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Abstract SARS-CoV-2 receptor binding domains (RBDs) interact with both the ACE2 receptor and heparan sulfate on the surface of host cells to enhance SARS-CoV-2 infection. We show that suramin, a polysulfated synthetic drug, binds to the ACE2 receptor and heparan sulfate binding sites on the RBDs of wild-type, Delta, and Omicron variants. Specifically, heparan sulfate and suramin had enhanced preferential binding for Omicron RBD, and suramin is most potent against the live SARS-CoV-2 Omicron variant (B.1.1.529) when compared to wild type and Delta (B.1.617.2) variants in vitro. These results suggest that inhibition of live virus infection occurs through dual SARS-CoV-2 targets of S-protein binding and previously reported RNA-dependent RNA polymerase inhibition and offers the possibility for this and other polysulfated molecules to be used as potential therapeutic and prophylactic options against COVID-19. 

Sulfated glycans from marine organisms are excellent sources of naturally occurring glycosaminoglycan (GAG) mimetics that demonstrate therapeutic activities, such as antiviral/microbial infection, anticoagulant, anticancer, and anti-inflammation activities. Many viruses use the heparan sulfate (HS) GAG on the surface of host cells as co-receptors for attachment and initiating cell entry. Therefore, virion–HS interactions have been targeted to develop broad-spectrum antiviral therapeutics. Here we report the potential anti-monkeypox virus (MPXV) activities of eight defined marine sulfated glycans, three fucosylated chondroitin sulfates, and three sulfated fucans extracted from the sea cucumber species Isostichopus badionotus, Holothuria floridana, and Pentacta pygmaea, and the sea urchin Lytechinus variegatus, as well as two chemically desulfated derivatives. The inhibitions of these marine sulfated glycans on MPXV A29 and A35 protein–heparin interactions were evaluated using surface plasmon resonance (SPR). These results demonstrated that the viral surface proteins of MPXV A29 and A35 bound to heparin, which is a highly sulfated HS, and sulfated glycans from sea cucumbers showed strong inhibition of MPXV A29 and A35 interactions. The study of molecular interactions between viral proteins and host cell GAGs is important in developing therapeutics for the prevention and treatment of MPXV. 

The now prevalent Omicron variant and its subvariants/sub-lineages have led to a significant increase in COVID-19 cases and raised serious concerns about increased risk of infectivity, immune evasion, and reinfection. Heparan sulfate (HS), located on the surface of host cells, plays an important role as a co-receptor for virus–host cell interaction. The ability of heparin and HS to compete for binding of the SARS-CoV-2 spike (S) protein to cell surface HS illustrates the therapeutic potential of agents targeting protein–glycan interactions. In the current study, phylogenetic tree of variants and mutations in S protein receptor-binding domain (RBD) of Omicron BA.2.12.1, BA.4 and BA.5 were described. The binding affinity of Omicron S protein RBD to heparin was further investigated by surface plasmon resonance (SPR). Solution competition studies on the inhibitory activity of heparin oligosaccharides and desulfated heparins at different sites on S protein RBD–heparin interactions revealed that different sub-lineages tend to bind heparin with different chain lengths and sulfation patterns. Furthermore, blind docking experiments showed the contribution of basic amino acid residues in RBD and sulfo groups and carboxyl groups on heparin to the interaction. Finally, pentosan polysulfate and mucopolysaccharide polysulfate were evaluated for inhibition on the interaction of heparin and S protein RBD of Omicron BA.2.12.1, BA.4/BA.5, and both showed much stronger inhibition than heparin. 

Involving students in scientific modeling practice is one of the most effective approaches to achieving the next generation science education learning goals. Given the complexity and multirepresentational features of scientific models, scoring student-developed models is time- and cost-intensive, remaining one of the most challenging assessment practices for science education. More importantly, teachers who rely on timely feedback to plan and adjust instruction are reluctant to use modeling tasks because they could not provide timely feedback to learners. This study utilized machine learn- ing (ML), the most advanced artificial intelligence (AI), to develop an approach to automatically score student- drawn models and their written descriptions of those models. We developed six modeling assessment tasks for middle school students that integrate disciplinary core ideas and crosscutting concepts with the modeling practice. For each task, we asked students to draw a model and write a description of that model, which gave students with diverse backgrounds an opportunity to represent their understanding in multiple ways. We then collected student responses to the six tasks and had human experts score a subset of those responses. We used the human-scored student responses to develop ML algorithmic models (AMs) and to train the computer. Validation using new data suggests that the machine-assigned scores achieved robust agreements with human consent scores. Qualitative analysis of student-drawn models further revealed five characteristics that might impact machine scoring accuracy: Alternative expression, confusing label, inconsistent size, inconsistent position, and redundant information. We argue that these five characteristics should be considered when developing machine-scorable modeling tasks. 

Monkeypox virus (MPXV), a member of the Orthopoxvirus genus, has begun to spread into many countries worldwide. While the prevalence of monkeypox in Central and Western Africa is well-known, the recent rise in the number of cases spread through intimate personal contact, particularly in the United States, poses a grave international threat. Previous studies have shown that cell-surface heparan sulfate (HS) is important for vaccinia virus (VACV) infection, particularly the binding of VACV A27, which appears to mediate the binding of virus to cellular HS. Some other glycosaminoglycans (GAGs) also bind to proteins on Orthopoxviruses. In this study, by using surface plasmon resonance, we demonstrated that MPXV A29 protein (a homolog of VACV A27) binds to GAGs including heparin and chondroitin sulfate/dermatan sulfate. The negative charges on GAGs are important for GAG–MPXV A29 interaction. GAG analogs, pentosan polysulfate and mucopolysaccharide polysulfate, show strong inhibition of MPXV A29–heparin interaction. A detailed understanding on the molecular interactions involved in this disease should accelerate the development of therapeutics and drugs for the treatment of MPXV.