NMR Characterization of the Interactions Between Glycosaminoglycans and Proteins

Identification of heparin-binding amino acid residues in antibody HS4C3 with the potential to design antibodies against heparan sulfate domains

Heparan sulfate (HS) is a linear polysaccharide with high structural and functional diversity. Detection and localization of HS in tissues can be performed using single chain variable fragment (scFv) antibodies. Although several anti-HS antibodies recognizing different sulfation motifs have been identified, little is known about their interaction with HS. In this study the interaction between the scFv antibody HS4C3 and heparin was investigated. Heparin-binding lysine and arginine residues were identified using a protect and label methodology. Site-directed mutagenesis was applied to further identify critical heparin-binding lysine/arginine residues using immunohistochemical and biochemical assays. In addition, computational docking of a heparin tetrasaccharide towards a 3-D homology model of HS4C3 was applied to identify potential heparin-binding sites. Of the 12 lysine and 15 arginine residues within the HS4C3 antibody, 6 and 9, respectively, were identified as heparin-binding. Most of these residues are located within one of the complementarity determining regions (CDR) or in their proximity. All basic amino acid residues in the CDR3 region of the heavy chain were involved in binding. Computational docking showed a heparin tetrasaccharide close to these regions. Mutagenesis of heparin-binding residues reduced or altered reactivity towards HS and heparin. Identification of heparin-binding arginine and lysine residues in HS4C3 allows for better understanding of the interaction with HS and creates a framework to rationally design antibodies targeting specific HS motifs.

Deciphering the role of glycosaminoglycans in GPCR signaling

G protein-coupled receptors (GPCR) and glycosaminoglycans (GAGs) are two essential components of the cell surface that regulate physiological processes in the body. GPCRs are the most extensive family of transmembrane receptors that control cellular responses to extracellular stimuli, while GAGs are polysaccharides that contribute to the function of the extracellular matrix (ECM). Due to their proximity to the plasma membrane, GAGs participate in signal transduction by interacting with various extracellular molecules and cell surface receptors. GAGs can directly interact with certain GPCRs or their ligands (chemokines, peptide hormones and neuropeptides, structural proteins, and enzymes) from the glutamate receptor family, the rhodopsin receptor family, the adhesion receptor family, and the secretin receptor family. These interactions have recently become an emerging topic, providing a new avenue for understanding how GPCR signaling is regulated. This review discusses our current state of knowledge about the role of GAGs in GPCR signaling and function.

Endosomal signaling via cAMP in parathyroid hormone (PTH) type 1 receptor biology

Compartmentalization of GPCR signaling is an emerging topic that highlights the physiological relevance of spatial bias in signaling. The parathyroid hormone (PTH) type 1 receptor (PTH1R) was the first GPCR described to signal via heterotrimeric G-protein and cAMP from endosomes after β-arrestin mediated internalization, challenging the canonical GPCR signaling model which established that signaling is terminated by receptor internalization. More than a decade later, many other GPCRs have been shown to signal from endosomes via cAMP, and recent studies have proposed that location of cAMP generation impacts physiological outcomes of GPCR signaling. Here, we review the extensive literature regarding PTH1R endosomal signaling via cAMP, the mechanisms that regulate endosomal generation of cAMP, and the implications of spatial bias in PTH1R physiological functions.

Heparin Oligosaccharides as Vasoactive Intestinal Peptide Inhibitors via their Binding Process Characterization

BACKGROUND

It has been proven that vasoactive intestinal peptide (VIP) was involved in the pathogenesis of prostate cancer. Cardin et al. found that by an alanine scan, the heparin- binding site on VIP was exactly the same sequence in VIP and its receptor. Therefore, heparin could competitively block the binding of VIP and its receptor. However, the structure-activity relationship between heparin and VIP has not been reported, especially in terms of the sequence and sulfation patterns of heparin oligosaccharides upon binding to VIP.

OBJECTIVE

A variety of experiments were designed to study the binding process and structure-activity relationship between heparin oligosaccharides and VIP.

METHODS

Heparin was enzymatically digested and purified to produce heparin oligosaccharides, and the structures were characterized by NMR. The binding capacity between heparin oligosaccharides and VIP was analyzed by GMSA and ITC experiments. The binding between heparin oligosaccharides and VIP was simulated using a molecular docking program to show the complex. ELISA assay was used to investigate the effect of non-anticoagulant heparin oligosaccharides on the VIP-mediated cAMP/PKA signaling pathway in vitro.

RESULTS

The results indicated that both the length and the sulfation pattern of heparin oligosaccharides affected its binding to VIP. VIP could induce the expression of cAMP at a higher level in PC3 cells, which could be regulated by the interaction of heparin oligosaccharides and VIP.

CONCLUSION

The binding between heparin oligosaccharides and VIP could block the binding between VIP and its receptor on tumor cells. Downloading the regulation of the expression level of cAMP could possibly further affect the subsequent activation of PKA. These non-anticoagulant heparin oligosaccharides may block the VIP-mediated cAMP/PKA signaling pathway and thus exert their antitumor activity.

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.

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.

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.

Antiblood Cell Adhesion of Mussel-Inspired Chondroitin Sulfate- and Caffeic Acid-Modified Polycarbonate Membranes

We fabricated a mussel-inspired hemocompatible polycarbonate membrane (PC) modified by the cross-linking of chondroitin sulfate and caffeic acid polymer using CA-CS via a Schiff base and Michael addition reaction and named it CA-CS-PC. The as-fabricated CA-CS-PC membrane shows excellent hydrophilicity with a water contact angle of 0° and a negative surface charge with a zeta potential of -32 mV. The antiadhesion property of the CA-CS-modified PC membrane was investigated by enzyme-linked immunosorbent assay (ELISA), using human plasma protein fibrinogen adsorption studies, and proved to have excellent antiadhesion properties, because of the lower fibrinogen adsorption. In addition, the CA-CS-PC membrane also shows enhanced hemocompatibility. Finally, blood cell attachment tests of the CA-CS-PC membrane were observed by CLSM and SEM, and the obtained results proved that CA-CS-PC effectively resisted cell adhesion, such as platelets and leucocytes. Therefore, this work disclosed a new way to design a simple and versatile modification of the membrane surface by caffeic acid and chondroitin sulfate and apply it for cell adhesion.

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

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

The glycosaminoglycan interactome 2.0

Glycosaminoglycans (GAGs) are complex linear polysaccharides, which are covalently attached to core proteins (except for hyaluronan) to form proteoglycans. They play key roles in the organization of the extracellular matrix, and at the cell surface where they contribute to the regulation of cell signaling and of cell adhesion. To explore the mechanisms and pathways underlying their functions, we have generated an expanded dataset of 4290 interactions corresponding to 3464 unique GAG-binding proteins, four times more than the first version of the GAG interactome (Vallet and Ricard-Blum, 2021 J Histochem Cytochem 69:93-104). The increased size of the GAG network is mostly due to the addition of GAG-binding proteins captured from cell lysates and biological fluids by affinity chromatography and identified by mass spectrometry. We review here the interaction repertoire of natural GAGs and of synthetic sulfated hyaluronan, the specificity and molecular functions of GAG-binding proteins, and the biological processes and pathways they are involved in. This dataset is also used to investigate the differences between proteins binding to iduronic acid-containing GAGs (dermatan sulfate and heparin/heparan sulfate) and those interacting with GAGs lacking iduronic acid (chondroitin sulfate, hyaluronan, and keratan sulfate).

Modeling Protein-Glycosaminoglycan Complexes: Does the Size Matter?

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

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

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

Semaphorin 3A-Glycosaminoglycans Interaction as Therapeutic Target for Axonal Regeneration

Semaphorin 3A (Sema3A) is a cell-secreted protein that participates in the axonal guidance pathways. Sema3A acts as a canonical repulsive axon guidance molecule, inhibiting CNS regenerative axonal growth and propagation. Therefore, interfering with Sema3A signaling is proposed as a therapeutic target for achieving functional recovery after CNS injuries. It has been shown that Sema3A adheres to the proteoglycan component of the extracellular matrix (ECM) and selectively binds to heparin and chondroitin sulfate-E (CS-E) glycosaminoglycans (GAGs). We hypothesize that the biologically relevant interaction between Sema3A and GAGs takes place at Sema3A C-terminal polybasic region (SCT). The aims of this study were to characterize the interaction of the whole Sema3A C-terminal polybasic region (Sema3A 725–771) with GAGs and to investigate the disruption of this interaction by small molecules. Recombinant Sema3A basic domain was produced and we used a combination of biophysical techniques (NMR, SPR, and heparin affinity chromatography) to gain insight into the interaction of the Sema3A C-terminal domain with GAGs. The results demonstrate that SCT is an intrinsically disordered region, which confirms that SCT binds to GAGs and helps to identify the specific residues involved in the interaction. NMR studies, supported by molecular dynamics simulations, show that a new peptoid molecule (CSIC02) may disrupt the interaction between SCT and heparin. Our structural study paves the way toward the design of new molecules targeting these protein–GAG interactions with potential therapeutic applications.