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Extracellular HSP90α (eHSP90α) is a promoter of tumor development and malignant progression. Patients with malignancies, including pancreatic ductal adenocarcinoma (PDAC), have generally shown 5~10-fold increases in serum/plasma eHSP90α levels. In this study, we developed a humanized antibody HH01 to target eHSP90α and evaluated its anticancer efficacy. HH01, with novel complementarity-determining regions, exhibits high binding affinity toward HSP90α. It recognizes HSP90α epitope sites 235AEEKEDKEEE244 and 251ESEDKPEIED260, with critical amino acid residues E237, E239, D240, K241, E253, and K255. HH01 effectively suppressed eHSP90α-induced invasive and spheroid-forming activities of colorectal cancer and PDAC cell lines by blocking eHSP90α’s ligation with the cell-surface receptor CD91. In mouse models, HH01 potently inhibited the tumor growth of PDAC cell grafts/xenografts promoted by endothelial-mesenchymal transition-derived cancer-associated fibroblasts while also reducing serum eHSP90α levels, reflecting its anticancer efficacy. HH01 also modulated tumor immunity by reducing M2 macrophages and reinvigorating immune T-cells. Additionally, HH01 showed low aggregation propensity, high water solubility, and a half-life time of >18 days in mouse blood. It was not cytotoxic to retinal pigmented epithelial cells and showed no obvious toxicity in mouse organs. Our data suggest that targeting eHSP90α with HH01 antibody can be a promising novel strategy for PDAC therapy.

Background: The ongoing COVID-19 pandemic has caused more than 193,825 deaths during the past few months. A quick-to-be-identified cure for the disease will be a therapeutic medicine that has prior use experiences in patients in order to resolve the current pandemic situation before it could become worsening. Artificial intelligence (AI) technology is hereby applied to identify the marketed drugs with potential for treating COVID-19. Methods: An AI platform was established to identify potential old drugs with anti-coronavirus activities by using two different learning databases; one consisted of the compounds reported or proven active against SARS-CoV, SARS-CoV-2, human immunodeficiency virus, influenza virus, and the other one containing the known 3C-like protease inhibitors. All AI predicted drugs were then tested for activities against a feline coronavirus in in vitro cell-based assay. These assay results were feedbacks to the AI system for relearning and thus to generate a modified AI model to search for old drugs again. Results: After a few runs of AI learning and prediction processes, the AI system identified 80 marketed drugs with potential. Among them, 8 drugs (bedaquiline, brequinar, celecoxib, clofazimine, conivaptan, gemcitabine, tolcapone, and vismodegib) showed in vitro activities against the proliferation of a feline infectious peritonitis (FIP) virus in Fcwf-4 cells. In addition, 5 other drugs (boceprevir, chloroquine, homoharringtonine, tilorone, and salinomycin) were also found active during the exercises of AI approaches. Conclusion: Having taken advantages of AI, we identified old drugs with activities against FIP coronavirus. Further studies are underway to demonstrate their activities against SARS-CoV-2 in vitro and in vivo at clinically achievable concentrations and doses. With prior use experiences in patients, these old drugs if proven active against SARS-CoV-2 can readily be applied for fighting COVID-19 pandemic.

Background: New therapeutic options to address the ongoing coronavirus disease 2019 (COVID-19) pandemic are urgently needed. One possible strategy is the repurposing of existing drugs approved for other indications as antiviral agents for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Due to the commercial unavailability of SARS-CoV-2 drugs for treating COVID-19, we screened approximately 250 existing drugs or pharmacologically active compounds for their inhibitory activities against feline infectious peritonitis coronavirus (FIPV) and human coronavirus OC43 (HCoV-OC43), a human coronavirus in the same genus (Betacoronavirus) as SARS-CoV-2. Methods: FIPV was proliferated in feline Fcwf-4 cells and HCoV-OC43 in human HCT-8 cells. Viral proliferation was assayed by visualization of cytopathic effects on the infected Fcwf-4 cells and immunofluorescent assay for detection of the nucleocapsid proteins of HCoV-OC43 in the HCT-8 cells. The concentrations (EC50) of each drug necessary to diminish viral activity to 50% of that for the untreated controls were determined. The viabilities of Fcwf-4 and HCT-8 cells were measured by crystal violet staining and MTS/PMS assay, respectively. Results: Fifteen out of the 252 drugs or pharmacologically active compounds screened were found to be active against both FIPV and HCoV-OC43, with EC50 values ranging from 11 nM to 75 μM. They are all old drugs as follows, anisomycin, antimycin A, atovaquone, chloroquine, conivaptan, emetine, gemcitabine, homoharringtonine, niclosamide, nitazoxanide, oligomycin, salinomycin, tilorone, valinomycin, and vismodegib. Conclusion: All of the old drugs identified as having activity against FIPV and HCoV-OC43 have seen clinical use in their respective indications and are associated with known dosing schedules and adverse effect or toxicity profiles in humans. Those, when later confirmed to have an anti-viral effect on SARS-CoV-2, should be considered for immediate uses in COVID-19 patients.

Nitro-fatty acids are a class of endogenous electrophilic lipid mediators with anti-inflammatory and cytoprotective effects in a wide range of inflammatory and fibrotic disease models. While these beneficial biological effects of nitro-fatty acids are mainly attributed to their ability to form covalent adducts with proteins, only a small number of proteins are known to be nitro-alkylated and the scope of protein nitro-alkylation remains undetermined. Here we describe the synthesis and application of a clickable nitro-fatty acid probe for the detection and first global identification of mammalian proteins that are susceptible to nitro-alkylation. 184 high confidence nitro-alkylated proteins were identified in THP1 macrophages, majority of which are novel targets of nitro-fatty acids, including extended synaptotagmin 2 (ESYT2), signal transducer and activator of transcription 3 (STAT3), toll-like receptor 2 (TLR2), retinoid X receptor alpha (RXRα) and glucocorticoid receptor (NR3C1). In particular, we showed that 9-nitro-oleate covalently modified and inhibited dexamethasone binding to NR3C1. Bioinformatic analyses revealed that nitro-alkylated proteins are highly enriched in endoplasmic reticulum and transmembrane proteins, and are overrepresented in lipid metabolism and transport pathways. This study significantly expands the scope of protein substrates targeted by nitro-fatty acids in living cells and provides a useful resource towards understanding the pleiotropic biological roles of nitro-fatty acids as signaling molecules or as multi-target therapeutic agents.

The CXC chemokine receptor type 4 (CXCR4) receptor and its ligand, CXCL12, are overexpressed in various cancers and mediate tumor progression and hypoxia-mediated resistance to cancer therapy. While CXCR4 antagonists have potential anticancer effects when combined with conventional anticancer drugs, their poor potency against CXCL12/CXCR4 downstream signaling pathways and systemic toxicity had precluded clinical application. Herein, BPRCX807, known as a safe, selective, and potent CXCR4 antagonist, has been designed and experimentally realized. In in vitro and in vivo hepatocellular carcinoma mouse models it can significantly suppress primary tumor growth, prevent distant metastasis/cell migration, reduce angiogenesis, and normalize the immunosuppressive tumor microenvironment by reducing tumor-associated macrophages (TAMs) infiltration, reprogramming TAMs toward an immunostimulatory phenotype and promoting cytotoxic T cell infiltration into tumor. Although BPRCX807 treatment alone prolongs overall survival as effectively as both marketed sorafenib and anti-PD-1, it could synergize with either of them in combination therapy to further extend life expectancy and suppress distant metastasis more significantly. [ABSTRACT FROM AUTHOR]

Here we report for the first time the use of fit quality (FQ), a ligand efficiency (LE) based measure for virtual screening (VS) of compound libraries. The LE based VS protocol was used to screen an in-house database of 125,000 compounds to identify aurora kinase A inhibitors. First, 20 known aurora kinase inhibitors were docked to aurora kinase A crystal structure (PDB ID: 2W1C); and the conformations of docked ligand were used to create a pharmacophore (PH) model. The PH model was used to screen the database compounds, and rank (PH rank) them based on the predicted IC50 values. Next, LE_Scale, a weight-dependant LE function, was derived from 294 known aurora kinase inhibitors. Using the fit quality (FQ = LE/LE_Scale) score derived from the LE_Scale function, the database compounds were reranked (PH_FQ rank) and the top 151 (0.12% of database) compounds were assessed for aurora kinase A inhibition biochemically. This VS protocol led to the identification of 7 novel hits, with compound 5 showing aurora kinase A IC50 = 1.29 µM. Furthermore, testing of 5 against a panel of 31 kinase reveals that it is selective toward aurora kinase A & B, with <50% inhibition for other kinases at 10 µM concentrations and is a suitable candidate for further development. Incorporation of FQ score in the VS protocol not only helped identify a novel aurora kinase inhibitor, 5, but also increased the hit rate of the VS protocol by improving the enrichment factor (EF) for FQ based screening (EF = 828), compared to PH based screening (EF = 237) alone. The LE based VS protocol disclosed here could be applied to other targets for hit identification in an efficient manner. [ABSTRACT FROM AUTHOR]

The homology modeling technique has been used to construct the structure of enterovirus 71 (EV 71) capsid protein VP1. The protein is consisted of 297 amino acid residues and treated as the target. The amino acid sequence identity between the target protein and sequences of template proteins 1EAH, 1PIV, and 1D4M searched from NCBI protein BLAST and WorkBench protein tools were 38, 37, and 36%, respectively. Based on these template structures, the protein model was constructed by using the InsightII/Homology program. The protein model was briefly refined by energy minimization and molecular dynamics (MD) simulation steps. The protein model was validated using some web available servers such as ERRAT, PROCHECK, PROVE, and PROSA2003. However, an inconsistency between the docking scores and the measured activity was observed for a series of EV 71 VP1 inhibitors synthesized by Shia et al. (J Med Chem 2002, 45, 1644) and docked into the binding pocket of the protein model using the DOCK 4.0.2 program. The protein model with an EV 71 VP1 inhibitor docked and engulfed was then refined further by some MD simulation steps in the presence of water molecules. The docking scores obtained for these inhibitors after such a MD refinement were well correlated with the activities. The structure–activity relationships for the ligand–protein model system was also analyzed using the GRID-VOLSURF programs and the corresponding noncrossvalidated and crossvalidated (by leave-one-out) r2 and q2 were 0.99 and 0.61, respectively. The hydrophobic nature of the binding pocket of the protein model was also examined using the GRID21 program. The possibility of improving the potency of the current series of EV 71 VP1 inhibitors was discussed based on all the studies presented. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1556–1570, 2006 [ABSTRACT FROM AUTHOR]

Wheat grass is one of the most widely used health foods, but its functional components and mechanisms remain unexplored. Herein, wheatgrass-derived oligosaccharides (WG-PS3) were isolated and found to induce CD69 and Th1 cytokine expression in human peripheral blood mononuclear cells. In particular, WG-PS3 directly activated the purified monocytes by inducing the expression of CD69, CD80, CD86, IL-12, and TNF-α but affectedNKand T cells only in the presence of monocytes. After further purification and structural analysis, maltoheptaose was identified from WG-PS3 as an immunomodulator. Maltoheptaose activated monocytes via Toll-like receptor 2 (TLR-2) signaling, as discovered by pretreatment of blocking antibodies against Toll-like receptors (TLRs) and also determined by click chemistry. This study is the first to reveal the immunostimulatory component of wheatgrass with well defined molecular structures and mechanisms. [ABSTRACT FROM AUTHOR]