Prediction and Experimental Evaluation of the hERG Blocking Potential of Drugs Showing Clinical Signs of Cardiotoxicity

Background:

A large scale experimental validation conducted at the National Center for Advancing Translational Sciences (NCATS/NIH, USA) confirmed the predictions of our 3D-SDAR model of hERG blockage and phospholipidosis induction. It was demonstrated that both hERG blockage and phospholipidosis induction are driven by a common three-center toxicophore composed of two aromatic rings and an amino group. This work extends our earlier efforts by predicting the hERG blocking potential of pharmaceuticals from two additional datasets: i) one comprised of 106 drugs with reported clinical signs of cardiotoxicity from the AZCERT database and ii) a dataset of 54 FDA-approved tyrosine kinase inhibitors (TKIs).

Methods:

A bagging-like 3D-SDAR algorithm aggregating predictions from 100 randomized models was used to predict the hERG blocking potential of all 160 drugs. All 106 drugs from the AZCERT dataset were furter evaluated for their hERG inhibition at NCATS using a thallium flux assay.

Results:

Comparison of the predicted hERG class against the results from the thallium flux qHTS assay resulted in an overall predictive accuracy of 0.736 and the area under the ROC curve of 0.780. Factors such as the generation of false negatives by the thallium flux assay, proximity to the cut-off, use of conformations that may differ from the biologically relevant ones, and the lack of structurally similar compounds in the modeling set could explain the somewhat reduced predictive performance compared to that of the original model. The original 3D-SDAR model was also used to evaluate the TKIs ability to block hERG. Comparing our predictions to class assignemts based on IC50 values with a 30 μM cut-off, an accuracy of 0.850, sensitivity of 0.906, and specificity of 0.625 were achieved.

Conclusion:

3D-SDAR provides a reliable platform for prediction of hERG blockage. Particular attention should be paid to all investigational new drugs containing our three-center hERG toxicophore, especially those having highly flexible molecules. Particular scrutiny should be given to the tyrosine kinase inhibitors, which represent a therapeutic class possessing all structural characteristics previously associated with an increased potential to block hERG.

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.