GlycoTorch Vina: Docking Designed and Tested for Glycosaminoglycans

Highly accurate carbohydrate-binding site prediction with DeepGlycanSite

As the most abundant organic substances in nature, carbohydrates are essential for life. Understanding how carbohydrates regulate proteins in the physiological and pathological processes presents opportunities to address crucial biological problems and develop new therapeutics. However, the diversity and complexity of carbohydrates pose a challenge in experimentally identifying the sites where carbohydrates bind to and act on proteins. Here, we introduce a deep learning model, DeepGlycanSite, capable of accurately predicting carbohydrate-binding sites on a given protein structure. Incorporating geometric and evolutionary features of proteins into a deep equivariant graph neural network with the transformer architecture, DeepGlycanSite remarkably outperforms previous state-of-the-art methods and effectively predicts binding sites for diverse carbohydrates. Integrating with a mutagenesis study, DeepGlycanSite reveals the guanosine-5'-diphosphate-sugar-recognition site of an important G-protein coupled receptor. These findings demonstrate DeepGlycanSite is invaluable for carbohydrate-binding site prediction and could provide insights into molecular mechanisms underlying carbohydrate-regulation of therapeutically important proteins.

Improving impact of heparan sulfate on the endothelial glycocalyx abnormalities in atherosclerosis as revealed by glycan-protein interactome

Endothelial dysfunction induced by oxidative stress is an early predictor of atherosclerosis, which can cause various cardiovascular diseases. The glycocalyx layer on the endothelial cell surface acts as a barrier to maintain endothelial biological function, and it can be impaired by oxidative stress. However, the mechanism of glycocalyx damage during the development of atherosclerosis remains largely unclear. Herein, we established a novel strategy to address these issues from the glycomic perspective that has long been neglected. Using countercharged fluorescence protein staining and quantitative mass spectrometry, we found that heparan sulfate, a major component of the glycocalyx, was structurally altered by oxidative stress. Comparative proteomics and protein microarray analysis revealed several new heparan sulfate-binding proteins, among which alpha-2-Heremans-Schmid glycoprotein (AHSG) was identified as a critical protein. The molecular mechanism of AHSG with heparin was characterized through several methods. A heparan analog could relieve atherosclerosis by protecting heparan sulfate from degradation during oxidative stress and by reducing the accumulation of AHSG at lesion sites. In the present study, the molecular mechanism of anti-atherosclerotic effect of heparin through interaction with AHSG was revealed. These findings provide new insights into understanding of glycocalyx damage in atherosclerosis and lead to the development of corresponding therapeutics.

Structural and mechanistic characterization of bifunctional heparan sulfate N-deacetylase-N-sulfotransferase 1

Heparan sulfate (HS) polysaccharides are major constituents of the extracellular matrix, which are involved in myriad structural and signaling processes. Mature HS polysaccharides contain complex, non-templated patterns of sulfation and epimerization, which mediate interactions with diverse protein partners. Complex HS modifications form around initial clusters of glucosamine-N-sulfate (GlcNS) on nascent polysaccharide chains, but the mechanistic basis underpinning incorporation of GlcNS itself into HS remains unclear. Here, we determine cryo-electron microscopy structures of human N-deacetylase-N-sulfotransferase (NDST)1, the bifunctional enzyme primarily responsible for initial GlcNS modification of HS. Our structures reveal the architecture of both NDST1 deacetylase and sulfotransferase catalytic domains, alongside a non-catalytic N-terminal domain. The two catalytic domains of NDST1 adopt a distinct back-to-back topology that limits direct cooperativity. Binding analyses, aided by activity-modulating nanobodies, suggest that anchoring of the substrate at the sulfotransferase domain initiates the NDST1 catalytic cycle, providing a plausible mechanism for cooperativity despite spatial domain separation. Our data shed light on key determinants of NDST1 activity, and describe tools to probe NDST1 function in vitro and in vivo.

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.

Molecular correlates of vaccine-induced protection against typhoid fever

BACKGROUNDTyphoid fever is caused by the Gram-negative bacterium Salmonella enterica serovar Typhi and poses a substantial public health burden worldwide. Vaccines have been developed based on the surface Vi-capsular polysaccharide of S. Typhi; these include a plain-polysaccharide-based vaccine, ViPS, and a glycoconjugate vaccine, ViTT. To understand immune responses to these vaccines and their vaccine-induced immunological protection, molecular signatures were analyzed using bioinformatic approaches.METHODSBulk RNA-Seq data were generated from blood samples obtained from adult human volunteers enrolled in a vaccine trial, who were then challenged with S. Typhi in a controlled human infection model (CHIM). These data were used to conduct differential gene expression analyses, gene set and modular analyses, B cell repertoire analyses, and time-course analyses at various post-vaccination and post-challenge time points between participants receiving ViTT, ViPS, or a control meningococcal vaccine.RESULTSTranscriptomic responses revealed strong differential molecular signatures between the 2 typhoid vaccines, mostly driven by the upregulation in humoral immune signatures, including selective usage of immunoglobulin heavy chain variable region (IGHV) genes and more polarized clonal expansions. We describe several molecular correlates of protection against S. Typhi infection, including clusters of B cell receptor (BCR) clonotypes associated with protection, with known binders of Vi-polysaccharide among these.CONCLUSIONThe study reports a series of contemporary analyses that reveal the transcriptomic signatures after vaccination and infectious challenge, while identifying molecular correlates of protection that may inform future vaccine design and assessment.TRIAL REGISTRATIONClinicalTrials.gov NCT02324751.

Analysis of the First Ion Coordination Sphere: A Toolkit to Analyze the Coordination Sphere of Ions

Rapid and accurate approaches to characterizing the coordination structure of an ion are important for designing ligands and quantifying structure-property trends. Here, we introduce AFICS (Analysis of the First Ion Coordination Sphere), a tool written in Python 3 for analyzing the structural and geometric features of the first coordination sphere of an ion over the course of molecular dynamics simulations. The principal feature of AFICS is its ability to quantify the distortion a coordination geometry undergoes compared to uniform polyhedra. This work applies the toolkit to analyze molecular dynamics simulations of the well-defined coordination structure of aqueous Cr³⁺ along with the more ambiguous structure of aqueous Eu³⁺ chelated to ethylenediaminetetraacetic acid. The tool is targeted for analyzing ions with fluxional or irregular coordination structures (e.g., solution structures of f-block elements) but is generalized such that it may be applied to other systems.

Solvent Model Benchmark for Molecular Dynamics of Glycosaminoglycans

In computational studies of glycosaminoglycans (GAGs), a group of anionic, periodic linear polysaccharides, so far there has been very little discussion about the role of solvent models in the molecular dynamics simulations of these molecules. Predominantly, the TIP3P water model is commonly used as one of the most popular explicit water models in general. However, there are numerous alternative explicit and implicit water models that are neglected in the computational research of GAGs. Since solvent-mediated interactions are particularly important for GAG dynamic and structural properties, it would be of great interest for the GAG community to establish the solvent model that is suited the best in terms of the quality of theoretically obtained GAG parameters and, at the same time, would be reasonably demanding in terms of computational resources required. In this study, heparin (HP) was simulated using five implicit and six explicit solvent models with the aim to find out how different solvent models influence HP's molecular descriptors in the molecular dynamics simulations. Here, we initiate the search for the most appropriate solvent representation for GAG systems and we hope to encourage other groups to contribute to this highly relevant subject.

Tools for mammalian glycoscience research

Cellular carbohydrates or glycans are critical mediators of biological function. Their remarkably diverse structures and varied activities present exciting opportunities for understanding many areas of biology. In this primer, we discuss key methods and recent breakthrough technologies for identifying, monitoring, and manipulating glycans in mammalian systems.

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.

Synthetic Heparan Sulfate Mimetic Pixatimod (PG545) Potently Inhibits SARS-CoV-2 by Disrupting the Spike-ACE2 Interaction

Heparan sulfate (HS) is a cell surface polysaccharide recently identified as a coreceptor with the ACE2 protein for the S1 spike protein on SARS-CoV-2 virus, providing a tractable new therapeutic target. Clinically used heparins demonstrate an inhibitory activity but have an anticoagulant activity and are supply-limited, necessitating alternative solutions. Here, we show that synthetic HS mimetic pixatimod (PG545), a cancer drug candidate, binds and destabilizes the SARS-CoV-2 spike protein receptor binding domain and directly inhibits its binding to ACE2, consistent with molecular modeling identification of multiple molecular contacts and overlapping pixatimod and ACE2 binding sites. Assays with multiple clinical isolates of SARS-CoV-2 virus show that pixatimod potently inhibits the infection of monkey Vero E6 cells and physiologically relevant human bronchial epithelial cells at safe therapeutic concentrations. Pixatimod also retained broad potency against variants of concern (VOC) including B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), and B.1.1.529 (Omicron). Furthermore, in a K18-hACE2 mouse model, pixatimod significantly reduced SARS-CoV-2 viral titers in the upper respiratory tract and virus-induced weight loss. This demonstration of potent anti-SARS-CoV-2 activity tolerant to emerging mutations establishes proof-of-concept for targeting the HS-Spike protein-ACE2 axis with synthetic HS mimetics and provides a strong rationale for clinical investigation of pixatimod as a potential multimodal therapeutic for COVID-19.

Structural Insights into Pixatimod (PG545) Inhibition of Heparanase, a Key Enzyme in Cancer and Viral Infections

Pixatimod (PG545), a heparan sulfate (HS) mimetic and anticancer agent currently in clinical trials, is a potent inhibitor of heparanase. Heparanase is an endo‐β‐glucuronidase that degrades HS in the extracellular matrix and basement membranes and is implicated in numerous pathological processes such as cancer and viral infections, including SARS−CoV‐2. To understand how PG545 interacts with heparanase, we firstly carried out a conformational analysis through a combination of NMR experiments and molecular modelling which showed that the reducing end β‐D‐glucose residue of PG545 adopts a distorted conformation. This was followed by docking and molecular dynamics simulations to study the interactions of PG545 with heparanase, revealing that PG545 is able to block the active site by binding in different conformations, with the cholestanol side‐chain making important hydrophobic interactions. While PG545 blocks its natural substrate HS from binding to the active site, small synthetic heparanase substrates are only partially excluded, and thus pentasaccharide or larger substrates are preferred for assaying this class of inhibitor. This study provides new insights for the design of next‐generation heparanase inhibitors and substrates.

Systemic Lectin-Glycan Interaction of Pathogenic Enteric Bacteria in the Gastrointestinal Tract

Microorganisms, such as bacteria, viruses, and fungi, and host cells, such as plants and animals, have carbohydrate chains and lectins that reciprocally recognize one another. In hosts, the defense system is activated upon non-self-pattern recognition of microbial pathogen-associated molecular patterns. These are present in Gram-negative and Gram-positive bacteria and fungi. Glycan-based PAMPs are bound to a class of lectins that are widely distributed among eukaryotes. The first step of bacterial infection in humans is the adhesion of the pathogen's lectin-like proteins to the outer membrane surfaces of host cells, which are composed of glycans. Microbes and hosts binding to each other specifically is of critical importance. The adhesion factors used between pathogens and hosts remain unknown; therefore, research is needed to identify these factors to prevent intestinal infection or treat it in its early stages. This review aims to present a vision for the prevention and treatment of infectious diseases by identifying the role of the host glycans in the immune response against pathogenic intestinal bacteria through studies on the lectin-glycan interaction.

Modeling Protein-Glycosaminoglycan Complexes: Does the Size Matter?

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

From Cancer to COVID-19: A Perspective on Targeting Heparan Sulfate-Protein Interactions

Heparan sulfate (HS) is a complex, polyanionic polysaccharide ubiquitously expressed on cell surfaces and in the extracellular matrix. HS interacts with numerous proteins to mediate a vast array of biological and pathological processes. Inhibition of HS‐protein interactions is thus an attractive approach for new therapeutic development for cancer and infectious diseases, including COVID‐19; however, synthesis of well‐defined native HS oligosaccharides remains challenging. This has aroused significant interest in the development of HS mimetics which are more synthetically tractable and have fewer side effects, such as undesired anticoagulant activity. This account provides a perspective on the design and synthesis of different classes of HS mimetics with useful properties, and the development of various assays and molecular modelling tools to progress our understanding of their interactions with HS‐binding proteins.

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.

Evidence of a putative glycosaminoglycan binding site on the glycosylated SARS-CoV-2 spike protein N-terminal domain

SARS-CoV-2 has rapidly spread throughout the world's population since its initial discovery in 2019. The virus infects cells via a glycosylated spike protein located on its surface. The protein primarily binds to the angiotensin-converting enzyme-2 (ACE2) receptor, using glycosaminoglycans (GAGs) as co-receptors. Here, we performed bioinformatics and molecular dynamics simulations of the spike protein to investigate the existence of additional GAG binding sites on the receptor-binding domain (RBD), separate from previously reported heparin-binding sites. A putative GAG binding site in the N-terminal domain (NTD) of the protein was identified, encompassing residues 245-246. We hypothesized that GAGs of a sufficient length might bridge the gap between this site and the PRRARS furin cleavage site, including the mutation S247R. Docking studies using GlycoTorch Vina and subsequent MD simulations of the spike trimer in the presence of dodecasaccharides of the GAGs heparin and heparan sulfate supported this possibility. The heparan sulfate chain bridged the gap, binding the furin cleavage site and S247R. In contrast, the heparin chain bound the furin cleavage site and surrounding glycosylation structures, but not S247R. These findings identify a site in the spike protein that favors heparan sulfate binding that may be particularly pertinent for a better understanding of the recent UK and South African strains. This will also assist in future targeted therapy programs that could include repurposing clinical heparan sulfate mimetics.