No abstract

Glycosaminoglycans (GAGs) play key roles in virtually all biologic responses through their interaction with proteins. A major challenge in understanding these roles is their massive structural complexity. Computational approaches are extremely useful in navigating this bottleneck and, in some cases, the only avenue to gain comprehensive insight. We discuss the state-of-the-art on computational approaches and present a flowchart to help answer most basic, and some advanced, questions on GAG-protein interactions. For example, firstly, does my protein bind to GAGs?; secondly, where does the GAG bind?; thirdly, does my protein preferentially recognize a particular GAG type?; fourthly, what is the most optimal GAG chain length?; fifthly, what is the structure of the most favored GAG sequence?; and finally, is my GAG-protein system 'specific', 'non-specific', or a combination of both? Recent advances show the field is now poised to enable a non-computational researcher perform advanced experiments through the availability of various tools and online servers.

Cystic fibrosis (CF) is a multifactorial disease in which dysfunction of protease-antiprotease balance plays a key role. The current CF therapy relies on dornase α, hypertonic saline, and antibiotics and does not address the high neutrophil elastase (NE) activity observed in the lung and sputum of CF patients. Our hypothesis is that variants of heparin, which potently inhibit NE but are not anticoagulant, would help restore the protease-antiprotease balance in CF. To realize this concept, we studied molecular principles governing the effectiveness of different heparins, especially 2-,3--desulfated heparin (ODSH), in the presence of sputum components and therapeutic agents. Using sputa from CF patients and an NE activity assay, we found that heparins are ineffective if used in the absence of dornase. This is true even when mucolytics, such as DTT or -acetylcysteine, were used. Computational modeling suggested that ODSH and DNA compete for binding to an overlapping allosteric site on NE, which reduces the anti-NE potential of ODSH. NE inhibition of both DNA and ODSH is chain length-dependent, but ODSH chains exhibit higher potency per unit residue length. Likewise, ODSH chains exhibit higher NE inhibition potential compared with DNA chains in the presence of saline. These studies suggest fundamental differences in DNA and ODSH recognition and inhibition of NE despite engaging overlapping sites and offer unique insights into molecular principles that could be used in developing antiprotease agents in the presence of current treatments, such as dornase and hypertonic saline.

Glycosaminoglycans (GAGs) interact with many proteins to regulate processes such as hemostasis, cell adhesion, growth and differentiation and viral infection. Yet, majority of these interactions remain poorly understood at a molecular level. A major reason for this state is the phenomenal structural diversity of GAGs, which has precluded analysis of specificity of their interactions. We had earlier presented a computational protocol for predicting "high-specificity" GAG sequences based on combinatorial virtual library screening (CVLS) technology. In this work, we expand the robustness of this technology through rigorous studies of parameters affecting GAG recognition of proteins, especially antithrombin and thrombin. The CVLS approach involves automated construction of a virtual library of all possible oligosaccharide sequences (di- to octasaccharide) followed by a two-step selection strategy consisting of "affinity" (GOLD score) and "specificity" (consistency of binding) filters. We find that "specificity" features are optimally evaluated using 100 genetic algorithm experiments, 100,000 evolutions and variable docking radius from 10 Å (disaccharide) to 14 Å (hexasaccharide). The results highlight critical interactions in H/HS oligosaccharides that govern specificity. Application of CVLS technology to the antithrombin-heparin system indicates that the minimal "specificity" element is the GlcAp(1 → 4)GlcNp2S3S disaccharide of heparin. The CVLS technology affords a simple, intuitive framework for the design of longer GAG sequences that can exhibit high "specificity" without resorting to exhaustive screening of millions of theoretical sequences.

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.