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.

Repulsive Scaling Replica Exchange Molecular Dynamics in Modeling Protein-Glycosaminoglycan Complexes.

Glycosaminoglycans are long linear periodic anionic polysaccharides consisting of disaccharide units exhibiting different sulfation patterns forming a highly heterogeneous group of molecules. Due to their flexibility, length, high charge, and periodicity, they are challenging for computational approaches. Despite their biological significance in terms of the important role in various diseases (e.g., Alzheimer, cancer, SARS-CoV-2) and proper cell functioning (e.g., proliferation, maturation), there is a lack of effective molecular docking tools designed specifically for glycosaminoglycans due to their challenging physical-chemical nature. In this chapter we present protocols for the Repulsive Scaling Replica Exchange Molecular Dynamics (RS-REMD) methods to dock glycosaminoglycans with both implicit and explicit solvent models implemented. This novel molecular dynamics-based replica exchange technique should help to elevate our current knowledge on the complexes and interactions between glycosaminoglycans and their protein receptors.

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.

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.

Modeling glycosaminoglycan-protein complexes.

Glycosaminoglycans are long linear and complex polysaccharides that are fundamental components of the mammalian extracellular matrix. Therefore, it is crucial to appropriately characterize molecular structure, dynamics, and interactions of protein-glycosaminoglycans complexes for improving understanding of molecular mechanisms underlying GAG biological function. Nevertheless, this proved challenging experimentally, and theoretical techniques are beneficial to construct new hypotheses and aid the interpretation of experimental data. The scope of this mini-review is to summarize four specific aspects of the current theoretical approaches for investigating noncovalent protein-glycosaminoglycan complexes such as molecular docking, free binding energy calculations, modeling ion impact, and addressing the phenomena of multipose binding of glycosaminoglycans to proteins.

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.

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.

Modeling protein structures with the coarse-grained UNRES force field in the CASP14 experiment.

The UNited RESidue (UNRES) force field was tested in the 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14), in which larger oligomeric and multimeric targets were present compared to previous editions. Three prediction modes were tested (i) ab initio (the UNRES group), (ii) contact-assisted (the UNRES-contact group), and (iii) template-assisted (the UNRES-template group). For most of the targets, the contact restraints were derived from the server models top-ranked by the DeepQA method, while the DNCON2 method was used for 11 targets. Our consensus-fragment procedure was used to run template-assisted predictions. Each group also processed the Nuclear Magnetic Resonance (NMR)- and Small Angle X-Ray Scattering (SAXS)-data assisted targets. The average Global Distance Test Total Score (GDT_TS) of the 'Model 1' predictions were 29.17, 39.32, and 56.37 for the UNRES, UNRES-contact, and UNRES-template predictions, respectively, increasing by 0.53, 2.24, and 3.76, respectively, compared to CASP13. It was also found that the GDT_TS of the UNRES models obtained in ab initio mode and in the contact-assisted mode decreases with the square root of chain length, while the exponent in this relationship is 0.20 for the UNRES-template group models and 0.11 for the best performing AlphaFold2 models, which suggests that incorporation of database information, which stems from protein evolution, brings in long-range correlations, thus enabling the correction of force-field inaccuracies.

Evaluation of replica exchange with repulsive scaling approach for docking glycosaminoglycans.

Glycosaminoglycans (GAGs), long linear periodic anionic polysaccharides, are key molecules in the extracellular matrix (ECM). Therefore, deciphering their role in the biologically relevant context is important for fundamental understanding of the processes ongoing in ECM and for establishing new strategies in the regenerative medicine. Although GAGs represent a number of computational challenges, molecular docking is a powerful tool for analysis of their interactions. Despite the recent development of GAG-specific docking approaches, there is plenty of room for improvement. Here, replica exchange molecular dynamics with repulsive scaling (REMD-RS) recently proved to be a successful approach for protein-protein complexes, was applied to dock GAGs. In this method, effective pairwise radii are increased in different Hamiltonian replicas. REMD-RS is shown to be an attractive alternative to classical docking approaches for GAGs. This work contributes to setting up of GAG-specific computational protocols and provides new insights into the nature of these biological systems.

Further analyses of APRIL/APRIL-receptor/glycosaminoglycan interactions by biochemical assays linked to computational studies.

A proliferation-inducing ligand (APRIL) is a member of the tumor necrosis factor superfamily. APRIL is quite unique in this superfamily for at least for two reasons: (i) it binds to glycosaminoglycans (GAGs) via its positively charged N-terminus; (ii) one of its signaling receptor, the transmembrane activator and CAML interactor (TACI), was also reported to bind GAGs. Here, as provided by biochemical evidences with the use of an APRIL deletion mutant linked to computational studies, APRIL-GAG interaction involved other regions than the APRIL N-terminus. Preferential interaction of APRIL with heparin followed by chondroitin sulfate E was confirmed by in silico analysis. Both computational and experimental approaches did not reveal the heparan sulfate binding to TACI. Together, computational results corroborated experiments contributing with atomistic details to the knowledge on this biologically relevant trimolecular system. Additionally, a high-throughput rigorous analysis of the free energy calculations data was performed to critically evaluate the applied computational methodologies.

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

Glycosaminoglycans (GAGs) are anionic, periodic, linear polysaccharides which are composed of periodic disaccharide units. They play a vital role in many biological processes ongoing in the extracellular matrix. In terms of computational approaches, GAGs are very challenging molecules due to their high flexibility, periodicity, predominantly electrostatic-driven nature of interactions with their protein counterparts and potential multipose binding. Furthermore, the molecular mechanisms underlying GAG-mediated interactions are not fully known yet, and experimental techniques alone are not always sufficient to gain insights into them. The aim of this study was to characterize protein-ion-GAG complexes for the systems where ions are directly involved in GAG binding. Molecular docking, molecular dynamics and free energy calculation approaches were applied to model and rigorously analyse the interactions between annexins (II and V), calcium ions (Ca2+) and heparin (HP). The computational data were examined and discussed in the context of the structural data previously reported by the crystallographic studies. The computational results confirm that the presence of Ca2+ has a tremendous impact on the annexin-HP binding site. This study provides a general computational pipeline to discover the complexity of protein-GAG interactions and helps to understand the role of ions involved at the atomic level. The limitations of the applied protocols are described and discussed pointing at the challenges persisting in the state-of-the-art in silico tools to study protein-ion-GAG systems.