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

Structural Insights into Endostatin-Heparan Sulfate Interactions Using Modeling Approaches

Glycosaminoglycans (GAGs) play a key role in a variety of biological processes in the extracellular matrix (ECM) via interactions with their protein targets. Due to their high flexibility, periodicity and electrostatics-driven interactions, GAG-containing complexes are very challenging to characterize both experimentally and in silico. In this study, we, for the first time, systematically analyzed the interactions of endostatin, a proteolytic fragment of collagen XVIII known to be anti-angiogenic and anti-tumoral, with heparin (HP) and representative heparan sulfate (HS) oligosaccharides of various lengths, sequences and sulfation patterns. We first used conventional molecular docking and a docking approach based on a repulsive scaling-replica exchange molecular dynamics technique, as well as unbiased molecular dynamic simulations, to obtain dynamically stable GAG binding poses. Then, the corresponding free energies of binding were calculated and the amino acid residues that contribute the most to GAG binding were identified. We also investigated the potential influence of Zn2+ on endostatin-HP complexes using computational approaches. These data provide new atomistic details of the molecular mechanism of HP's binding to endostatin, which will contribute to a better understanding of its interplay with proteoglycans at the cell surface and in the extracellular matrix.

Conformational preferences of heparan sulfate to recognize the CXCL8 dimer in aqueous medium: degree of sulfation and hydrogen bonds

The sulfation pattern and epimerization of the long-chain sulfated polysaccharide heparan sulfate (HS) cause structural diversity and regulate various physiological and pathological processes when binding with proteins. In this work, we performed a series of molecular dynamics simulations of three variants of the octadecasaccharide HS with varying sulfation positions in aqueous medium in their free forms and in the presence of the chemokine CXCL8 dimer. The free energy of binding depicts the sulfation at the 6-O position of GlcNAc (HS6S), and both 3-O and 6-O positions of GlcNAc (HS3S6S) of HS variants are more likely to bind with the CXCL8 dimer than the triply sulfated HS2S3S6S, which is sulfated at the 2-O position of GlcUA additionally along with 3-O and 6-O positions of GlcNAc. Binding between HS and CXCL8 was driven by electrostatic and van der Waals interactions predominantly regardless of the sulfation pattern; however, unfavorable entropic contribution suppressed the interaction between HS and CXCL8. The contribution of different amino acid residues to the binding energetics suggested that basic amino acids line up the binding site of CXCL8. This study further acknowledges the role of interfacial water that is structured and bound with HS through hydrogen bonds, exhibiting differential hydrogen bond relaxation dynamics compared to when the HS molecules are free. Moreover, this study identifies that with the increase in sulfation, the HS-water hydrogen bond relaxation occurs faster with the complexation, while the reverse trend is followed in their free forms. Significant structural adaptation of the different sulfated HS molecules, as verified from the free energy landscapes generated from various reaction coordinates, root-mean-square-deviations, end-to-end distances, including ring pucker angles, dihedral flexibility, and the high conformational entropy cost arising from the glycosidic bonds, suggests that the different sulfated variants of HS undergo significant structural transformation to bind with CXCL8. The presence of a CXCL8 dimer imposes the bound forms of HS to adopt non-linear structures with skew-boat conformations. The atomistic details of the study would help in understanding the selectivity and conformational diversity, as well as the role of solvents in the recognition of CXCL8 by different sulfated variants of HS molecules.

Benchmarking Water Models in Molecular Dynamics of Protein-Glycosaminoglycan Complexes

Glycosaminoglycans (GAGs) made of repeating disaccharide units intricately engage with proteins, playing a crucial role in the spatial organization of the extracellular matrix (ECM) and the transduction of biological signals in cells to modulate a number of biochemical processes. Exploring protein-GAG interactions reveals several challenges for their analysis, namely, the highly charged and periodic nature of GAGs, their multipose binding, and the abundance of the interfacial water molecules in the protein-GAG complexes. Most of the studies on protein-GAG interactions are conducted using the TIP3P water model, and there are no data on the effect of various water models on the results obtained in molecular dynamics (MD) simulations of protein-GAG complexes. Hence, it is essential to perform a systematic analysis of different water models in MD simulations for these systems. In this work, we aim to evaluate the properties of the protein-GAG complexes in MD simulations using different explicit: TIP3P, SPC/E, TIP4P, TIP4PEw, OPC, and TIP5P and implicit: IGB = 1, 2, 5, 7, and 8 water models to find out which of them are best suited to study the dynamics of protein-GAG complexes. The FF14SB and GLYCAM06 force fields were used for the proteins and GAGs, respectively. The interactions of several GAG types, such as heparin, chondroitin sulfate, and hyaluronic acid with basic fibroblast growth factor, cathepsin K, and CD44 receptor, respectively, are investigated. The observed variations in different descriptors used to study the binding in these complexes emphasize the relevance of the choice of water models for the MD simulation of these complexes.

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.

In silico insights into procathepsin S maturation mediated by glycosaminoglycans

Procathepsins, inactive precursors of cathepsins are present in the extracellular matrix (ECM) and in lysosomes. Their active forms are involved in a number of biologically relevant processes, including bone resorption, intracellular proteolysis and regulation of programmed cell death. These processes might be mediated by glycosaminoglycans (GAGs), long unbranched periodic negatively charged polysaccharides. GAGs are also present in ECM and play important role in anticoagulation, angiogenesis and tissue regeneration. GAGs not only mediate the enzymatic activity of cathepsins but can also regulate the process of procathepsin maturation, as it was shown for procathepsin B and S. In this study, we propose the molecular mechanism underlying the biological role of GAGs in procathepsin S maturation and compare our findings with computational data obtained for procathepsin B. We rigorously analyse procathepsin S-GAG complexes in terms of their dynamics, free energy and potential allosteric regulation. We conclude that the GAG binding region might have an effect on the dynamics of procathepsin S structure and so affect its maturation by two different mechanisms.

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.