Use of Tox21 Screening Data to Evaluate the COVID-19 Drug Candidates for Their Potential Toxic Effects and Related Pathways

Currently, various potential therapeutic agents for coronavirus disease-2019 (COVID-19), a global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are being investigated worldwide mainly through the drug repurposing approach. Several anti-viral, anti-bacterial, anti-malarial, and anti-inflammatory drugs were employed in randomized trials and observational studies for developing new therapeutics for COVID-19. Although an increasing number of repurposed drugs have shown anti-SARS-CoV-2 activities in vitro, so far only remdesivir has been approved by the US FDA to treat COVID-19, and several other drugs approved for Emergency Use Authorization, including sotrovimab, tocilizumab, baricitinib, paxlovid, molnupiravir, and other potential strategies to develop safe and effective therapeutics for SARS-CoV-2 infection are still underway. Many drugs employed as anti-viral may exert unwanted side effects (i.e., toxicity) via unknown mechanisms. To quickly assess these drugs for their potential toxicological effects and mechanisms, we used the Tox21 in vitro assay datasets generated from screening ∼10,000 compounds consisting of approved drugs and environmental chemicals against multiple cellular targets and pathways. Here we summarize the toxicological profiles of small molecule drugs that are currently under clinical trials for the treatment of COVID-19 based on their in vitro activities against various targets and cellular signaling pathways.

Identification of Selective CYP3A7 and CYP3A4 Substrates and Inhibitors Using a High-Throughput Screening Platform

Cytochrome P450 (CYP) 3A7 is one of the major xenobiotic metabolizing enzymes in human embryonic, fetal, and newborn liver. CYP3A7 expression has also been observed in a subset of the adult population, including pregnant women, as well as in various cancer patients. The characterization of CYP3A7 is not as extensive as other CYPs, and health authorities have yet to provide guidance towards DDI assessment. To identify potential CYP3A7-specific molecules, we used a P450-Glo CYP3A7 enzyme assay to screen a library of ∼5,000 compounds, including FDA-approved drugs and drug-like molecules, and compared these screening data with that from a P450-Glo CYP3A4 assay. Additionally, a subset of 1,000 randomly selected compounds were tested in a metabolic stability assay. By combining the data from the qHTS P450-Glo and metabolic stability assays, we identified several chemical features important for CYP3A7 selectivity. Halometasone was chosen for further evaluation as a potential CYP3A7-selective inhibitor using molecular docking. From the metabolic stability assay, we identified twenty-two CYP3A7-selective substrates over CYP3A4 in supersome setting. Our data shows that CYP3A7 has ligand promiscuity, much like CYP3A4. Furthermore, we have established a large, high-quality dataset that can be used in predictive modeling for future drug metabolism and interaction studies.

Targeting CAR and Nrf2 improves cyclophosphamide bioactivation while reducing doxorubicin-induced cardiotoxicity in triple-negative breast cancer treatment

Cyclophosphamide (CPA) and doxorubicin (DOX) are key components of chemotherapy for triple-negative breast cancer (TNBC), although suboptimal outcomes are commonly associated with drug resistance and/or intolerable side effects. Through an approach combining high-throughput screening and chemical modification, we developed CN06 as a dual activator of the constitutive androstane receptor (CAR) and nuclear factor erythroid 2-related factor 2 (Nrf2). CN06 enhances CAR-induced bioactivation of CPA (a prodrug) by provoking hepatic expression of CYP2B6, while repressing DOX-induced cytotoxicity in cardiomyocytes in vitro via stimulating Nrf2-antioxidant signaling. Utilizing a multicellular coculture model incorporating human primary hepatocytes, TNBC cells, and cardiomyocytes, we show that CN06 increased CPA/DOX-mediated TNBC cell death via CAR-dependent CYP2B6 induction and subsequent conversion of CPA to its active metabolite 4-hydroxy-CPA, while protecting against DOX-induced cardiotoxicity by selectively activating Nrf2-antioxidant signaling in cardiomyocytes but not in TNBC cells. Furthermore, CN06 preserves the viability and function of human iPSC-derived cardiomyocytes by modulating antioxidant defenses, decreasing apoptosis, and enhancing the kinetics of contraction and relaxation. Collectively, our findings identify CAR and Nrf2 as potentially novel combined therapeutic targets whereby CN06 holds the potential to improve the efficacy/toxicity ratio of CPA/DOX-containing chemotherapy.

[Effects and mechanism of negative pressure microenvironment on the neogenesis of human umbilical vein endothelial cells]

Objective: To investigate the effects and mechanism of negative pressure microenvironment on the neogenesis of human umbilical vein endothelial cells (HUVECs). Methods: The experimental research methods were adopted. The third to the fifth passage of HUVECs in the logarithmic growth stage were used for the subsequent experiments. Three batches of cells were taken, with each batch of cells being divided into normal control group and negative pressure treatment alone group (both routinely cultured for 24 h), and 17-allylamino-17-demethoxy-geldanamycin (17-AAG) alone group and 17-AAG+negative pressure treatment group (both cultured with 17-AAG for 24 h). In addition, the intermittent negative pressure suction, with the negative pressure value of -5.33 kPa (suction for 30 s, pause for 10 s) was continuously applied for 8 h on cells in the two negative pressure treatment groups using an automatic three-dimensional cell gradient negative pressure loading device designed and developed by ourselves. After the treatment of the first batch of cells, the cell proliferation level was detected by cell counting kit 8 method at 0 (immediately), 24, 48, and 72 h of culture, with the number of samples being 6. After the treatment of the second batch of cells, the scratch experiment was performed. At 12 h after scratching, the cell migration was observed under an inverted phase contrast microscope and the cell migration rate was calculated, with the number of samples being 3. After the treatment of the third batch of cells, the tubule formation experiment was conducted. After 6 h of culture, the tubulogenesis was observed under an inverted phase contrast microscope and the total tubule length and the number of branch nodes of cells were calculated, with the number of samples being 3. The cells were taken and divided into normal control group, negative pressure treatment alone group, and 17-AAG+negative pressure treatment group. The cells were treated the same as in the previous corresponding group. After the treatment, Western blotting was used to detect the protein expressions of heat shock protein 90 (HSP90), caveolin 1, endothelial nitric oxide synthase (eNOS), and eNOS phosphorylation site 1177 in the cells, and the eNOS phosphorylation site 1177/eNOS ratio was calculated, with the number of samples being 3; co-immunoprecipitation (co-precipitating HSP90 and caveolin 1, caveolin 1 and eNOS) and Western blotting were used to detect the protein expressions of caveolin 1 and eNOS in the cells, with the number of samples being 3; the protein co-localization of HSP90 and caveolin 1 and that of caveolin 1 and eNOS in the cells was assessed by immunofluorescence double staining. The molecular docking prediction of caveolin 1 and eNOS was processed by HADDOCK 2.4 protein-protein docking program. Data were statistically analyzed with analysis of variance for factorial design, one-way analysis of variance, and least significant difference method. Results: Compared with that in normal control group, the cell proliferation level in 17-AAG alone group was significantly decreased at culture hour of 24, 48, and 72 after the treatment (P<0.01), while the cell proliferation level in negative pressure treatment alone group was significantly increased at culture hour of 24, 48, and 72 after the treatment (P<0.01). Compared with that in 17-AAG alone group, the cell proliferation level in 17-AAG+negative pressure treatment group was significantly increased at culture hour of 48 and 72 after the treatment (P<0.05 or P<0.01). Compared with that in negative pressure treatment alone group, the cell proliferation level in 17-AAG+negative pressure treatment group was significantly decreased at culture hour of 24, 48, and 72 after the treatment (P<0.01). At 12 h after scratching, compared with (39.9±2.7)% in normal control group, the cell migration rate in 17-AAG alone group was significantly decreased ((10.7±2.7)%, P<0.01), while the cell migration rate in negative pressure treatment alone group was significantly increased ((61.9±2.4)%, P<0.01). Compared with those in 17-AAG alone group, the cell migration rate in 17-AAG+negative pressure treatment group was significantly increased ((37.7±3.7)%, P<0.01). Compared with that in negative pressure treatment alone group, the cell migration rate in 17-AAG+negative pressure treatment group was significantly decreased (P<0.01). At culture hour of 6 after the treatment, compared with those in normal control group, the total length of the tube formed by the cells in 17-AAG alone group was significantly shortened (P<0.05) and the number of branch nodes was significantly reduced (P<0.05), while the total length of the tube formed by the cells in negative pressure treatment alone group was significantly prolonged (P<0.01) and the number of branch nodes was dramatically increased (P<0.01). Compared with that in 17-AAG alone group, the number of branch nodes of the tube formed by the cells was significantly increased in 17-AAG+negative pressure treatment group (P<0.05). Compared with those in negative pressure treatment alone group, the total length of the tube formed by the cells in 17-AAG+negative pressure treatment group was significantly shortened (P<0.01) and the number of branch nodes was significantly reduced (P<0.01). Western blotting detection showed that after treatment, the overall comparison of eNOS and caveolin 1 protein expressions among the three groups of cells showed no statistically significant differences (P>0.05). The expression of HSP90 protein and the eNOS phosphorylation site 1177/eNOS ratio in the cells of negative pressure treatment alone group were significantly increased (P<0.01) compared with those in normal control group. Compared with those in negative pressure treatment alone group, the HSP90 protein expression and the eNOS phosphorylation site 1177/eNOS ratio in the cells of 17-AAG+negative pressure treatment group were significantly decreased (P<0.01). Co-immunoprecipitation and Western blotting detection after the treatment showed that compared with those in normal control group, the expression of caveolin 1 protein in the cells of negative pressure treatment alone group was significantly increased (P<0.01), while the protein expression of eNOS was significantly decreased (P<0.05). Compared with those in negative pressure treatment alone group, the expression of caveolin 1 protein in the cells of 17-AAG+negative pressure treatment group was significantly decreased (P<0.01), while the protein expression of eNOS was significantly increased (P<0.01). After the treatment, compared with those in normal control group, the co-localization of HSP90 and caveolin 1 protein in the cells of negative pressure treatment alone group was significantly increased, while the co-localization of caveolin 1 and eNOS protein was significantly decreased. Compared with those in negative pressure treatment alone group, the co-localization of HSP90 and caveolin 1 protein in the cells of 17-AAG+negative pressure treatment group was significantly decreased, while the co-localization of caveolin 1 and eNOS protein was significantly increased. Molecular docking prediction suggested that caveolin 1 interacted strongly with eNOS and inhibited the 1177 site phosphorylation of eNOS. Conclusions: The negative pressure microenvironment may inhibit the binding of caveolin 1 to eNOS by promoting the binding of HSP90 to caveolin 1 in HUVECs, so as to relieve the inhibition of 1177 site phosphorylation of eNOS by caveolin 1, thereby promoting the proliferation, migration, and tubulogenesis of HUVECs, and ultimately promoting the neogenesis of HUVECs.

Retro Drug Design: From Target Properties to Molecular Structures

To deliver more therapeutics to more patients more quickly and economically is the ultimate goal of pharmaceutical researchers. The advent and rapid development of artificial intelligence (AI), in combination with other powerful computational methods in drug discovery, makes this goal more practical than ever before. Here, we describe a new strategy, retro drug design, or RDD, to create novel small-molecule drugs from scratch to meet multiple predefined requirements, including biological activity against a drug target and optimal range of physicochemical and ADMET properties. The molecular structure was represented by an atom typing based molecular descriptor system, optATP, which was further transformed to the space of loading vectors from principal component analysis. Traditional predictive models were trained over experimental data for the target properties using optATP and shallow machine learning methods. The Monte Carlo sampling algorithm was then utilized to find the solutions in the space of loading vectors that have the target properties. Finally, a deep learning model was employed to decode molecular structures from the solutions. To test the feasibility of the algorithm, we challenged RDD to generate novel kinase inhibitors from random numbers with five different ADMET properties optimized at the same time. The best Tanimoto similarity score between the generated valid structures and the available 4,314 kinase inhibitors was < 0.50, indicating a high extent of novelty of the generated compounds. From the 3,040 structures that met all six target properties, 20 were selected for synthesis and experimental measurement of inhibition activity over 97 representative kinases and the ADMET properties. Fifteen and eight compounds were determined to be hits or strong hits, respectively. Five of the six strong kinase inhibitors have excellent experimental ADMET properties. The results presented in this paper illustrate that RDD has the potential to significantly improve the current drug discovery process.

Identification of environmental chemicals that activate p53 signaling after in vitro metabolic activation

Currently, approximately 80,000 chemicals are used in commerce. Most have little-to-no toxicity information. The U.S. Toxicology in the 21st Century (Tox21) program has conducted a battery of in vitro assays using a quantitative high-throughput screening (qHTS) platform to gain toxicity information on environmental chemicals. Due to technical challenges, standard methods for providing xenobiotic metabolism could not be applied to qHTS assays. To address this limitation, we screened the Tox21 10,000-compound (10K) library, with concentrations ranging from 2.8 nM to 92 µM, using a p53 beta-lactamase reporter gene assay (p53-bla) alone or with rat liver microsomes (RLM) or human liver microsomes (HLM) supplemented with NADPH, to identify compounds that induce p53 signaling after biotransformation. Two hundred and seventy-eight compounds were identified as active under any of these three conditions. Of these 278 compounds, 73 gave more potent responses in the p53-bla assay with RLM, and 2 were more potent in the p53-bla assay with HLM compared with the responses they generated in the p53-bla assay without microsomes. To confirm the role of metabolism in the differential responses, we re-tested these 75 compounds in the absence of NADPH or with heat-attenuated microsomes. Forty-four compounds treated with RLM, but none with HLM, became less potent under these conditions, confirming the role of RLM in metabolic activation. Further evidence of biotransformation was obtained by measuring the half-life of the parent compounds in the presence of microsomes. Together, the data support the use of RLM in qHTS for identifying chemicals requiring biotransformation to induce biological responses.

Repurposing drugs as COVID-19 therapies: a toxicity evaluation

Drug repurposing is an appealing method to address the Coronavirus 2019 (COVID-19) pandemic because of the low cost and efficiency. We analyzed our in-house database of approved drug screens and compared their activity profiles with results from a severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) cytopathic effect (CPE) assay. The activity profiles of the human ether-à-go-go-related gene (hERG), phospholipidosis (PLD), and many cytotoxicity screens were found significantly correlated with anti-SARS-CoV-2 activity. hERG inhibition is a nonspecific off-target effect that has contributed to promiscuous drug interactions, whereas drug-induced PLD is an undesirable effect linked to hERG blockers. Thus, this study identifies preferred drug candidates as well as chemical structures that should be avoided because of their potential to induce toxicity. Lastly, we highlight the hERG liability of anti-SARS-CoV-2 drugs currently enrolled in clinical trials.

Efficient Identification of Anti-SARS-CoV-2 Compounds Using Chemical Structure- and Biological Activity-Based Modeling

Identification of anti-SARS-CoV-2 compounds through traditional high-throughput screening (HTS) assays is limited by high costs and low hit rates. To address these challenges, we developed machine learning models to identify compounds acting via inhibition of the entry of SARS-CoV-2 into human host cells or the SARS-CoV-2 3-chymotrypsin-like (3CL) protease. The optimal classification models achieved good performance with area under the receiver operating characteristic curve (AUC-ROC) values of >0.78. Experimental validation showed that the best performing models increased the assay hit rate by 2.1-fold for viral entry inhibitors and 10.4-fold for 3CL protease inhibitors compared to those of the original drug repurposing screens. Twenty-two compounds showed potent (<5 μM) antiviral activities in a SARS-CoV-2 live virus assay. In conclusion, machine learning models can be developed and used as a complementary approach to HTS to expand compound screening capacities and improve the speed and efficiency of anti-SARS-CoV-2 drug discovery.

A Quantitative High-Throughput Screening Data Analysis Pipeline for Activity Profiling

The U.S. Tox21 program has developed in vitro assays to test large collections of environmental chemicals in a quantitative high-throughput screening (qHTS) format, using triplicate 15-dose titrations to generate over 100 million data points to date. Counterscreens are also employed to minimize interferences from non-target-specific assay artifacts, such as compound autofluorescence and cytotoxicity. New data analysis approaches are needed to integrate these data and characterize the activities observed from these assays. Here, we describe a complete analysis pipeline that evaluates these qHTS data for technical quality in terms of signal reproducibility. We integrate signals from repeated assay runs, primary readouts and counterscreens to produce a final call on on-target compound activity.

A gene expression biomarker for predictive toxicology to identify chemical modulators of NF-κB

The nuclear factor-kappa B (NF-κB) is a transcription factor with important roles in inflammation, immune response, and oncogenesis. Dysregulation of NF-κB signaling is associated with inflammation and certain cancers. We developed a gene expression biomarker predictive of NF-κB modulation and used the biomarker to screen a large compendia of gene expression data. The biomarker consists of 108 genes responsive to tumor necrosis factor α in the absence but not the presence of IκB, an inhibitor of NF-κB. Using a set of 450 profiles from cells treated with immunomodulatory factors with known NF-κB activity, the balanced accuracy for prediction of NF-κB activation was > 90%. The biomarker was used to screen a microarray compendium consisting of 12,061 microarray comparisons from human cells exposed to 2,672 individual chemicals to identify chemicals that could cause toxic effects through NF-κB. There were 215 and 49 chemicals that were identified as putative or known NF-κB activators or suppressors, respectively. NF-κB activators were also identified using two high-throughput screening assays; 165 out of the ~3,800 chemicals (ToxCast assay) and 55 out of ~7,500 unique compounds (Tox21 assay) were identified as potential activators. A set of 32 chemicals not previously associated with NF-κB activation and which partially overlapped between the different screens were selected for validation in wild-type and NFKB1-null HeLa cells. Using RT-qPCR and targeted RNA-Seq, 31 of the 32 chemicals were confirmed to be NF-κB activators. These results comprehensively identify a set of chemicals that could cause toxic effects through NF-κB.

A224 COVID-19 INFECTION IN LIVER TRANSPLANT RECIPIENTS: CLINICAL FEATURES, HOSPITALIZATION, AND MORTALITY FROM A CANADIAN MULTICENTRE COHORT

Background

The COVID-19 pandemic has brought significant challenges to clinicians caring for liver transplant (LT) recipients. Researchers have sought to better understand the risk and clinical outcomes of LT recipients infected with COVID-19 globally, however, there is a paucity of data from within Canada.

Aims

Our multi-center study aims to examine the characteristics and clinical outcomes of LT patients with COVID-19 in Canada.

Methods

We identified a retrospective cohort of adult LT recipients with RT-PCR confirmed COVID-19 from 7 Canadian tertiary care centers between March 2020 and June 2021. Demographic and clinical data were compiled by clinicians within those centers. We identified liver enzyme profile at the time of COVID-19 infection, immunosuppression type and post-infection adjustments, rate of hospitalization, ICU admission, mechanical ventilation, and death.

Results

A total of 49 patients with a history of LT and COVID-19 infection were identified. Twenty nine patients (59%) were male, the median time from LT was 66 months (1, 128) and the median age at COVID-19 infection was 59 years (52, 65). At COVID-19 diagnosis, the median ALT was 37 U/L (21, 41), AST U/L was 34 (20, 37), ALP U/L was 156 (88, 156), Total Bilirubin was 11 umol/L (7, 14), and INR was 1.1 (1.0, 1.1). The majority of patients (92%) were on tacrolimus monotherapy or a combination of tacrolimus and mycophenolate mofetil (MMF); median tacrolimus level at COVID-19 diagnosis was 5.3 ug/L (4.0, 8.1). Immunosuppression was modified in 8 (16%) patients post-infection; either the tacrolimus dose was reduced or MMF was held. One patient developed acute cellular rejection which recovered after re-initiation of the prior regimen. Eighteen patients (37%) required hospitalization, 6 (12%) were treated with dexamethasone, and 3 (6%) required ICU admission and mechanical ventilation. Four patients (8%) died due to complications of COVID-19. On univariate analysis, neither age, sex, co-morbidities nor duration post-transplant were associated with risk of hospitalization.

Conclusions

In our national retrospective study, approximately 40% of patients required hospitalization with a mortality rate of &lt; 10%. Previous studies have shown proximity to LT as an independent factor for mortality with COVID-19; the median time from LT for our patients was 5 years, which may explain the lower mortality rate. Of note, the median tacrolimus levels were much lower in comparison to the target of 8–10 ug/L used in the first year post-transplant. As the landscape of COVID-19 changes with vaccination, evolving treatments, and increasing rates of variant transmission, additional studies are required to continue identifying trends in clinical outcomes.

Funding Agencies

None

Activation of Functional Somatic Stem Cells Promotes Endogenous Tissue Regeneration

Periodontal ligament derived stem cells (PDLSCs) are capable of differentiating into multiple cell types and inducing a promising immunomodulation for tissue regeneration and disease treatment. However, it is still challenging to develop a practical approach to activate endogenous stem cells for tissue self-healing and regeneration. In this study, transcriptome analysis reveals that resveratrol promotes PDLSC stemness through activation of stem cell, osteoprogenitor, and chondroprogenitor markers. Self-renewal and multipotent differentiation abilities are also improved in resveratrol-treated PDLSCs. In addition, immunomodulation of PDLSCs is dramatically increased after resveratrol treatment. Mechanistically, we show that resveratrol activates ERK/WNT crosstalk through elevation of olfactory and growth factor signaling pathways to upregulate the expression levels of RUNX2 and FASL for osteogenesis and immunomodulation, respectively. By using a periodontitis animal model, administration of resveratrol partially rescues bone loss through activation of endogenous somatic stem cells and inhibition of inflammatory T-cell infiltration. Taken together, our findings identify a novel pharmacological approach to achieve autotherapies for endogenous tissue regeneration.

High-Throughput Chemical Screening and Structure-Based Models to Predict hERG Inhibition

Simple Summary

Cardiovascular disease is the leading cause of death for people of most ethnicities in the United States. The human ether-a-go-go-related gene (hERG) potassium channel plays a pivotal role in cardiac rhythm regulation, and cardiotoxicity associated with hERG inhibition by drug molecules and environmental chemicals is a major public health concern. An evaluation of the effect of environmental chemicals on hERG channel function can help inform the potential public health risks of these compounds. To assess the cardiotoxic effect of diverse drugs and environmental compounds, the Tox21 federal research program has screened a collection of 9667 chemicals for inhibitory activity against the hERG channel. A set of molecular descriptors covering physicochemical and structural properties of chemicals, self-organizing maps, and hierarchical clustering were applied to characterize the chemicals inhibiting hERG. Machine learning approaches were applied to build robust statistical models that can predict the probability of any new chemical to cause cardiotoxicity via this mechanism.

Abstract

Chemical inhibition of the human ether-a -go-go-related gene (hERG) potassium channel leads to a prolonged QT interval that can contribute to severe cardiotoxicity. The adverse effects of hERG inhibition are one of the principal causes of drug attrition in clinical and pre-clinical development. Preliminary studies have demonstrated that a wide range of environmental chemicals and toxicants may also inhibit the hERG channel and contribute to the pathophysiology of cardiovascular (CV) diseases. As part of the US federal Tox21 program, the National Center for Advancing Translational Science (NCATS) applied a quantitative high throughput screening (qHTS) approach to screen the Tox21 library of 10,000 compounds (~7871 unique chemicals) at 14 concentrations in triplicate to identify chemicals perturbing hERG activity in the U2OS cell line thallium flux assay platform. The qHTS cell-based thallium influx assay provided a robust and reliable dataset to evaluate the ability of thousands of drugs and environmental chemicals to inhibit hERG channel protein, and the use of chemical structure-based clustering and chemotype enrichment analysis facilitated the identification of molecular features that are likely responsible for the observed hERG activity. We employed several machine-learning approaches to develop QSAR prediction models for the assessment of hERG liabilities for drug-like and environmental chemicals. The training set was compiled by integrating hERG bioactivity data from the ChEMBL database with the Tox21 qHTS thallium flux assay data. The best results were obtained with the random forest method (~92.6% balanced accuracy). The data and scripts used to generate hERG prediction models are provided in an open-access format as key in vitro and in silico tools that can be applied in a translational toxicology pipeline for drug development and environmental chemical screening.

Identification of Compounds for Butyrylcholinesterase Inhibition

Butyrylcholinesterase (BChE) is a nonspecific cholinesterase enzyme that hydrolyzes choline-based esters. BChE plays a critical role in maintaining normal cholinergic function like acetylcholinesterase (AChE) through hydrolyzing acetylcholine (ACh). Selective BChE inhibition has been regarded as a viable therapeutic approach in Alzheimer's disease. As of now, a limited number of selective BChE inhibitors are available. To identify BChE inhibitors rapidly and efficiently, we have screened 8998 compounds from several annotated libraries against an enzyme-based BChE inhibition assay in a quantitative high-throughput screening (qHTS) format. From the primary screening, we identified a group of 125 compounds that were further confirmed to inhibit BChE activity, including previously reported BChE inhibitors (e.g., bambuterol and rivastigmine) and potential novel BChE inhibitors (e.g., pancuronium bromide and NNC 756), representing diverse structural classes. These BChE inhibitors were also tested for their selectivity by comparing their IC50 values in BChE and AChE inhibition assays. The binding modes of these compounds were further studied using molecular docking analyses to identify the differences between the interactions of these BChE inhibitors within the active sites of AChE and BChE. Our qHTS approach allowed us to establish a robust and reliable process to screen large compound collections for potential BChE inhibitors.

Discovery and characterization of potent And-1 inhibitors for cancer treatment

Acidic nucleoplasmic DNA-binding protein 1 (And-1), an important factor for deoxyribonucleic acid (DNA) replication and repair, is overexpressed in many types of cancer but not in normal tissues. Although multiple independent studies have elucidated And-1 as a promising target gene for cancer therapy, an And-1 inhibitor has yet to be identified. Using an And-1 luciferase reporter assay to screen the Library of Pharmacologically Active Compounds (LOPAC) in a high throughput screening (HTS) platform, and then further screen the compound analog collection, we identified two potent And-1 inhibitors, bazedoxifene acetate (BZA) and an uncharacterized compound [(E)-5-(3,4-dichlorostyryl)benzo[c][1,2]oxaborol-1(3H)-ol] (CH3), which specifically inhibit And-1 by promoting its degradation. Specifically, through direct interaction with And-1 WD40 domain, CH3 interrupts the polymerization of And-1. Depolymerization of And-1 promotes its interaction with E3 ligase Cullin 4B (CUL4B), resulting in its ubiquitination and subsequent degradation. Furthermore, CH3 suppresses the growth of a broad range of cancers. Moreover, And-1 inhibitors re-sensitize platinum-resistant ovarian cancer cells to platinum drugs in vitro and in vivo. Since BZA is an FDA approved drug, we expect a clinical trial of BZA-mediated cancer therapy in the near future. Taken together, our findings suggest that targeting And-1 by its inhibitors is a potential broad-spectrum anti-cancer chemotherapy regimen.

Immunoglobulin D Multiple Myeloma with a “Hidden” Lambda Light Chain

Introduction/Objective

In rare cases, the conventional immunofixation gel electrophoresis technique fails to detect the light chain of an M-protein. We report a case of immunoglobulin (Ig) D multiple myeloma with a hidden lambda (λ) light chain.

Methods/Case Report

Capillary electrophoresis (CE) (Sebia CAPILLARYS 2) was used to detect and quantify M- proteins in serum specimens. Immunosubtraction (IS) on the CAPILLARYS 2 systems was used to identify the classes of M-proteins. Conventional gel immunofixation electrophoresis (IFE) was performed, using monospecific antisera for IgD, IgE, kappa (κ) or λ in the Sebia HYDRASYS system, and IgG, IgA, IgM, κ or λ in the Helena SPIFE3000 system. Beta-mercaptoethanol (BME) with Fluidil were used as reduction agents.

Results (if a Case Study enter NA)

Results of serum CE showed two abnormal peaks in beta 2 and gamma regions, suspected to be positive for M-proteins. IS results showed subtraction for λ light chain only in both peaks, suggesting two monoclonal λ light chains. In contrary, no monoclonal λ light chain was detected in gamma region by IFE (Sebia). Epitope masking in the folded monoclonal protein was suspected to cause the “hidden λ light chain” and was further investigated by two laboratory approaches. IFE performed on the Helena SPIFE3000 system found two λ bands in beta 2 and gamma regions, which was consistent with the results from IS. The treatment of BME with Fluidil helped unmasking the hidden epitope and revealed the λ band in gamma region on IFE (Sebia).

Conclusion

The medical laboratories should be aware of the described scenario. The failure to detect light chains of certain intact M-proteins is most likely due to the structurally inaccessibility of light chains. It is recommended that treatment with reduction agents or use of an alternative methodology or IS might be helpful for investigating suspected heavy chain only cases, due to the limitation of conventional methodology.

High-throughput screening assays for SARS-CoV-2 drug development: Current status and future directions

In response to the ongoing coronavirus disease 2019 (COVID-19) pandemic, a panel of assays has been developed and applied to screen collections of approved and investigational drugs for anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) activity in a quantitative high-throughput screening (qHTS) format. In this review, we applied data-driven approaches to evaluate the ability of each assay to identify potential anti-SARS-CoV-2 leads. Multitarget assays were found to show advantages in terms of accuracy and efficiency over single-target assays, whereas target-specific assays were more suitable for investigating compound mechanisms of action. Moreover, strict filtering with counter screens might be more detrimental than beneficial in identifying true positives. Thus, developing novel HTS assays acting simultaneously against multiple targets in the SARS-CoV-2 life cycle will benefit anti-COVID-19 drug discovery.

[Identification and genetic analysis of new mutations in EYA1 gene of BOS syndrome]

Objective: To analyze the clinical manifestations of a patient with branchiootic syndrome(BOS) and her families and to carry out genetic testing in order to specify the biological pathogenesis. Methods: Clinical data of the patient and her families were collected. Genomic DNA in the peripheral blood of the proband and her family members was extracted. All exons of 406 deafness-related susceptible genes as well as their flanking regions were sequenced by high-throughput sequencing, and the mutation sites of the proband and her parents were validated by Sanger sequencing. Results: There were nine members in three generations, of whom four presented with hearing loss, preauricular fistula and branchial fistula which met the diagnostic criteria of BOS. Proband and her mother presented with auricle malformation and inner ear malformation. And no one had abnormalities in the kidneys of all the patients. Pedigree analysis revealed that the mode of inheritance in the family was consistent with the autosomal dominant pattern. Mutational analysis showed that all the affected patients detected a heterozygous frameshift variation c.1255delT in the EYA1 gene, which had not been reported. Genotype and phenotype were co-isolated in this family. Such a frameshift variation produced a premature termination codon, thereby causing premature termination of translation (p.C419VFS*12). ACMG identified that the mutation was pathogenic. This mutation was novel and not detected in controls. A heterozygous missense variation mutation c.403G>A(p.G135S) in EYA1 gene was also detected in three members of this family. ACMG identified that the mutation clinical significance was uncertain. However, two of whom were normal, which seemed the disease was not caused by this mutation in this family. Conclusions: A novel frameshift mutation in EYA1(c.1255delT) is the main molecular etiology of BOS in the Chinese family. This study expands the mutational spectrum of EYA1 gene. The clinical manifestations are heterogeneous among patients in this family. The diagnosis of BOS should combine gene tests with clinical phenotypes analysis.

Development of Robust Quantitative Structure-Activity Relationship Models for CYP2C9, CYP2D6, and CYP3A4 Catalysis and Inhibition

Cytochrome P450 enzymes are responsible for the metabolism of >75% of marketed drugs, making it essential to identify the contributions of individual cytochromes P450 to the total clearance of a new candidate drug. Overreliance on one cytochrome P450 for clearance levies a high risk of drug-drug interactions; and considering that several human cytochrome P450 enzymes are polymorphic, it can also lead to highly variable pharmacokinetics in the clinic. Thus, it would be advantageous to understand the likelihood of new chemical entities to interact with the major cytochrome P450 enzymes at an early stage in the drug discovery process. Typical screening assays using human liver microsomes do not provide sufficient information to distinguish the specific cytochromes P450 responsible for clearance. In this regard, we experimentally assessed the metabolic stability of ∼5000 compounds for the three most prominent xenobiotic metabolizing human cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4, and used the data sets to develop quantitative structure-activity relationship models for the prediction of high-clearance substrates for these enzymes. Screening library included the NCATS Pharmaceutical Collection, comprising clinically approved low-molecular-weight compounds, and an annotated library consisting of drug-like compounds. To identify inhibitors, the library was screened against a luminescence-based cytochrome P450 inhibition assay; and through crossreferencing hits from the two assays, we were able to distinguish substrates and inhibitors of these enzymes. The best substrate and inhibitor models (balanced accuracies ∼0.7), as well as the data used to develop these models, have been made publicly available (https://opendata.ncats.nih.gov/adme) to advance drug discovery across all research groups. SIGNIFICANCE STATEMENT: In drug discovery and development, drug candidates with indiscriminate cytochrome P450 metabolic profiles are considered advantageous, since they provide less risk of potential issues with cytochrome P450 polymorphisms and drug-drug interactions. This study developed robust substrate and inhibitor quantitative structure-activity relationship models for the three major xenobiotic metabolizing cytochromes P450, i.e., CYP2C9, CYP2D6, and CYP3A4. The use of these models early in drug discovery will enable project teams to strategize or pivot when necessary, thereby accelerating drug discovery research.

Association between periodontal disease and prostate cancer: a systematic review and meta-analysis

Background

Periodontal disease is a chronic infectious disease caused by bacterial infection which may lead to various systematic diseases. Recently, increasing studies have explored the correlation of periodontal disease with the risk of prostate cancer. However, the findings were inconsistent. Hence, this study aims to investigate the association between periodontal disease and the risk of prostate cancer by a meta-analysis.

Material and Methods

PubMed, EMBASE, and Cochrane were searched for publications up to July 17, 2020. Cohort and case-control studies evaluating the risk of prostate cancer in patients with periodontal disease were included. A fixed or random-effect model was used to calculate the summary relative risk (RR) along with 95% confidence interval (CI). All analyses were conducted using Stata 12.0 software.

Results

Seven studies were included in the final analysis. The pooled estimates showed that periodontal disease was significantly associated with the risk of prostate cancer (RR = 1.17; 95% CI = 1.07-1.27; P = 0.001). Findings of sensitivity analyses proved that the overall results were robust.

Conclusions

Periodontal disease may be considered as a potential risk factor for prostate cancer. Although it’s a possibility, males should be more aware of their oral health and implement effective measures to prevent and treat periodontal disease.

Key words:Periodontal disease, periodontitis, prostate cancer, meta-analysis

AI-based language models powering drug discovery and development

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

A Universal and High-Throughput Proteomics Sample Preparation Platform

Major advances have been made to improve the sensitivity of mass analyzers, spectral quality, and speed of data processing enabling more comprehensive proteome discovery and quantitation. While focus has recently begun shifting toward robust proteomics sample preparation efforts, a high-throughput proteomics sample preparation is still lacking. We report the development of a highly automated universal 384-well plate sample preparation platform with high reproducibility and adaptability for extraction of proteins from cells within a culture plate. Digestion efficiency was excellent in comparison to a commercial digest peptide standard with minimal sample loss while improving sample preparation throughput by 20- to 40-fold (the entire process from plated cells to clean peptides is complete in ∼300 min). Analysis of six human cell types, including two primary cell samples, identified and quantified ∼4,000 proteins for each sample in a single high-performance liquid chromatography (HPLC)-tandem mass spectrometry injection with only 100-10K cells, thus demonstrating universality of the platform. The selected protein was further quantified using a developed HPLC-multiple reaction monitoring method for HeLa digests with two heavy labeled internal standard peptides spiked in. Excellent linearity was achieved across different cell numbers indicating a potential for target protein quantitation in clinical research.

[Effects and mechanisms of polycaprolactone-cellulose acetate nanofiber scaffold loaded with rat epidermal stem cells on wound healing of full-thickness skin defects in rats]

Objective: To explore the effects and mechanisms of polycaprolactone-cellulose acetate (PCL-CA) nanofiber scaffold loaded with rat epidermal stem cells (ESCs) on wound healing of full-thickness skin defects in rats. Methods: The experiment research method was applied. The primary ESCs were isolated from 1-3 d old Sprague-Dawley (SD) rats (undefined gender) by rapid adherent method and cultured by rapid adherent method. ESCs of the first passage were used for the subsequent experiments after the positive expressions of integrin β₁ and cytokeratin 19 (CK19) in primary cells were identified respectively by flow cytometey and immunofluorescence method. PCL-CA nanofiber scaffolds with polycaprolactone and cellulose acetate as components were prepared by electrospinning technique. The topological structure of the nanofiber scaffolds was determined and the diameter of 25 fibers was measured by scanning electron microscope. The constructed PCL-CA nanofiber scaffolds were used as the culture substrate for ESCs, which were cultured in keratinocytes (KCs) medium to construct ESCs-nanofiber scaffold complex (hereinafter referred to as ESCs scaffold). After 3 days of culture, the morphology of ESCs in the scaffold and their relationship was observed by scanning electron microscopy. The ESCs in ESCs scaffold were set as PCL-CA nanofiber scaffold group, and the ESCs cultured with KCs medium in culture dishes coated with type Ⅳ collagen were set as type Ⅳ collagen group. Western blotting was used to detect the protein expression level of CK19 in ESCs in the two groups after 3 days of culture (n=3). The protein expressions of CK19 and proliferating nuclear antigen (PCNA) in ESCs in the two groups were detected by immunofluorescence method after 7 days of culture. A circular full-thickness skin wound of about 2 cm in diameter was prepared on both left and right sides of the back of 15 male SD rats aged 6-8 weeks. The rats were then equally divided into blank control group without implantation, scaffold alone group implanted with PCL-CA nanofiber scaffold, and ESCs scaffold group implanted with ESCs scaffold which were constructed after 3 days of culture according to the random number table. The percentage of wound areas on post injury day (PID) 3, 7, 14, and 21 was calculated (n=5). The new skin tissue at the wound edge was collected on PID 21, the wound healing quality was evaluated by Masson staining, and the protein expression levels of Notch1, Jagged1, and Hes1, which are key proteins of Notch signaling pathway, were detected by Western blotting (n=3). Data were statistically analyzed with one-way analysis of variance, one-way analysis of variance, analysis of variance for repeated measurement, independent sample t test, and Bonferroni correction. Results: The constructed PCL-CA nanofiber scaffolds had a porous, mesh-like, and multilayered three-dimensional structure, in which the surface of the fibers was smooth and non-porous, and the fiber diameter was (383±24) nm. The ESCs in ESCs scaffold showed intact cellular structures and were tightly attached to the scaffold after 3 days of culture. The cells were interconnected and fully extended on the surface of the scaffold to form a membrane. After 3 days of culture, the protein expression level of CK19 of ESCs in PCL-CA nanofiber scaffold group was significantly higher than that in type Ⅳ collagen group (t=24.56, P<0.01). After 7 days of culture, compared with those in type Ⅳ collagen group, there was no significant change in the proportion of PCNA positive cells of ESCs in PCL-CA nanofiber scaffold group, while the proportion of CK19 positive cells was higher. On PID 3, 7, 14, and 21, the percentages of wound areas of rats in ESCs scaffold group were (78.0±1.8)%, (40.9±2.0)%, (17.9±1.1)%, and (5.0±1.0)%, respectively, which were significantly lower than (84.2±1.9)%, (45.4±2.6)%, (21.8±1.7)%, and (10.1±1.1)% in blank control group (t=5.42, 3.09, 4.33, 7.58, P<0.05 or P<0.01) and (82.7±1.2)%, (44.8±2.0)%, (22.4±2.4)%, and (10.3±2.4)% in scaffold alone group (t=4.98, 3.11, 3.84, 4.57, P<0.05 or P<0.01), while the percentages of wound areas of rats between blank control group and scaffold alone group were similar (t=1.47, 0.39, 0.47, 0.22, P>0.05). On PID 21, the layer of new skin at the wound edge of rats in each group was intact; compared with that in blank control group or scaffold alone group, the new skin tissue at the wound edge of rats in ESCs scaffold group had more orderly collagen arrangement; the scaffolds in the new skin at the wound edge of rats were completely degraded in ESCs scaffold group and scaffold alone group. On PID 21, the protein expression levels of Notch1, Jagged1, and Hes1 in the new skin tissue at the wound edge of rats in scaffold alone group were similar to those in blank control group (t=1.70, 1.94, 0.18, P>0.05), while the protein expression levels of Notch1, Jagged1, and Hes1 in the new skin tissue at the wound edge of rats in ESCs scaffold group were significantly higher than those in scaffold alone group (t=13.31, 22.07, 20.71, P<0.01). Conclusions: PCL-CA nanofiber scaffolds can inhibit the differentiation of ESCs of rats without affecting their proliferation in vitro. ESCs scaffolds constructed through using PCL-CA nanofiber scaffolds as the carrier to culture ESCs of rats can significantly promote the wound healing of full-thickness skin defects in rats, and the mechanism may be related to the activation of Notch signaling pathway.

[Aryl hydrocarbon receptor modulates airway inflammation in mice with cockroach allergen-induced asthma by regulating Th17/Treg differentiation]

OBJECTIVE

To investigate whether aryl hydrocarbon receptor (AhR) modulates cockroach allergen (CRE)-induced asthma by regulating Th17/Treg differentiation.

OBJECTIVE

Mouse models of CRE-induced asthma established by sensitizing and challenging the mice with CRE were randomized into asthma model group, AhR agonist group treated with TCDD (10 μg/ kg), and AhR antagonist group treated with TCDD and CH223191 (10 mg/kg) (n=5), with 5 mice without CRE challenge as the control group. The expressions of AhR, Cyp1a1 and Cyp1b1 mRNA in the lung tissues of the mice were detected using RT-PCR, and pulmonary inflammation was evaluated with immumohistochemical staining. The expressions of inflammatory cytokines in the lungs were detected using ELISA, and the expression of Treg in the lung tissues and pulmonary lymph nodes was analyzed with flow cytometry.

OBJECTIVE

Both TCDD and CH223191 were capable of modulating pulmonary expressions of AhR and its downstream genes Cyp1a1 and Cyp1b1 in asthmatic mice (P < 0.002). TCDD treatment significantly decreased inflammatory cells and mucus production in the lungs of asthmatic mice, and BALFs from TCDD-treated mice with CRE challenge contained lowered levels of the proinflammatory factors including IL-4, IL-13 and IL-17A (P < 0.001) but increased anti-inflammatory factors including IL-10, IL-22 and TGF-β1 (P < 0.001). All these changes were significantly reversed by treatment with CH223191 to the levels comparable with those in the asthma model group (P>0.05). More importantly, TCDD treatment significantly increased the number of Tregs cells and FOXP3 expression and lowered RORγt mRNA expression in the lungs and pulmonary lymph nodes in asthmatic mice (P < 0.001); inhibition of AhR with CH223191, as compared with TCDD, significantly decreased the expression of CD4⁺CD25⁺Foxp3⁺Treg cells in the lungs and pulmonary lymph nodes and the expression of FOXP3 mRNA in lymphocytes and increased RORγt mRNA expression (P < 0.001) to the levels comparable with those in asthma model group (P>0.05).

OBJECTIVE

AhR activation modulates airway inflammation in mice with CRE-induced asthma by modulating the differentiation of Th17/Treg.

Predictive Models to Identify Small Molecule Activators and Inhibitors of Opioid Receptors

Opioid receptors (OPRs) are the main targets for the treatment of pain and related disorders. The opiate compounds that activate these receptors are effective analgesics but their use leads to adverse effects, and they often are highly addictive drugs of abuse. There is an urgent need for alternative chemicals that are analgesics and to reduce/avoid the unwanted effects in order to relieve the public health crisis of opioid addiction. Here, we aim to develop computational models to predict the OPR activity of small molecule compounds based on chemical structures and apply these models to identify novel OPR active compounds. We used four different machine learning algorithms to build models based on quantitative high throughput screening (qHTS) data sets of three OPRs in both agonist and antagonist modes. The best performing models were applied to virtually screen a large collection of compounds. The model predicted active compounds were experimentally validated using the same qHTS assays that generated the training data. Random forest was the best classifier with the highest performance metrics, and the mu OPR (OPRM)-agonist model achieved the best performance measured by AUC-ROC (0.88) and MCC (0.7) values. The model predicted actives resulted in hit rates ranging from 2.3% (delta OPR-agonist) to 15.8% (OPRM-agonist) after experimental confirmation. Compared to the original assay hit rate, all models enriched the hit rate by ≥2-fold. Our approach produced robust OPR prediction models that can be applied to prioritize compounds from large libraries for further experimental validation. The models identified several novel potent compounds as activators/inhibitors of OPRs that were confirmed experimentally. The potent hits were further investigated using molecular docking to find the interactions of the novel ligands in the active site of the corresponding OPR.

Identification of hit compounds with anti-schistosomal activity on in vitro generated juvenile worms in cell-free medium

Background

Anthelminthic treatment options against schistosomiasis are limited. The current treatment relies almost exclusively on a single drug, praziquantel (PZQ). As a consequence, the development of resistance to PZQ and limited activity of PZQ against earlier development stages are respectively a risk and a limitation to achieving the goals of the new WHO roadmap towards elimination. For the discovery of new chemical starting points, the in vitro drug screening on Schistosoma mansoni (S. mansoni) against newly transformed schistosomula (NTS) is still the most predominant approach. The use of only NTS in the initial screening limits sensitivity to potential new compounds which are predominantly active in later developmental stages. Using our recently described highly standardized, straightforward and reliable culture method that generates high rates of juvenile worms, we aimed to repurpose a subset of the National Center for Advancing Translational Sciences (NCATS) Pharmaceutical Collection (340 compounds) to identify new hits with an in vitro worm culture assay.

Methodology/Principal findings

Cercariae were mechanically transformed into skin-stage (SkS) schistosomula and continuously cultured for 3–6 weeks to the liver stage (LiS). A commercial source of serum was identified, and decrease of NTS/well along with optimal drug testing conditions was established to test compounds on early and late LiS worms. The library was screened in 96-well format assays using praziquantel (PZQ) as a positive control. Primary screening allowed a 5.9% hit rate and generated two confirmed hits on adult worms; a prophylactic antianginal agent and an antihistaminic drug.

Conclusion

With this standardized and reliable in vitro assay, important S. mansoni developmental stages up to LiS worms can be generated and cultured over an extended period. When exposed to a subset of the NCATS Pharmaceutical Collection, 3 compounds yielded a defined anti-schistosomal phenotype on juvenile worms. Translation of activity on perfused adult S. mansoni worms was achieved only for perhexiline (a prophylactic antianginal agent) and astemizole (an antihistaminic drug).

Schistosomiasis continues to be a major public health problem, mainly in developing countries. Although there have been some advances in finding new drugs, praziquantel is still the drug of choice. Certainly, one of the most important advances in the search for new treatments was the ability to in vitro transform cercariae and to grow schistosomula in culture. To reduce animal use in future drug discovery efforts (3Rs), we optimized a previously established reliable and robust in vitro cell-free culture system for the generation of liver-stage worms that we applied to the screening of a compound library stemming from the National Center for Advancing Translational Sciences (NCATS) Pharmaceutical Collection.

Retro Drug Design: From Target Properties to Molecular Structures

To generate drug molecules of desired properties with computational methods is the holy grail in pharmaceutical research. Here we describe an AI strategy, retro drug design, or RDD, to generate novel small molecule drugs from scratch to meet predefined requirements, including but not limited to biological activity against a drug target, and optimal range of physicochemical and ADMET properties. Traditional predictive models were first trained over experimental data for the target properties, using an atom typing based molecular descriptor system, ATP. Monte Carlo sampling algorithm was then utilized to find the solutions in the ATP space defined by the target properties, and the deep learning model of Seq2Seq was employed to decode molecular structures from the solutions. To test feasibility of the algorithm, we challenged RDD to generate novel drugs that can activate μ opioid receptor (MOR) and penetrate blood brain barrier (BBB). Starting from vectors of random numbers, RDD generated 180,000 chemical structures, of which 78% were chemically valid. About 42,000 (31%) of the valid structures fell into the property space defined by MOR activity and BBB permeability. Out of the 42,000 structures, only 267 chemicals were commercially available, indicating a high extent of novelty of the AI-generated compounds. We purchased and assayed 96 compounds, and 25 of which were found to be MOR agonists. These compounds also have excellent BBB scores. The results presented in this paper illustrate that RDD has potential to revolutionize the current drug discovery process and create novel structures with multiple desired properties, including biological functions and ADMET properties. Availability of an AI-enabled fast track in drug discovery is essential to cope with emergent public health threat, such as pandemic of COVID-19.

New Limit for Neutrinoless Double-Beta Decay of ^{100}Mo from the CUPID-Mo Experiment

The CUPID-Mo experiment at the Laboratoire Souterrain de Modane (France) is a demonstrator for CUPID, the next-generation ton-scale bolometric 0νββ experiment. It consists of a 4.2 kg array of 20 enriched Li_{2}^{100}MoO_{4} scintillating bolometers to search for the lepton-number-violating process of 0νββ decay in ^{100}Mo. With more than one year of operation (^{100}Mo exposure of 1.17  kg×yr for physics data), no event in the region of interest and, hence, no evidence for 0νββ is observed. We report a new limit on the half-life of 0νββ decay in ^{100}Mo of T_{1/2}>1.5×10^{24}  yr at 90% C.I. The limit corresponds to an effective Majorana neutrino mass ⟨m_{ββ}⟩<(0.31-0.54)  eV, dependent on the nuclear matrix element in the light Majorana neutrino exchange interpretation.

Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma

High-risk neuroblastoma (NB) remains a significant therapeutic challenge facing current pediatric oncology patients. Structural variants such as gene fusions have shown an initial promise in enhancing mechanistic understanding of NB and improving survival rates. In this study, we performed a comprehensive in silico investigation on the translational ability of gene fusions for patient stratification and treatment development for high-risk NB patients. Specifically, three state-of-the-art gene fusion detection algorithms, including ChimeraScan, SOAPfuse, and TopHat-Fusion, were employed to identify the fusion transcripts in a RNA-seq data set of 498 neuroblastoma patients. Then, the 176 high-risk patients were further stratified into four different subgroups based on gene fusion profiles. Furthermore, Kaplan-Meier survival analysis was performed, and differentially expressed genes (DEGs) for the redefined high-risk group were extracted and functionally analyzed. Finally, repositioning candidates were enriched in each patient subgroup with drug transcriptomic profiles from the LINCS L1000 Connectivity Map. We found the number of identified gene fusions was increased from clinical the low-risk stage to the high-risk stage. Although the technical concordance of fusion detection algorithms was suboptimal, they have a similar biological relevance concerning perturbed pathways and regulated DEGs. The gene fusion profiles could be utilized to redefine high-risk patient subgroups with significant onset age of NB, which yielded the improved survival curves (Log-rank p value ≤ 0.05). Out of 48 enriched repositioning candidates, 45 (93.8%) have antitumor potency, and 24 (50%) were confirmed with either on-going clinical trials or literature reports. The gene fusion profiles have a discrimination power for redefining patient subgroups in high-risk NB and facilitate precision medicine-based drug repositioning implementation.

Metabolic syndrome cannot mask the changes of faecal microbiota compositions caused by primary hepatocellular carcinoma

Both hepatocellular carcinoma (HCC) and metabolic syndrome are closely associated with the composition of the gut microbiota (GM). Although it has been proposed that elements of the GM can be used as biomarkers for the early diagnosis of HCC, whether metabolic syndrome results in a misrepresentation of the results of the early diagnosis of HCC using GM remains unclear. We compared the differences in the faecal microbiota of 10 patients with primary HCC, six patients with type 2 diabetes mellitus (T2DM), seven patients with arterial hypertension, six patients with both HCC and T2DM, and 10 patients with both HCC and arterial hypertension, as well as 10 healthy subjects, using high-throughput sequencing of 16S rRNA gene amplicons. Our results revealed a significant difference in the GM between subjects with and without HCC. The 49 bacterial genera out of the 494 detected genera were significantly different between the groups. These results show that changes in the GM can be used to distinguish between subjects with and without HCC, and can resist interference of T2DM and arterial hypertension with the GM. The results of the present study provide an important basis for the clinical auxiliary diagnosis of HCC by detecting the GM.

Profiling the Tox21 Chemical Collection for Acetylcholinesterase Inhibition

BACKGROUND

Inhibition of acetylcholinesterase (AChE), a biomarker of organophosphorous and carbamate exposure in environmental and occupational human health, has been commonly used to identify potential safety liabilities. So far, many environmental chemicals, including drug candidates, food additives, and industrial chemicals, have not been thoroughly evaluated for their inhibitory effects on AChE activity. AChE inhibitors can have therapeutic applications (e.g., tacrine and donepezil) or neurotoxic consequences (e.g., insecticides and nerve agents).

OBJECTIVES

The objective of the current study was to identify environmental chemicals that inhibit AChE activity using in vitro and in silico models.

METHODS

To identify AChE inhibitors rapidly and efficiently, we have screened the Toxicology in the 21st Century (Tox21) 10K compound library in a quantitative high-throughput screening (qHTS) platform by using the homogenous cell-based AChE inhibition assay and enzyme-based AChE inhibition assays (with or without microsomes). AChE inhibitors identified from the primary screening were further tested in monolayer or spheroid formed by SH-SY5Y and neural stem cell models. The inhibition and binding modes of these identified compounds were studied with time-dependent enzyme-based AChE inhibition assay and molecular docking, respectively.

RESULTS

A group of known AChE inhibitors, such as donepezil, ambenonium dichloride, and tacrine hydrochloride, as well as many previously unreported AChE inhibitors, such as chelerythrine chloride and cilostazol, were identified in this study. Many of these compounds, such as pyrazophos, phosalone, and triazophos, needed metabolic activation. This study identified both reversible (e.g., donepezil and tacrine) and irreversible inhibitors (e.g., chlorpyrifos and bromophos-ethyl). Molecular docking analyses were performed to explain the relative inhibitory potency of selected compounds.

CONCLUSIONS

Our tiered qHTS approach allowed us to generate a robust and reliable data set to evaluate large sets of environmental compounds for their AChE inhibitory activity. https://doi.org/10.1289/EHP6993.

Mining of high throughput screening database reveals AP-1 and autophagy pathways as potential targets for COVID-19 therapeutics

The recent global pandemic of the Coronavirus disease 2019 (COVID-19) caused by the new coronavirus SARS-CoV-2 presents an urgent need for the development of new therapeutic candidates. Many efforts have been devoted to screening existing drug libraries with the hope to repurpose approved drugs as potential treatments for COVID-19. However, the antiviral mechanisms of action of the drugs found active in these phenotypic screens remain largely unknown. In an effort to deconvolute the viral targets in pursuit of more effective anti-COVID-19 drug development, we mined our in-house database of approved drug screens against 994 assays and compared their activity profiles with the drug activity profile in a cytopathic effect (CPE) assay of SARS-CoV-2. We found that the autophagy and AP-1 signaling pathway activity profiles are significantly correlated with the anti-SARS-CoV-2 activity profile. In addition, a class of neurology/psychiatry drugs was found to be significantly enriched with anti-SARS-CoV-2 activity. Taken together, these results provide new insights into SARS-CoV-2 infection and potential targets for COVID-19 therapeutics, which can be further validated by in vivo animal studies and human clinical trials.

Application of niclosamide and analogs as small molecule inhibitors of Zika virus and SARS-CoV-2 infection

Zika virus has emerged as a potential threat to human health globally. A previous drug repurposing screen identified the approved anthelminthic drug niclosamide as a small molecule inhibitor of Zika virus infection. However, as antihelminthic drugs are generally designed to have low absorption when dosed orally, the very limited bioavailability of niclosamide will likely hinder its potential direct repurposing as an antiviral medication. Here, we conducted SAR studies focusing on the anilide and salicylic acid regions of niclosamide to improve physicochemical properties such as microsomal metabolic stability, permeability and solubility. We found that the 5-bromo substitution in the salicylic acid region retains potency while providing better drug-like properties. Other modifications in the anilide region with 2′-OMe and 2′-H substitutions were also advantageous. We found that the 4′-NO₂ substituent can be replaced with a 4′-CN or 4′-CF₃ substituents. Together, these modifications provide a basis for optimizing the structure of niclosamide to improve systemic exposure for application of niclosamide analogs as drug lead candidates for treating Zika and other viral infections. Indeed, key analogs were also able to rescue cells from the cytopathic effect of SARS-CoV-2 infection, indicating relevance for therapeutic strategies targeting the COVID-19 pandemic.