Adverse Effects of Oseltamivir Phosphate Therapy on the Liver of LDLR-/- Mice Without Any Benefit on Atherosclerosis and Thrombosis

Inhibition of neuraminidase-1 sialidase activity by interfering peptides impairs insulin receptor activity in vitro and glucose homeostasis in vivo

Neuraminidases (NEUs) also called sialidases are glycosidases which catalyze the removal of terminal sialic acid residues from glycoproteins, glycolipids, and oligosaccharides. Mammalian NEU-1 participates in regulation of cell surface receptors such as insulin receptor (IR), epithelial growth factor receptor, low-density lipoprotein receptor, and toll-like receptor 4. At the plasma membrane, NEU-1 can be associated with the elastin-binding protein and the carboxypeptidase protective protein/cathepsin A to constitute the elastin receptor complex. In this complex, NEU-1 is essential for elastogenesis, signal transduction through this receptor and for biological effects of the elastin-derived peptides on atherosclerosis, thrombosis, insulin resistance, nonalcoholic steatohepatitis, and cancers. This is why research teams are developing inhibitors targeting this sialidase. Previously, we developed interfering peptides to inhibit the dimerization and the activation of NEU-1. In this study, we investigated the effects of these peptides on IR activation in vitro and in vivo. Using cellular overexpression and endogenous expression models of NEU-1 and IR (COS-7 and HepG2 cells, respectively), we have shown that interfering peptides inhibit NEU-1 dimerization and sialidase activity which results in a reduction of IR phosphorylation. These results demonstrated that NEU-1 positively regulates IR phosphorylation and activation in our conditions. In vivo, biodistribution study showed that interfering peptides are well distributed in mice. Treatment of C57Bl/6 mice during 8 weeks with interfering peptides induces a hyperglycemic effect in our experimental conditions. Altogether, we report here that inhibition of NEU-1 sialidase activity by interfering peptides decreases IR activity in vitro and glucose homeostasis in vivo.

Sialic acids cleavage induced by elastin-derived peptides impairs the interaction between insulin and its receptor in adipocytes 3T3-L1

The insulin receptor (IR) plays an important role in insulin signal transduction, the defect of which is believed to be the root cause of type 2 diabetes. In 3T3-L1 adipocytes as in other cell types, the mature IR is a heterotetrameric cell surface glycoprotein composed of two α subunits and two β subunits. Our objective in our study, is to understand how the desialylation of N-glycan chains, induced by elastin-derived peptides, plays a major role in the function of the IR. Using the 3T3-L1 adipocyte line, we show that removal of the sialic acid from N-glycan chains (N893 and N908), induced by the elastin receptor complex (ERC) and elastin derived-peptides (EDPs), leads to a decrease in the autophosphorylation activity of the insulin receptor. We demonstrate by molecular dynamics approaches that the absence of sialic acids on one of these two sites is sufficient to generate local and general modifications of the structure of the IR. Biochemical approaches highlight a decrease in the interaction between insulin and its receptor when ERC sialidase activity is induced by EDPs. Therefore, desialylation by EDPs is synonymous with a decrease of IR sensitivity in adipocytes and could thus be a potential source of insulin resistance associated with diabetic conditions.

BioAct-Het: A Heterogeneous Siamese Neural Network for Bioactivity Prediction Using Novel Bioactivity Representation

Drug failure during experimental procedures due to low bioactivity presents a significant challenge. To mitigate this risk and enhance compound bioactivities, predicting bioactivity classes during lead optimization is essential. The existing studies on structure-activity relationships have highlighted the connection between the chemical structures of compounds and their bioactivity. However, these studies often overlook the intricate relationship between drugs and bioactivity, which encompasses multiple factors beyond the chemical structure alone. To address this issue, we propose the BioAct-Het model, employing a heterogeneous siamese neural network to model the complex relationship between drugs and bioactivity classes, bringing them into a unified latent space. In particular, we introduce a novel representation for the bioactivity classes, called Bio-Prof, and enhance the original bioactivity data sets to tackle data scarcity. These innovative approaches resulted in our model outperforming the previous ones. The evaluation of BioAct-Het is conducted through three distinct strategies: association-based, bioactivity class-based, and compound-based. The association-based strategy utilizes supervised learning classification, while the bioactivity class-based strategy adopts a retrospective study evaluation approach. On the other hand, the compound-based strategy demonstrates similarities to the concept of meta-learning. Furthermore, the model's effectiveness in addressing real-world problems is analyzed through a case study on the application of vancomycin and oseltamivir for COVID-19 treatment as well as molnupiravir's potential efficacy in treating COVID-19 patients. The data and code underlying this article are available on https://github.com/CBRC-lab/BioAct-Het. However, data sets were derived from sources in the public domain.

Lipoprotein sialylation in atherosclerosis: Lessons from mice

Sialylation is a dynamically regulated modification, which commonly occurs at the terminal of glycan chains in glycoproteins and glycolipids in eukaryotic cells. Sialylation plays a key role in a wide array of biological processes through the regulation of protein-protein interactions, intracellular localization, vesicular trafficking, and signal transduction. A majority of the proteins involved in lipoprotein metabolism and atherogenesis, such as apolipoproteins and lipoprotein receptors, are sialylated in their glycan structures. Earlier studies in humans and in preclinical models found a positive correlation between low sialylation of lipoproteins and atherosclerosis. More recent works using loss- and gain-of-function approaches in mice have revealed molecular and cellular mechanisms by which protein sialylation modulates causally the process of atherosclerosis. The purpose of this concise review is to summarize these findings in mouse models and to provide mechanistic insights into lipoprotein sialylation and atherosclerosis.

Proatherogenic Sialidases and Desialylated Lipoproteins: 35 Years of Research and Current State from Bench to Bedside

This review summarizes the main achievements in basic and clinical research of atherosclerosis. Focusing on desialylation as the first and the most important reaction of proatherogenic pathological cascade, we speak of how desialylation increases the atherogenic properties of low density lipoproteins and decreases the anti-atherogenic properties of high density lipoproteins. The separate sections of this paper are devoted to immunogenicity of lipoproteins, the enzymes contributing to their desialylation and animal models of atherosclerosis. In addition, we evaluate the available experimental and diagnostic protocols that can be used to develop new therapeutic approaches for atherosclerosis.