Longitudinal Dynamics of the Neutralizing Antibody Response to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global pandemic with no licensed vaccine or specific antiviral agents for therapy. Little is known about the longitudinal dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific neutralizing antibodies (NAbs) in patients with COVID-19. METHODS: Blood samples (n = 173) were collected from 30 patients with COVID-19 over a 3-month period after symptom onset and analyzed for SARS-CoV-2-specific NAbs using the lentiviral pseudotype assay, coincident with the levels of IgG and proinflammatory cytokines. RESULTS: SARS-CoV-2-specific NAb titers were low for the first 7-10 days after symptom onset and increased after 2-3 weeks. The median peak time for NAbs was 33 days (interquartile range [IQR], 24-59 days) after symptom onset. NAb titers in 93.3% (28/30) of the patients declined gradually over the 3-month study period, with a median decrease of 34.8% (IQR, 19.6-42.4%). NAb titers increased over time in parallel with the rise in immunoglobulin G (IgG) antibody levels, correlating well at week 3 (r = 0.41, P < .05). The NAb titers also demonstrated a significant positive correlation with levels of plasma proinflammatory cytokines, including stem cell factor (SCF), TNF-related apoptosis-inducing ligand (TRAIL), and macrophage colony-stimulating factor (M-CSF). CONCLUSIONS: These data provide useful information regarding dynamic changes in NAbs in patients with COVID-19 during the acute and convalescent phases.

A Peptide-Based Magnetic Chemiluminescence Enzyme Immunoassay for Serological Diagnosis of Coronavirus Disease 2019.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel ß-coronavirus, causes severe pneumonia and has spread throughout the globe rapidly. The disease associated with SARS-CoV-2 infection is named coronavirus disease 2019 (COVID-19). To date, real-time reverse-transcription polymerase chain reaction (RT-PCR) is the only test able to confirm this infection. However, the accuracy of RT-PCR depends on several factors; variations in these factors might significantly lower the sensitivity of detection. METHODS: In this study, we developed a peptide-based luminescent immunoassay that detected immunoglobulin (Ig)G and IgM. The assay cutoff value was determined by evaluating the sera from healthy and infected patients for pathogens other than SARS-CoV-2. RESULTS: To evaluate assay performance, we detected IgG and IgM in the sera from confirmed patients. The positive rate of IgG and IgM was 71.4% and 57.2%, respectively. CONCLUSIONS: Therefore, combining our immunoassay with real-time RT-PCR might enhance the diagnostic accuracy of COVID-19.

IFPTarget: A Customized Virtual Target Identification Method Based on Protein-Ligand Interaction Fingerprinting Analyses.

Small-molecule target identification is an important and challenging task for chemical biology and drug discovery. Structure-based virtual target identification has been widely used, which infers and prioritizes potential protein targets for the molecule of interest (MOI) principally via a scoring function. However, current "universal" scoring functions may not always accurately identify targets to which the MOI binds from the retrieved target database, in part due to a lack of consideration of the important binding features for an individual target. Here, we present IFPTarget, a customized virtual target identification method, which uses an interaction fingerprinting (IFP) method for target-specific interaction analyses and a comprehensive index (Cvalue) for target ranking. Evaluation results indicate that the IFP method enables substantially improved binding pose prediction, and Cvalue has an excellent performance in target ranking for the test set. When applied to screen against our established target library that contains 11,863 protein structures covering 2842 unique targets, IFPTarget could retrieve known targets within the top-ranked list and identified new potential targets for chemically diverse drugs. IFPTarget prediction led to the identification of the metallo-ß-lactamase VIM-2 as a target for quercetin as validated by enzymatic inhibition assays. This study provides a new in silico target identification tool and will aid future efforts to develop new target-customized methods for target identification.

Engineering P450 Peroxygenase to Catalyze Highly Enantioselective Epoxidation of cis-ß-Methylstyrenes.

P450 119 peroxygenase and its site-directed mutants are discovered to catalyze the enantioselective epoxidation of methyl-substituted styrenes. Two new site-directed P450 119 mutants, namely T213Y and T213M, which were designed to improve the enantioselectivity and activity for the epoxidation of styrene and its methyl substituted derivatives, were studied. The T213M mutant is found to be the first engineered P450 peroxygenase that shows highly enantioselective epoxidation of cis-ß-methylstyrenes, with up to 91 % ee. Molecular modeling studies provide insights into the different catalytic activity of the T213M mutant and the T213Y mutant in the epoxidation of cis-ß-methylstyrene. The results of the calculations also contribute to a better understanding of the substrate specificity and configuration control for the regio- and stereoselective peroxygenation catalyzed by the T213M mutant.

SLC27A5 promotes sorafenib-induced ferroptosis in hepatocellular carcinoma by downregulating glutathione reductase.

Sorafenib, a first-line drug for advanced hepatocellular carcinoma (HCC), shows a favorable anti-tumor effect while resistance is a barrier impeding patients from benefiting from it. Thus, more efforts are needed to lift this restriction. Herein, we first find that solute carrier family 27 member 5 (SLC27A5/FATP5), an enzyme involved in the metabolism of fatty acid and bile acid, is downregulated in sorafenib-resistant HCC. SLC27A5 deficiency facilitates the resistance towards sorafenib in HCC cells, which is mediated by suppressing ferroptosis. Further mechanism studies reveal that the loss of SLC27A5 enhances the glutathione reductase (GSR) expression in a nuclear factor erythroid 2-related factor 2 (NRF2)-dependent manner, which maintains glutathione (GSH) homeostasis and renders insensitive to sorafenib-induced ferroptosis. Notably, SLC27A5 negatively correlates with GSR, and genetic or pharmacological inhibition of GSR strengthens the efficacy of sorafenib through GSH depletion and the accumulation of lipid peroxide products in SLC27A5-knockout and sorafenib-resistant HCC cells. Based on our results, the combination of sorafenib and carmustine (BCNU), a selective inhibitor of GSR, remarkably hamper tumor growth by enhancing ferroptotic cell death in vivo. In conclusion, we describe that SLC27A5 serves as a suppressor in sorafenib resistance and promotes sorafenib-triggered ferroptosis via restraining the NRF2/GSR pathway in HCC, providing a potential therapeutic strategy for overcoming sorafenib resistance.

O-GlcNAcylation of SPOP promotes carcinogenesis in hepatocellular carcinoma.

Aberrantly elevated O-GlcNAcylation level is commonly observed in human cancer patients, and has been proposed as a potential therapeutic target. Speckle-type POZ protein (SPOP), an important substrate adaptor of cullin3-RING ubiquitin ligase, plays a key role in the initiation and development of various cancers. However, the regulatory mechanisms governing SPOP and its function during hepatocellular carcinoma (HCC) progression remain unclear. Here, we show that, in HCC, SPOP is highly O-GlcNAcylated by O-GlcNAc transferase (OGT) at Ser96. In normal liver cells, the SPOP protein mainly localizes in the cytoplasm and mediates the ubiquitination of the oncoprotein neurite outgrowth inhibitor-B (Nogo-B) (also known as reticulon 4 B) by recognizing its N-terminal SPOP-binding consensus (SBC) motifs. However, O-GlcNAcylation of SPOP at Ser96 increases the nuclear positioning of SPOP in hepatoma cells, alleviating the ubiquitination of the Nogo-B protein, thereby promoting HCC progression in vitro and in vivo. In addition, ablation of O-GlcNAcylation by an S96A mutation increased the cytoplasmic localization of SPOP, thereby inhibiting the Nogo-B/c-FLIP cascade and HCC progression. Our findings reveal a novel post-translational modification of SPOP and identify a novel SPOP substrate, Nogo-B, in HCC. Intervention with the hyper O-GlcNAcylation of SPOP may provide a novel strategy for HCC treatment.

High dietary fructose promotes hepatocellular carcinoma progression by enhancing O-GlcNAcylation via microbiota-derived acetate.

Emerging studies have addressed the tumor-promoting role of fructose in different cancers. The effects and pathological mechanisms of high dietary fructose on hepatocellular carcinoma (HCC) remain unclear. Here, we examined the effects of fructose supplementation on HCC progression in wild-type C57BL/6 mice using a spontaneous and chemically induced HCC mouse model. We show that elevated uridine diphospho-N-acetylglucosamine (UDP-GlcNAc) and O-GlcNAcylation levels induced by high dietary fructose contribute to HCC progression. Non-targeted metabolomics and stable isotope tracing revealed that under fructose treatment, microbiota-derived acetate upregulates glutamine and UDP-GlcNAc levels and enhances protein O-GlcNAcylation in HCC. Global profiling of O-GlcNAcylation revealed that hyper-O-GlcNAcylation of eukaryotic elongation factor 1A1 promotes cell proliferation and tumor growth. Targeting glutamate-ammonia ligase or O-linked N-acetylglucosamine transferase (OGT) remarkably impeded HCC progression in mice with high fructose intake. We propose that high dietary fructose promotes HCC progression through microbial acetate-induced hyper-O-GlcNAcylation.

Designing a nanoparticle-containing polymeric substrate for detecting cancer cells by computer simulations.

Efficient and accurate detection of cancer cells (from normal cells) is of great importance in cancer diagnosis and prognosis. In this work, we design a new type of polymeric substrate containing nanoparticles for detecting cancers by the dissipative particle dynamics (DPD) simulation. It is found that the cancer cells and the normal cells can be indeed distinguished since the uptake number of nanoparticles from the substrate is different. The competition between the nanoparticle-cell specific interaction and nanoparticle-polymer non-specific interaction is the main factor for different uptake behaviors. Moreover, the dynamics of the nanoparticle diffusion in the polymer layer also plays an important role in the detection. To improve the detection accuracy, we further investigate the effect of the polymer type and density as well as the ligand type on the detection, and find that there may exist an optimal parameter to maximize the difference between cancer cells and normal cells. The present study may provide useful insights into the design of functionalized substrate-based nanodevices in biomedicine.

Ion transport through a nanoporous C2N membrane: the effect of electric field and layer number.

Ion transport through a two-dimensional membrane with nanopores plays an important role in many scientific and technical applications (e.g., water desalination, ion separation and nanofiltration). Although there have been many two-dimensional membranes for these applications, the problem of how to controllably fabricate nanopores with proper shape and size still remains challenging. In the present work, the transport of ions through a C2N membrane with intrinsically regular and uniformly distributed nanopores is investigated using all-atom molecular dynamic simulations. It was found that the monolayer C2N membrane possesses higher ion permeability compared to the graphene membrane because of its higher density of nanopores. In addition, it exhibits excellent ion selectivity under a low electric field due to the distinct dehydration capabilities and interaction behaviors (with the pore edges) of the different ions. Furthermore, we found that multilayer C2N membranes have weak ion selectivity, but show promising potential for desalination. The present study may provide some physical insights into the experimental design of C2N-based nanodevices in nanofluids.

Discovery of Potent and Selective Inhibitors of Cdc2-Like Kinase 1 (CLK1) as a New Class of Autophagy Inducers.

Autophagy inducers represent new promising agents for the treatment of a wide range of medical illnesses. However, safe autophagy inducers for clinical applications are lacking. Inhibition of cdc2-like kinase 1 (CLK1) was recently found to efficiently induce autophagy. Unfortunately, most of the known CLK1 inhibitors have unsatisfactory selectivity. Herein, we report the discovery of a series of new CLK1 inhibitors containing the 1H-[1,2,3]triazolo[4,5-c]quinoline scaffold. Among them, compound 25 was the most potent and selective, with an IC50 value of 2 nM against CLK1. The crystal structure of CLK1 complexed with compound 25 was solved, and the potency and kinase selectivity of compound 25 were interpreted. Compound 25 was able to induce autophagy in in vitro assays and displayed significant hepatoprotective effects in the acetaminophen (APAP)-induced liver injury mouse model. Collectively, due to its potency and selectivity, compound 25 could be used as a chemical probe or agent in future mechanism-of-action or autophagy-related disease therapy studies.

Design, Synthesis, and Biological Evaluation of 1-Benzyl-1H-pyrazole Derivatives as Receptor Interacting Protein 1 Kinase Inhibitors.

Receptor interacting protein 1 (RIP1) kinase plays an important role in necroptosis, and inhibitors of the RIP1 kinase are thought to have a potential therapeutic value in the treatment of diseases related to necrosis. Herein, we report the structural optimization of a RIP1 kinase inhibitor, 1-(2,4-dichlorobenzyl)-3-nitro-1H-pyrazole (1a). A number of 1-benzyl-1H-pyrazole derivatives were synthesized and structure-activity relationship (SAR) analysis led to the discovery of a potent compound, 4b, which showed a Kd value of 0.078 µm against the RIP1 kinase and an EC50 value of 0.160 µm in a cell necroptosis inhibitory assay. Compound 4b also displayed considerable ability to protect the pancreas in an l-arginine-induced pancreatitis mouse model.

A prediction model of drug-induced ototoxicity developed by an optimal support vector machine (SVM) method.

Drug-induced ototoxicity, as a toxic side effect, is an important issue needed to be considered in drug discovery. Nevertheless, current experimental methods used to evaluate drug-induced ototoxicity are often time-consuming and expensive, indicating that they are not suitable for a large-scale evaluation of drug-induced ototoxicity in the early stage of drug discovery. We thus, in this investigation, established an effective computational prediction model of drug-induced ototoxicity using an optimal support vector machine (SVM) method, GA-CG-SVM. Three GA-CG-SVM models were developed based on three training sets containing agents bearing different risk levels of drug-induced ototoxicity. For comparison, models based on naïve Bayesian (NB) and recursive partitioning (RP) methods were also used on the same training sets. Among all the prediction models, the GA-CG-SVM model II showed the best performance, which offered prediction accuracies of 85.33% and 83.05% for two independent test sets, respectively. Overall, the good performance of the GA-CG-SVM model II indicates that it could be used for the prediction of drug-induced ototoxicity in the early stage of drug discovery.