligand for Pan-Variant Targeting of SARS-CoV-2 Spike Glycoprotein

Identifying smaller sulfated glycan fragments that recognize target proteins with high affinity is highly challenging. In this work, we show that microarray screening of 53 small glycan fragments helped identify distinct sulfated monosaccharide to tetrasaccharide fragments that bind to multiple isoforms of SARS-CoV-2 spike glycoprotein (SgP) with high affinity. Our library consisted of natural and unnatural glycan sequences with a wide range of sulfation levels. The unnatural features arose from the presence of phosphate or fluoro groups on the natural sulfated GAG scaffold as well as sulfate modification of idose fragments that were monomer to tetramer long. None of the natural glycans yielded much promise, which probably conveys the importance of the polymeric glycosaminoglycan chain in SgP biology. However, the unnatural idose fragments with sulfation at the 2, 3, 4, and 6 positions displayed high affinities (100-500 nM) for wild-type, Delta, and Omicron variants of SgP. The unnatural sulfated idose monosaccharide is the smallest molecule known to date that can be classified as a high-affinity, pan-variant fragment. This fragment is expected to serve as the lead for the design of pan-variant ligands with sub-nM inhibition potency.

A Robust Proteomics-Based Method for Identifying Preferred Protein Targets of Synthetic Glycosaminoglycan Mimetics

A robust technology is critically needed for identifying preferred protein targets of glycosaminoglycans (GAGs), and synthetic mimetics thereof, in biological milieu. We present a robust 10-step strategy for identification and validation of preferred protein targets of highly sulfated, synthetic, small, GAG-like molecules using diazirine-based photoaffinity labeling-proteomics approach. Our work reveals that optimally designed, homogeneous probes based on minimalistic photoactivation and affinity pulldown groups coupled with rigorous proteomics, biochemical and orthogonal validation steps offer excellent potential to identify preferred targets of GAG mimetics from the potentially numerous possible targets that cloud GAG interaction studies. Application of this 10-step strategy for a promising highly sulfated, small GAG mimetic led to identification of only a handful of preferred targets in human plasma. This new robust strategy will greatly aid drug discovery and development efforts involving GAG sequences, or sulfated small mimetics thereof, as leads.

Elucidating the Mechanism of Recognition and Binding of Heparin to Amyloid Fibrils of Serum Amyloid A

Amyloid diseases feature pathologic deposition of normally soluble proteins and peptides as insoluble fibrils in vital organs. Amyloid fibrils co-deposit with various nonfibrillar components including heparan sulfate (HS), a glycosaminoglycan that promotes amyloid formation in vitro for many unrelated proteins. HS-amyloid interactions have been proposed as a therapeutic target for inflammation-linked amyloidosis wherein N-terminal fragments of serum amyloid A (SAA) protein deposit in the kidney and liver. The structural basis for these interactions is unclear. Here, we exploit the high-resolution cryoelectron microscopy (cryo-EM) structures of ex vivo murine and human SAA fibrils in a computational study employing molecular docking, Brownian dynamics simulations, and molecular dynamics simulations to elucidate how heparin, a highly sulfated HS mimetic, recognizes and binds to amyloid protein fibrils. Our results demonstrate that negatively charged heparin chains bind to linear arrays of uncompensated positively charged basic residues along the spines of amyloid fibrils facilitated by electrostatic steering. The predicted heparin binding sites match the location of unidentified densities observed in cryo-EM maps of SAA amyloids, suggesting that these extra densities represent bound HS. Since HS is constitutively found in various amyloid deposits, our results suggest a common mechanism for HS-amyloid recognition and binding.

Design and Synthesis of Small Molecule Probes of MDA-9/Syntenin

MDA-9/Syntenin, a key scaffolding protein and a molecular hub involved in a diverse range of cell signaling responses, has proved to be a challenging target for the design and discovery of small molecule probes. In this paper, we report on the design and synthesis of small molecule ligands of this key protein. Genetic algorithm-based computational design and the five-eight step synthesis of three molecules led to ligands with affinities in the range of 1-3 µM, a 20-60-fold improvement over literature reports. The design and synthesis strategies, coupled with the structure-dependent gain or loss in affinity, afford the deduction of principles that should guide the design of advanced probes of MDA-9/Syntenin.

Introducing Ion Mobility Mass Spectrometry in Brain Glycosaminoglycomics: Application to Chondroitin/Dermatan Sulfate Octasaccharide Domains

Glycosaminoglycans (GAGs) are sulfated linear O-glycan chains abundantly expressed in the extracellular matrix (ECM). Among GAGs, chondroitin sulfate (CS) and dermatan sulfate (DS) play important roles at the brain level, where the distribution and location of the sulfates within the CS/DS chains are responsible for numerous biological events. The diversity of the neural hybrid CS/DS expressed in the brain and the need to elucidate their structure gave rise to considerable efforts toward the development of analytical methods able to discover novel regularly and irregularly sulfated domains. In this context, we report here the introduction of ion mobility separation (IMS) mass spectrometry (MS) in brain glycosaminoglycomics. Based on IMS MS and tandem MS (MS/MS) by collision-induced dissociation (CID), we have developed a powerful approach for the screening and structural analysis of neural CS/DS and optimized and validated the method for the structural analysis of octasaccharides that were released from brain proteoglycans by β-elimination and pooled after chain depolymerization using chondroitin AC lyase. The IMS MS data revealed the separation of CS/DS octamers into mobility families based on the amount of sulfation. Among the discovered oversulfated domains, of major biological importance is the pentasulfated-[4,5-Δ-GlcAGalNAc(IdoAGalNAc)3], for which the (-) nanoESI IMS CID MS/MS analysis disclosed through the presence of distinct drift times, the incidence of two isomers. Moreover, the generated fragment ions revealed an uncommon trisulfated motif and an uncommon pentasulfated motif. Hence, using IMS MS and CID MS/MS, novel brain-related CS/DS domains of atypical sulfation patterns were discovered and structurally characterized in detail.

In silico approaches for better understanding cysteine cathepsin-glycosaminoglycan interactions

Cysteine cathepsins constitute the largest cathepsin family, with 11 proteases in human that are present primarily within acidic endosomal and lysosomal compartments. They are involved in the turnover of intracellular and extracellular proteins. They are synthesized as inactive procathepsins that are converted to mature active forms. Cathepsins play important roles in physiological and pathological processes and, therefore, receive increasing attention as potential therapeutic targets. Their maturation and activity can be regulated by glycosaminoglycans (GAGs), long linear negatively charged polysaccharides composed of recurring dimeric units. In this review, we summarize recent computational progress in the field of (pro)cathepsin-GAG complexes analyses.

Computational toolbox for the analysis of protein-glycan interactions

Protein-glycan interactions play pivotal roles in numerous biological processes, ranging from cellular recognition to immune response modulation. Understanding the intricate details of these interactions is crucial for deciphering the molecular mechanisms underlying various physiological and pathological conditions. Computational techniques have emerged as powerful tools that can help in drawing, building and visualising complex biomolecules and provide insights into their dynamic behaviour at atomic and molecular levels. This review provides an overview of the main computational tools useful for studying biomolecular systems, particularly glycans, both in free state and in complex with proteins, also with reference to the principles, methodologies, and applications of all-atom molecular dynamics simulations. Herein, we focused on the programs that are generally employed for preparing protein and glycan input files to execute molecular dynamics simulations and analyse the corresponding results. The presented computational toolbox represents a valuable resource for researchers studying protein-glycan interactions and incorporates advanced computational methods for building, visualising and predicting protein/glycan structures, modelling protein-ligand complexes, and analyse MD outcomes. Moreover, selected case studies have been reported to highlight the importance of computational tools in studying protein-glycan systems, revealing the capability of these tools to provide valuable insights into the binding kinetics, energetics, and structural determinants that govern specific molecular interactions.

Alteration of Neuropilin-1 and Heparan Sulfate Interaction Impairs Murine B16 Tumor Growth

Neuropilin-1 acts as a coreceptor with vascular endothelial growth factor receptors to facilitate binding of its ligand, vascular endothelial growth factor. Neuropilin-1 also binds to heparan sulfate, but the functional significance of this interaction has not been established. A combinatorial library screening using heparin oligosaccharides followed by molecular dynamics simulations of a heparin tetradecasaccharide suggested a highly conserved binding site composed of amino acid residues extending across the b1 and b2 domains of murine neuropilin-1. Mutagenesis studies established the importance of arginine513 and lysine514 for binding of heparin to a recombinant form of Nrp1 composed of the a1, a2, b1, and b2 domains. Recombinant Nrp1 protein bearing R513A,K514A mutations showed a significant loss of heparin-binding, heparin-induced dimerization, and heparin-dependent thermal stabilization. Isothermal calorimetry experiments suggested a 1:2 complex of heparin tetradecasaccharide:Nrp1. To study the impact of altered heparin binding in vivo, a mutant allele of Nrp1 bearing the R513A,K514A mutations was created in mice (Nrp1D) and crossbred to Nrp1+/- mice to examine the impact of altered heparan sulfate binding. Analysis of tumor formation showed variable effects on tumor growth in Nrp1D/D mice, resulting in a frank reduction in tumor growth in Nrp1D/- mice. Expression of mutant Nrp1D protein was normal in tissues, suggesting that the reduction in tumor growth was due to the altered binding of heparin/heparan sulfate to neuropilin-1. These findings suggest that the interaction of neuropilin-1 with heparan sulfate modulates its stability and its role in tumor formation and growth.

Glycosaminoglycan microarrays for studying glycosaminoglycan-protein systems

More than 3000 proteins are now known to bind to glycosaminoglycans (GAGs). Yet, GAG-protein systems are rather poorly understood in terms of selectivity of recognition, molecular mechanism of action, and translational promise. High-throughput screening (HTS) technologies are critically needed for studying GAG biology and developing GAG-based therapeutics. Microarrays, developed within the past two decades, have now improved to the point of being the preferred tool in the HTS of biomolecules. GAG microarrays, in which GAG sequences are immobilized on slides, while similar to other microarrays, have their own sets of challenges and considerations. GAG microarrays are rapidly becoming the first choice in studying GAG-protein systems. Here, we review different modalities and applications of GAG microarrays presented to date. We discuss advantages and disadvantages of this technology, explain covalent and non-covalent immobilization strategies using different chemically reactive groups, and present various assay formats for qualitative and quantitative interpretations, including selectivity screening, binding affinity studies, competitive binding studies etc. We also highlight recent advances in implementing this technology, cataloging of data, and project its future promise. Overall, the technology of GAG microarray exhibits enormous potential of evolving into more than a mere screening tool for studying GAG - protein systems.

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.

Assessing Genetic Algorithm-Based Docking Protocols for Prediction of Heparin Oligosaccharide Binding Geometries onto Proteins

Although molecular docking has evolved dramatically over the years, its application to glycosaminoglycans (GAGs) has remained challenging because of their intrinsic flexibility, highly anionic character and rather ill-defined site of binding on proteins. GAGs have been treated as either fully "rigid" or fully "flexible" in molecular docking. We reasoned that an intermediate semi-rigid docking (SRD) protocol may be better for the recapitulation of native heparin/heparan sulfate (Hp/HS) topologies. Herein, we study 18 Hp/HS-protein co-complexes containing chains from disaccharide to decasaccharide using genetic algorithm-based docking with rigid, semi-rigid, and flexible docking protocols. Our work reveals that rigid and semi-rigid protocols recapitulate native poses for longer chains (5→10 mers) significantly better than the flexible protocol, while 2→4-mer poses are better predicted using the semi-rigid approach. More importantly, the semi-rigid docking protocol is likely to perform better when no crystal structure information is available. We also present a new parameter for parsing selective versus non-selective GAG-protein systems, which relies on two computational parameters including consistency of binding (i.e., RMSD) and docking score (i.e., GOLD Score). The new semi-rigid protocol in combination with the new computational parameter is expected to be particularly useful in high-throughput screening of GAG sequences for identifying promising druggable targets as well as drug-like Hp/HS sequences.

Merging cultures and disciplines to create a drug discovery ecosystem at Virginia commonwealth university: Medicinal chemistry, structural biology, molecular and behavioral pharmacology and computational chemistry

The Department of Medicinal Chemistry, together with the Institute for Structural Biology, Drug Discovery and Development, at Virginia Commonwealth University (VCU) has evolved, organically with quite a bit of bootstrapping, into a unique drug discovery ecosystem in response to the environment and culture of the university and the wider research enterprise. Each faculty member that joined the department and/or institute added a layer of expertise, technology and most importantly, innovation, that fertilized numerous collaborations within the University and with outside partners. Despite moderate institutional support with respect to a typical drug discovery enterprise, the VCU drug discovery ecosystem has built and maintained an impressive array of facilities and instrumentation for drug synthesis, drug characterization, biomolecular structural analysis and biophysical analysis, and pharmacological studies. Altogether, this ecosystem has had major impacts on numerous therapeutic areas, such as neurology, psychiatry, drugs of abuse, cancer, sickle cell disease, coagulopathy, inflammation, aging disorders and others. Novel tools and strategies for drug discovery, design and development have been developed at VCU in the last five decades; e.g., fundamental rational structure-activity relationship (SAR)-based drug design, structure-based drug design, orthosteric and allosteric drug design, design of multi-functional agents towards polypharmacy outcomes, principles on designing glycosaminoglycans as drugs, and computational tools and algorithms for quantitative SAR (QSAR) and understanding the roles of water and the hydrophobic effect.

Molecular implications of glycosaminoglycans in diabetes pharmacotherapy

Diabetes mellitus causes a wide range of metabolic derangements with multiple organ damage. The microvascular and macrovascular complications of diabetes result partly from the damage to the glycosaminoglycans (GAG) in the basement membrane. GAGs are negatively charged polysaccharides with repeating disaccharide units. They play a significant role in cellular proliferation and signal transduction. Destruction of extracellular matrix results in diseases in various organs including myocardial fibrosis, retinal damage and nephropathy. To substitute the natural GAGs pharmacotherapeutically, they have been synthesized by using basic disaccharide units. Among the four classes of GAGs, heparin is the most widely studied. Recent studies have revealed multiple significant GAG-protein interactions suggesting their use for the management of diabetic complications. Moreover, they can act as biomarkers for assessing the disease progression. A number of GAG-based therapeutic agents are being evaluated for managing diabetic complications. The current review provides an outline of the role of GAGs in diabetes while covering their interaction with different molecular players that can serve as targets for the diagnosis, management and prevention of diabetes and its complications. The medicinal chemistry and clinical pharmacotherapeutics aspects have are covered to aid in the establishment of GAG-based therapies as a possible avenue for diabetes.

Computational studies on glycosaminoglycan recognition of sialyl transferases

Despite decades of research, glycosaminoglycans (GAGs) have not been known to interact with sialyl transferases (STs). Using our in-house combinatorial virtual library screening (CVLS) technology, we studied seven human isoforms, including ST6GAL1, ST6GAL2, ST3GAL1, ST3GAL3, ST3GAL4, ST3GAL5, and ST3GAL6, and predicted that GAGs, especially heparan sulfate (HS), are likely to differentially bind to STs. Exhaustive CVLS and molecular dynamics studies suggested that the common hexasaccharide sequence of HS preferentially recognized ST6GAL1 in a site overlapping the binding site of the donor substrate CMP-Sia. Interestingly, CVLS did not ascribe any special role for the rare 3-O-sulfate modification of HS in ST6GAL1 recognition. The computational predictions were tested using spectrofluorimetric studies, which confirmed preferential recognition of HS over other GAGs. A classic chain length-dependent binding of GAGs to ST6GAL1 was observed with polymeric HS displaying a tight affinity of ~65 nM. Biophysical studies also confirmed a direct competition between CMP-Sia and an HS oligosaccharide and CS polysaccharide for binding to ST6GAL1. Overall, our novel observation that GAGs bind to ST6GAL1 with high affinity and compete with the donor substrate is likely to be important because modulation of sialylation of glycan substrates on cells has considerable physiological/pathological consequences. Our work also brings forth the possibility of developing GAG-based chemical probes of ST6GAL1.

Designing Smaller, Synthetic, Functional Mimetics of Sulfated Glycosaminoglycans as Allosteric Modulators of Coagulation Factors

Natural glycosaminoglycans (GAGs) are arguably the most diverse collection of natural products. Unfortunately, this bounty of structures remains untapped. Decades of research has realized only one GAG-like synthetic, small-molecule drug, fondaparinux. This represents an abysmal output because GAGs present a frontier that few medicinal chemists, and even fewer pharmaceutical companies, dare to undertake. GAGs are heterogeneous, polymeric, polydisperse, highly water soluble, synthetically challenging, too rapidly cleared, and difficult to analyze. Additionally, GAG binding to proteins is not very selective and GAG-binding sites are shallow. This Perspective attempts to transform this negative view into a much more promising one by highlighting recent advances in GAG mimetics. The Perspective focuses on the principles used in the design/discovery of drug-like, synthetic, sulfated small molecules as allosteric modulators of coagulation factors, such as antithrombin, thrombin, and factor XIa. These principles will also aid the design/discovery of sulfated agents against cancer, inflammation, and microbial infection.

Glycosaminoglycans: What Remains To Be Deciphered?

Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise "glycocodes" that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics.

Molecular Dynamics-Based Comparative Analysis of Chondroitin and Dermatan Sulfates

Glycosaminoglycans (GAGs) are a class of linear anionic periodic polysaccharides containing disaccharide repetitive units. These molecules interact with a variety of proteins in the extracellular matrix and so participate in biochemically crucial processes such as cell signalling affecting tissue regeneration as well as the onset of cancer, Alzheimer's or Parkinson's diseases. Due to their flexibility, periodicity and chemical heterogeneity, often termed "sulfation code", GAGs are challenging molecules both for experiments and computation. One of the key questions in the GAG research is the specificity of their intermolecular interactions. In this study, we make a step forward to deciphering the "sulfation code" of chondroitin sulfates-4,6 (CS4, CS6, where the numbers correspond to the position of sulfation in NAcGal residue) and dermatan sulfate (DS), which is different from CSs by the presence of IdoA acid instead of GlcA. We rigorously investigate two sets of these GAGs in dimeric, tetrameric and hexameric forms with molecular dynamics-based descriptors. Our data clearly suggest that CS4, CS6 and DS are substantially different in terms of their structural, conformational and dynamic properties, which contributes to the understanding of how these molecules can be different when they bind proteins, which could have practical implications for the GAG-based drug design strategies in the regenerative medicine.

Designing Synthetic, Sulfated Glycosaminoglycan Mimetics That Are Orally Bioavailable and Exhibiting In Vivo Anticancer Activity

Sulfated glycosaminoglycans (GAGs), or synthetic mimetics thereof, are not favorably viewed as orally bioavailable drugs owing to their high number of anionic sulfate groups. Devising an approach for oral delivery of such highly sulfated molecules would be very useful. This work presents the concept that conjugating cholesterol to synthetic sulfated GAG mimetics enables oral delivery. A focused library of sulfated GAG mimetics was synthesized and found to inhibit the growth of a colorectal cancer cell line under spheroid conditions with a wide range of potencies ( 0.8 to 46 μM). Specific analogues containing cholesterol, either alone or in combination with clinical utilized drugs, exhibited pronounced in vivo anticancer potential with intraperitoneal as well as oral administration, as assessed by ex vivo tertiary and quaternary spheroid growth, cancer stem cell (CSC) markers, and/or self-renewal factors. Overall, cholesterol derivatization of highly sulfated GAG mimetics affords an excellent approach for engineering oral activity.

The diverse role of heparan sulfate and other GAGs in SARS-CoV-2 infections and therapeutics

In December 2019, the global coronavirus disease 2019 (COVID-19) pandemic began in Wuhan, China. COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which infects host cells primarily through the angiotensin-converting enzyme 2 (ACE2) receptor. In addition to ACE2, several studies have shown the importance of heparan sulfate (HS) on the host cell surface as a co-receptor for SARS-CoV-2-binding. This insight has driven research into antiviral therapies, aimed at inhibiting the HS co-receptor-binding, e.g., by glycosaminoglycans (GAGs), a family of sulfated polysaccharides that includes HS. Several GAGs, such as heparin (a highly sulfated analog of HS), are used to treat various health indications, including COVID-19. This review is focused on current research on the involvement of HS in SARS-CoV-2 infection, implications of viral mutations, as well as the use of GAGs and other sulfated polysaccharides as antiviral agents.

Antiviral Disaccharide Lead Compounds against SARS-CoV-2 through Computer-Aided High-Throughput Screen

SARS-CoV-2 infects human epithelial cells through specific interaction with angiotensin-converting enzyme 2 (ACE2). In addition, heparan sulfate proteoglycans act as the attachment factor to promote the binding of viral spike protein receptor binding domain (RBD) to ACE2 on host cells. Though the rapid development of vaccines has contributed significantly to preventing severe disease, mutated SARS-CoV-2 strains, especially the SARS-CoV-2 Omicron variant, show increased affinity of RBD binding to ACE2, leading to immune escape. Thus, there is still an unmet need for new antiviral drugs. In this study, we constructed pharmacophore models based on the spike RBD of SARS-CoV-2 and SARS-CoV-2 Omicron variant and performed virtual screen for best-hit compounds from our disaccharide library. Screening of 96 disaccharide structures identified two disaccharides that displayed higher binding affinity to RBD in comparison to reported small molecule antiviral drugs. Further, screening PharmMapper demonstrated interactions of the disaccharides with a number of inflammatory cytokines, suggesting a potential for disaccharides with multiple-protein targets.

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.

Effect of Sulfation on the Conformational Dynamics of Dermatan Sulfate Glycosaminoglycan: A Gaussian Accelerated Molecular Dynamics Study

Glycosaminoglycans (GAGs) are anionic biopolymers present on cell surfaces as a part of proteoglycans. The biological activities of GAGs depend on the sulfation pattern. In our study, we have considered three octadecasaccharide dermatan sulfate (DS) chains with increasing order of sulfation (dp6s, dp7s, and dp12s) to illuminate the role of sulfation on the GAG units and its chain conformation through 10 μs-long Gaussian accelerated molecular dynamics simulations. DS is composed of repeating disaccharide units of iduronic acid (IdoA) and N-acetylgalactosamine (N-GalNAc). Here, N-GalNAc is linked to IdoA via β(1-4), while IdoA is linked to N-GalNAc through α(1-3). With the increase in sulfation, the DS structure becomes more rigid and linear, as is evident from the distribution of root-mean-square deviations (RMSDs) and end-to-end distances. The tetrasaccharide linker region of the main chain shows a rigid conformation in terms of the glycosidic linkage. We have observed that upon sulfation (i.e., dp12s), the ring flip between two chair forms vanished for IdoA. The dynamic cross-correlation analysis reveals that the anticorrelation motions in dp12s are reduced significantly compared to dp6s or dp7s. An increase in sulfation generates relatively more stable hydrogen-bond networks, including water bridging with the neighboring monosaccharides. Despite the favorable linear structures of the GAG chains, our study also predicts few significant bendings related to the different puckering states, which may play a notable role in the function of the DS. The relation between the global conformation with the micro-level parameters such as puckering and water-mediated hydrogen bonds shapes the overall conformational space of GAGs. Overall, atomistic details of the DS chain provided in this study will help understand their functional and mechanical roles, besides developing new biomaterials.

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.

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.

On the Selectivity of Heparan Sulfate Recognition by SARS-CoV-2 Spike Glycoprotein

SARS-CoV-2 infects human cells through its surface spike glycoprotein (SgP), which relies on host cell surface heparan sulfate (HS) proteoglycans that facilitate interaction with the ACE2 receptor. Targeting this process could lead to inhibitors of early steps in viral entry. Screening a microarray of 24 HS oligosaccharides against recombinant S1 and receptor-binding domain (RBD) proteins led to identification of only eight sequences as potent antagonists; results that were supported by detailed dual-filter computational studies. Competitive studies using the HS microarray suggested almost equivalent importance of IdoA2S-GlcNS6S and GlcNS3S structures, which were supported by affinity studies. Exhaustive virtual screening on a library of >93 000 sequences led to a novel pharmacophore with at least two 3-O-sulfated GlcN residues that can engineer unique selectivity in recognizing the RBD. This work puts forward the key structural motif in HS that should lead to potent and selective HS or HS-like agents against SARS-CoV-2.

The Influences of Sulphation, Salt Type, and Salt Concentration on the Structural Heterogeneity of Glycosaminoglycans

The increasing recognition of the biochemical importance of glycosaminoglycans (GAGs) has in recent times made them the center of attention of recent research investigations. It became evident that subtle conformational factors play an important role in determining the relationship between the chemical composition of GAGs and their activity. Therefore, a thorough understanding of their structural flexibility is needed, which is addressed in this work by means of all-atom molecular dynamics (MD) simulations. Four major GAGs with different substitution patterns, namely hyaluronic acid as unsulphated GAG, heparan-6-sulphate, chondroitin-4-sulphate, and chondroitin-6-sulphate, were investigated to elucidate the influence of sulphation on the dynamical features of GAGs. Moreover, the effects of increasing NaCl and KCl concentrations were studied as well. Different structural parameters were determined from the MD simulations, in combination with a presentation of the free energy landscape of the GAG conformations, which allowed us to unravel the conformational fingerprints unique to each GAG. The largest effects on the GAG structures were found for sulphation at position 6, as well as binding of the metal ions in the absence of chloride ions to the carboxylate and sulphate groups, which both increase the GAG conformational flexibility.

Computerized Molecular Modeling for Discovering Promising Glycosaminoglycan Oligosaccharides that Modulate Protein Function

Glycosaminoglycans (GAGs) are a class of highly negatively charged polysaccharides that plays a major role in various biological processes through their interaction with hundreds of proteins. A major challenge in understanding the specific protein-GAG interaction is their structural diversity and complexity. Recently, computational approaches have been used extensively in addressing this challenge. In this chapter, we present a generally-applicable methodology termed Combinatorial Virtual Library Screening (CVLS) that can identify potential high-affinity, high-specificity sequence(s) binding to a suitable GAG-binding protein from large GAG combinatorial libraries of various lengths and structural patterns.

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.

Chondroitin Sulfate/Dermatan Sulfate-Protein Interactions and Their Biological Functions in Human Diseases: Implications and Analytical Tools

Chondroitin sulfate (CS) and dermatan sulfate (DS) are linear anionic polysaccharides that are widely present on the cell surface and in the cell matrix and connective tissue. CS and DS chains are usually attached to core proteins and are present in the form of proteoglycans (PGs). They not only are important structural substances but also bind to a variety of cytokines, growth factors, cell surface receptors, adhesion molecules, enzymes and fibrillary glycoproteins to execute series of important biological functions. CS and DS exhibit variable sulfation patterns and different sequence arrangements, and their molecular weights also vary within a large range, increasing the structural complexity and diversity of CS/DS. The structure-function relationship of CS/DS PGs directly and indirectly involves them in a variety of physiological and pathological processes. Accumulating evidence suggests that CS/DS serves as an important cofactor for many cell behaviors. Understanding the molecular basis of these interactions helps to elucidate the occurrence and development of various diseases and the development of new therapeutic approaches. The present article reviews the physiological and pathological processes in which CS and DS participate through their interactions with different proteins. Moreover, classic and emerging glycosaminoglycan (GAG)-protein interaction analysis tools and their applications in CS/DS-protein characterization are also discussed.

Combinatorial Virtual Library Screening Study of Transforming Growth Factor-β2-Chondroitin Sulfate System

Transforming growth factor-beta (TGF-β), a member of the TGF-β cytokine superfamily, is known to bind to sulfated glycosaminoglycans (GAGs), but the nature of this interaction remains unclear. In a recent study, we found that preterm human milk TGF-β2 is sequestered by chondroitin sulfate (CS) in its proteoglycan form. To understand the molecular basis of the TGF-β2-CS interaction, we utilized the computational combinatorial virtual library screening (CVLS) approach in tandem with molecular dynamics (MD) simulations. All possible CS oligosaccharides were generated in a combinatorial manner to give 24 di- (CS02), 192 tetra- (CS04), and 1536 hexa- (CS06) saccharides. This library of 1752 CS oligosaccharides was first screened against TGF-β2 using the dual filter CVLS algorithm in which the GOLDScore and root-mean-square-difference (RMSD) between the best bound poses were used as surrogate markers for in silico affinity and in silico specificity. CVLS predicted that both the chain length and level of sulfation are critical for the high affinity and high specificity recognition of TGF-β2. Interestingly, CVLS led to identification of two distinct sites of GAG binding on TGF-β2. CVLS also deduced the preferred composition of the high specificity hexasaccharides, which were further assessed in all-atom explicit solvent MD simulations. The MD results confirmed that both sites of binding form stable GAG-protein complexes. More specifically, the highly selective CS chains were found to engage the TGF-β2 monomer with high affinity. Overall, this work present key principles of recognition with regard to the TGF-β2-CS system. In the process, it led to the generation of the in silico library of all possible CS oligosaccharides, which can be used for advanced studies on other protein-CS systems. Finally, the study led to the identification of unique CS sequences that are predicted to selectively recognize TGF-β2 and may out-compete common natural CS biopolymers.

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.

Glycosaminoglycan-Protein Interactions and Their Roles in Human Disease

Glycosaminoglycans (GAGs) are a family of linear and negatively charged polysaccharides that exist ubiquitously on the human cell surface as well as in the extracellular matrix. GAGs interact with a wide range of proteins, including proteases, growth factors, cytokines, chemokines and adhesion molecules, enabling them to mediate many physiological processes, such as protein function, cellular adhesion and signaling. GAG-protein interactions participate in and intervene in a variety of human diseases, including cardiovascular disease, infectious disease, neurodegenerative diseases and tumors. The breakthrough in analytical tools and approaches during the last two decades has facilitated a greater understanding of the importance of GAG-protein interactions and their roles in human diseases. This review focuses on aspects of the molecular basis and mechanisms of GAG-protein interactions involved in human disease. The most recent advances in analytical tools, especially mass spectrometry-based GAG sequencing and binding motif characterization methods, are introduced. An update of selected families of GAG binding proteins is presented. Perspectives on development of novel therapeutics targeting specific GAG-protein interactions are also covered in this review.

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.

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.

Metabolic engineering of non-pathogenic Escherichia coli strains for the controlled production of low molecular weight heparosan and size-specific heparosan oligosaccharides

BACKGROUND

Heparin, a lifesaving blood thinner used in over 100 million surgical procedures worldwide annually, is currently isolated from over 700 million pigs and ~200 million cattle in slaughterhouses worldwide. Though animal-derived heparin has been in use over eight decades, it is a complex mixture that poses a risk for chemical adulteration, and its availability is highly vulnerable. Therefore, there is an urgent need in devising bioengineering approaches for the production of heparin polymers, especially low molecular weight heparin (LMWH), and thus, relying less on animal sources. One of the main challenges, however, is the rapid, cost-effective production of low molecular weight heparosan, a precursor of LMWH and size-defined heparosan oligosaccharides. Another challenge is N-sulfation of N-acetyl heparosan oligosaccharides efficiently, an essential modification required for subsequent enzymatic modifications, though chemical and enzymatic N-sulfation is effectively performed at the polymer level.

METHODS

To devise a strategy to produce low molecular weight heparosan and heparosan oligosaccharides, several non-pathogenic E. coli strains are engineered by transforming the essential heparosan biosynthetic genes with or without the eliminase gene (elmA) from pathogenic E. coli K5.

RESULTS

The metabolically engineered non-pathogenic strains are shown to produce ~5 kDa heparosan, a precursor for low molecular weight heparin, for the first time. Additionally, heparosan oligosaccharides of specific sizes ranging from tetrasaccharide to dodecasaccharide are directly generated, in a single step, from the recombinant bacterial strains that carry both heparosan biosynthetic genes and the eliminase gene. Various modifications, such as chemical N-sulfation of N-acetyl heparosan hexasaccharide following the selective protection of reducing end GlcNAc residue, enzymatic C5-epimerization of N-sulfo heparosan tetrasaccharide and complete 6-O sulfation of N-sulfo heparosan hexasaccharide, are shown to be feasible.

CONCLUSIONS

We engineered non-pathogenic E. coli strains to produce low molecular weight heparosan and a range of size-specific heparosan oligosaccharides in a controlled manner through modulating culture conditions. We have also shown various chemical and enzymatic modifications of heparosan oligosaccharides.

GENERAL SIGNIFICANCE

Heparosan is a precursor of heparin and the methods to produce low molecular weight heparosan is widely awaited. The methods described herein are promising and will pave the way for potential large scale production of low molecular weight heparin anticoagulants and bioactive heparin oligosaccharides in the coming decade.

Preferential recognition and antagonism of SARS-CoV-2 spike glycoprotein binding to 3-O-sulfated heparan sulfate

The COVID-19 pandemic caused by SARS-CoV-2 is in immediate need of an effective antidote. Although the Spike glycoprotein (SgP) of SARS-CoV-2 has been shown to bind to heparins, the structural features of this interaction, the role of a plausible heparan sulfate proteoglycan (HSPG) receptor, and the antagonism of this pathway through small molecules remain unaddressed. Using an in vitro cellular assay, we demonstrate HSPGs modified by the 3-O-sulfotransferase isoform-3, but not isoform-5, preferentially increased SgP-mediated cell-to-cell fusion in comparison to control, unmodified, wild-type HSPGs. Computational studies support preferential recognition of the receptor-binding domain of SgP by 3-O-sulfated HS sequences. Competition with either fondaparinux, a 3-O-sulfated HS-binding oligopeptide, or a synthetic, non-sugar small molecule, blocked SgP-mediated cell-to-cell fusion. Finally, the synthetic, sulfated molecule inhibited fusion of GFP-tagged pseudo SARS-CoV-2 with human 293T cells with sub-micromolar potency. Overall, overexpression of 3-O-sulfated HSPGs contribute to fusion of SARS-CoV-2, which could be effectively antagonized by a synthetic, small molecule.

Discovery of Sulfated Small Molecule Inhibitors of Matrix Metalloproteinase-8

Elevated matrix metalloproteinase-8 (MMP-8) activity contributes to the etiology of many diseases, including atherosclerosis, pulmonary fibrosis, and sepsis. Yet, very few small molecule inhibitors of MMP-8 have been identified. We reasoned that the synthetic non-sugar mimetics of glycosaminoglycans may inhibit MMP-8 because natural glycosaminoglycans are known to modulate the functions of various MMPs. The screening a library of 58 synthetic, sulfated mimetics consisting of a dozen scaffolds led to the identification of only two scaffolds, including sulfated benzofurans and sulfated quinazolinones, as promising inhibitors of MMP-8. Interestingly, the sulfated quinazolinones displayed full antagonism of MMP-8 and sulfated benzofuran appeared to show partial antagonism. Of the two, sulfated quinazolinones exhibited a >10-fold selectivity for MMP-8 over MMP-9, a closely related metalloproteinase. Molecular modeling suggested the plausible occupancy of the S₁^′ pocket on MMP-8 as the distinguishing feature of the interaction. Overall, this work provides the first proof that the sulfated mimetics of glycosaminoglycans could lead to potent, selective, and catalytic activity-tunable, small molecular inhibitors of MMP-8.

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.

Discovering small-molecule therapeutics against SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly become a global health pandemic. The lack of effective treatments, coupled with its etiology, has resulted in more than 400,000 deaths at the time of writing. The SARS-CoV-2 genome is highly homologous to that of SARS-CoV, the causative agent behind the 2003 SARS outbreak. Based on prior reports, clinicians have pursued the off-label use of several antiviral drugs, while the scientific community has responded by seeking agents against traditional targets, especially viral proteases. However, several avenues remain unexplored, including disrupting E and M protein oligomerization, outcompeting host glycan-virus interactions, interfering with the heparan sulfate proteoglycans-virus interaction, and others. In this review, we highlight some of these opportunities while summarizing the drugs currently in use against coronavirus 2019 (COVID-19).

Rigorous analysis of free solution glycosaminoglycan dynamics using simple, new tools

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