Discovery of SARS-CoV-2 antiviral drugs through large-scale compound repurposing - PubMed (original) (raw)

. 2020 Oct;586(7827):113-119.

doi: 10.1038/s41586-020-2577-1. Epub 2020 Jul 24.

Shuofeng Yuan # 2 3 4, Xin Yin 1, Laura Martin-Sancho 1, Naoko Matsunaga 1, Lars Pache 1, Sebastian Burgstaller-Muehlbacher 5, Paul D De Jesus 1, Peter Teriete 1, Mitchell V Hull 6, Max W Chang 7, Jasper Fuk-Woo Chan 2 3 4, Jianli Cao 2 3 4, Vincent Kwok-Man Poon 2 3 4, Kristina M Herbert 1, Kuoyuan Cheng 8 9, Tu-Trinh H Nguyen 6, Andrey Rubanov 1, Yuan Pu 1, Courtney Nguyen 1, Angela Choi 10 11 12, Raveen Rathnasinghe 10 11 12, Michael Schotsaert 10 11, Lisa Miorin 10 11, Marion Dejosez 13, Thomas P Zwaka 13, Ko-Yung Sit 14, Luis Martinez-Sobrido 15, Wen-Chun Liu 10 11, Kris M White 10 11, Mackenzie E Chapman 16, Emma K Lendy 17, Richard J Glynne 18, Randy Albrecht 10 11, Eytan Ruppin 8, Andrew D Mesecar 16 17, Jeffrey R Johnson 10, Christopher Benner 7, Ren Sun 19, Peter G Schultz 6, Andrew I Su 20, Adolfo García-Sastre 10 11 21 22, Arnab K Chatterjee 23, Kwok-Yung Yuen 24 25 26, Sumit K Chanda 27

Affiliations

Discovery of SARS-CoV-2 antiviral drugs through large-scale compound repurposing

Laura Riva et al. Nature. 2020 Oct.

Erratum in

Abstract

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 has triggered an ongoing global pandemic of the severe pneumonia-like disease coronavirus disease 2019 (COVID-19)1. The development of a vaccine is likely to take at least 12-18 months, and the typical timeline for approval of a new antiviral therapeutic agent can exceed 10 years. Thus, repurposing of known drugs could substantially accelerate the deployment of new therapies for COVID-19. Here we profiled a library of drugs encompassing approximately 12,000 clinical-stage or Food and Drug Administration (FDA)-approved small molecules to identify candidate therapeutic drugs for COVID-19. We report the identification of 100 molecules that inhibit viral replication of SARS-CoV-2, including 21 drugs that exhibit dose-response relationships. Of these, thirteen were found to harbour effective concentrations commensurate with probable achievable therapeutic doses in patients, including the PIKfyve kinase inhibitor apilimod2-4 and the cysteine protease inhibitors MDL-28170, Z LVG CHN2, VBY-825 and ONO 5334. Notably, MDL-28170, ONO 5334 and apilimod were found to antagonize viral replication in human pneumocyte-like cells derived from induced pluripotent stem cells, and apilimod also demonstrated antiviral efficacy in a primary human lung explant model. Since most of the molecules identified in this study have already advanced into the clinic, their known pharmacological and human safety profiles will enable accelerated preclinical and clinical evaluation of these drugs for the treatment of COVID-19.

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Conflict of interest statement

Competing interest statement

JFWC has received travel grants from Pfizer Corporation Hong Kong and Astellas Pharma Hong Kong Corporation Limited and was an invited speaker for Gilead Sciences Hong Kong Limited and Luminex Corporation. The funding sources had no role in study design, data collection, analysis or interpretation or writing of the report. AG-S is inventor in patent applications on antiviral compounds against SARS-CoV-2 unrelated to this study and owned by the Icahn School of Medicine at Mount Sinai. AK-C and SK-C are inventors on a patent application on repurposed antiviral compounds for SARS-CoV-2, and owned by Scripps Research and Sanford Burnham Prebys. U.S. Patent Application Serial No. 63/010630, entitled “METHODS AND COMPOSITIONS FOR ANTIVIRAL TREATMENT,” relates to aspects of this work and was filed on April 15, 2020. The corresponding authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. The other authors declared no conflict of interests.

Figures

Figure ED1.

Figure ED1.. High-throughput repositioning screens for SARS-CoV-2 antivirals.

(a-c) Data from preliminary LOPAC®1280 library primary screen. (d-f) Data from ReFRAME collection screen. (a, d) Log2 fold change (Log2FC) of ATP levels after normalization to the median of each plate for SARS-CoV-2 infected all positive (APY0201) and negative (DMSO) controls, as well as for non-infected cells, across all screening plates. Error bars represent mean ± SD for at least n=40 and n=376 (d) independent wells. (b, e) Correlation plot indicating the Log2FC of each compound of two replicate screens. (c, f) Distribution of activities for each compound according to the average of the log2FC of each replicate. Each datapoint indicates the Log2FC average of each drug in screen (black dots). Values corresponding to DMSO (orange dots), APY0201 (cyan dots) and non-infected cells (purple dots) are also represented. Red circles indicate the activities of selected compounds chosen for follow-up for the LOPAC®1280 screens. R squared value indicates the linear correlation coefficient for the replicates of LOPAC®1280 (b) and ReFRAME (e) screens.

Figure ED2.

Figure ED2.. Supplemental GSEA analysis.

Gene set enrichment analysis (GSEA) of primary screening data according to the average Z′ factor. GSEA enrichment plots of additional ten target classes that were enriched in the primary HTS assay are shown, including beta adrenoreceptor antagonists, platelet aggregation inhibitors, progesterone receptor agonists, protein synthesis inhibitors, phosphodiesterase inhibitors, angiotensin II 1 antagonists, GPIIB IIIA receptor antagonists, thromboxane A2 receptor antagonists, leucotriene B4 antagonists, serine protease inhibitors (_P_-value < 0.05, FDR q-value < 0.25). Z-scores distributions of compound activities within the screen are depicted below each plot (Ranked list metric). _P_-values were calculated as indicated in the materials and methods.

Figure ED3.

Figure ED3.. Enriched biological pathways and processes of putative antiviral compound targets

(a) Bar graph of enriched biological pathways and putative proteins targeted by the antiviral compounds identified by HTS analysis. Molecular targets contained within enriched GSEA classes, as well as those of the 326 compounds selected for validation, were assessed for enrichment of pathways and biological function. The x-axis corresponds to -log10(_P_-value) while the y-axis indicates the enriched terms. The analysis was performed using the online tool Metascape and _P_-values were calculated as indicated in the materials and methods. (b) Chemical epistasis analysis of GPCR agonists and antagonists on viral replication. Vero E3 cells were treated with antagonists of the serotonin receptor 1A (elopiprazole, 5 μM), serotonin receptor 1B (CGS-12066-A maleate, 2.5 μM), Dopamine D2 and D3 receptors (NAD 299 hydrochloride, 5 μM) and Platelet-Activating Factor (PAF) receptor (SDZ-62-434, 5 μM) and challenged with SARS-CoV-2. Infection was determined in the top panels as described in Figure 3. Similarly, Vero E6 cells where pretreated with an antagonist of the serotonin receptor 1A (quinelorane hydrochloride, 5 μM), serotonin receptor 1B (SB-616234-A, 2.5 μM), Dopamine D2 and D3 receptors (elopiprazole, 5 μM) and Platelet-Activating Factor (PAF) receptor (PAF, 5 μM), either alone or in combination (combo) with the corresponding antagonist (left panel). Cellular toxicity was measured through enumeration of cell numbers (bottom panels). Data are normalized to the average of DMSO-treated wells and represent mean ± SEM for n=3 independent experiments.

Figure ED4.

Figure ED4.. A cellular map of SARS-CoV-2 antiviral targets.

Reported targets or target classes of confirmed SARS-CoV-2 antiviral compounds (Table S1) were mapped to a cell based on known or inferred subcellular localization, function, and potential intersection with the viral life cycle.

Figure ED5.

Figure ED5.. Expression profiles of compound-targeted genes in human airway samples.

Expression profiles of ACE2, TMPRSS2, and indicated targets of putative antiviral compounds identified in the HTS screen was analyzed using previously reported single-cell RNA profiling data from human airway samples of healthy donors. Clustered heat maps show the fraction of gene-expressing cells separated by sampling locations (left panel) or cell type (right panel).

Figure ED6.

Figure ED6.. Cell number and IF relative to dose-response orthogonal validation in Vero E6 cells.

(a) Vero E6 cells were pre-treated for 16 h with increasing concentrations of the indicated compound and then infected with SARS-CoV-2 with MOI = 0.01. 24 h post-infection, cells were fixed, and immunostained, and imaged. For each condition, the total amount of cells stained with DAPI was calculated. Data are normalized to the average of DMSO-treated wells. The heatmap represents the normalized cell number of the indicated 21 compounds in dose-response, on a scale from 0 to 1, on the average of five independent experiments. Compounds are associated in clusters, based on their classification category. Concentrations are rounded. Corresponding antiviral activities of these compounds are shown in Fig. 3A. † Indicated compounds were evaluated at a concentration of 0.85 μM instead of 1 μM. (b) Representative immunofluorescence images corresponding to one of the three dose-responses illustrated in Figure 3. For each condition, the corresponding entire well is shown (4x objective). Scale bar=1.35 mm. (c) Dose-response curves for additional antiviral compounds. Vero E6 cells were pre-treated for 16 h with increasing concentrations of the indicated compound and then infected with SARS-CoV-2 with MOI = 0.01 in the presence of the compound. 24 h post-infection, cells were fixed, and an immunofluorescence was performed. For each condition, the percentage of infection was calculated as the ratio between the number of infected cells stained for CoV NP and the total amount of cells stained with DAPI. Dose-response curves for both infectivity (black) and cell number (red) are shown. Data are normalized to the average of DMSO-treated wells and represent mean ± SEM for n=5 independent experiments. * indicates compounds for which EC50 values were calculated based on observed values at the highest concentrations.

Figure ED7.

Figure ED7.. Dose-response curves of additional antiviral compounds in 293T and Huh-7-ACE2 expressing cells.

HEK-293T (a) and Huh-7 cells (b), both transduced with ACE2, were pre-treated for 16 h with increasing concentrations of the indicated compound and then infected with SARS-CoV-2 with MOI = 0.3, in the presence of the compound. 24 h post-infection, cells were fixed, and immunostained, followed by imaging. For each condition, the percentage of infection was calculated as the ratio between the number of infected cells stained for CoV NP and the total amount of cells stained with DAPI. Compound concentrations range between 1 nM and 2.5 μM with 3-fold dilutions. Dose-response curves for both infectivity (black) and cell number (red) are shown. Data are normalized to the average of DMSO-treated wells and represent mean ± SEM for n=4 independent experiments. EC50 for each compound was calculated as 4-parameter logistic non-linear regression model and are indicated.

Figure ED8.

Figure ED8.. In vitro protease assay on SARS-CoV-2 papain-like protease (PLpro) and main protease (Mpro).

Purified SARS-CoV-2 Mpro (A) and SARS-CoV-2 PLpro (B) enzymes were incubated with varying concentrations of each compound, ranging from 1 to 50 μM. Activity of purified SARS-CoV-2 Mpro and SARS-CoV-2 PLpro enzymes was measured using the UIVT-3 peptide substrate (HiLyte Fluor488TM-ESATLQSGLRKAK-QXL520TM-NH2) and the peptide substrate Arg-Leu-Arg-Gly-Gly-AMC (RLRGG-AMC) respectively. Enzyme activity in the absence (zero percent inhibition control) and presence of compounds were used to calculate the percent inhibition at each compound concentration. Data are presented as mean ±SD for n=3 independent experiments.

Figure ED9.

Figure ED9.. Cell viability in human iPSC-derived pneumocyte-like cells.

(a-c) MTT assay performed on human iPSC-derived pneumocyte-like cells corresponding to the ones used for infectivity assay in Figure 5c–e. Data represents mean ± SEM for n=3 (DMSO, ONO-5334 (a), MDL 28170 (b) and apilimod (c)) and n=2 (remdesivir) biological replicates.

Figure ED10.

Figure ED10.. Triaging strategy and workflow.

An overview of the down-selection strategy and accompanying selection criteria for the study is shown.

Figure 1.

Figure 1.. High-throughput ReFRAME collection repositioning screen for SARS-CoV-2 antivirals.

(a) A schematic of the screening strategy employed for the repositioning analysis of the ReFRAME library. Classification of the approximately 12,000 compounds in the ReFRAME collection across different stages of clinical development is depicted in the pie chart. For the HTS screen, compounds were pre-spotted in 384-well plates at a final concentration of 5 μM. 3,000 Vero E6 cells were added to each well and pre-incubated with each compound for 16 h, followed by infection with a clinical isolate of SARS-CoV-2 (HKU-001a) with MOI of 0.01. ATP levels in each well were measured 72 h post-infection using a Cell Titer Glo viability assay as a surrogate measurement of viral cytopathic effect (CPE). (b) Z-scores after normalization to the median of each plate for all positive (APY0201) and negative (DMSO) controls, as well as for non-infected cells, across all the screening plates are shown. Error bars represent mean ± SD for n=376 independent wells (at least). (c) Correlation plot indicates the activity (Z-score) of each compound in the two replicate screens. (d) The activity distribution of each compound based on the average of the Z-score of each replicate is also presented. Each dot indicates the Z-score of each drug in each replicate of the screen (black dots). Values corresponding to DMSO (orange dots), APY0201 (cyan dots) and non-infected cells (purple dots) are also represented. R squared indicate the linear correlation coefficients for the replicates (b, e).

Figure 2.

Figure 2.. Gene set enrichment analysis and target gene expression.

(a) Enriched targets and mechanisms of action of potential antiviral compounds were determined through Gene Set Enrichment Analysis (GSEA). GSEA enrichment plots provide the distribution of the enrichment score (green line) across compounds that were annotated to molecular targets, ranked in order of antiviral activities (left to right). Vertical black lines reflect the positioning of each compound within a specific target class across the ranked dataset, where again, the leftmost position indicates most potent antiviral activity (red), and the rightmost position indicates inactivity in the HTS screen (blue). Enriched target clusters are shown, including retinoic acid receptor agonist, benzodiazepine receptor inhibitor, aldose reductase agonist, potassium channel agonist, cholesterol inhibitor, and antimalarials (_P_-value < 0.05, FDR q-value < 0.33). Additional enriched target classes are shown in Figure ED2. _P_-values were calculated as indicated in the materials and methods. (b) Chemical epistasis analysis of Retinoic Acid Receptor Agonist Antiviral Activity. Vero E3 cells were treated with 5 μM of the RAR agonist tazarotene and challenged with SARS-CoV-2, and infection was determined as described in Figure 3. Similarly, Vero E6 cells where pretreated with 5 μM of the RAR antagonist Ro41-5253, either alone or in combination with 5 μM of tazarotene (left panel). Cellular toxicity was measured through enumeration of cell numbers (right panel). Data are normalized to the average of DMSO-treated wells and represent mean ± SEM for n=3 independent experiments. One-way ANOVA followed by Dunnett post-test was performed as statistical analysis. ** P ≤ 0.01, *** P ≤ 0.001.

Figure 3.

Figure 3.. Dose-response relationships of selected antiviral compounds and synergy with remdesivir.

(a-c) Vero E6 cells were pre-treated for 16 h with increasing concentrations of the indicated compound and then infected with SARS-CoV-2 at MOI = 0.01. 24 h post-infection, cells were fixed, and immunofluorescence imaging was performed. For each condition, the percentage of infection was calculated as the ratio between the number of infected cells stained for CoV NP and the total amount of cells stained with DAPI. (a) Heatmap representing normalized infection of the indicated 21 compounds in dose-response, on a scale from 0 to 1, depicting the average of n=5 independent experiments. Compounds are grouped in predicted function clusters. † concentration of 0.85 μM instead of 1 μM at the second highest dose. Extrapolated EC50 values are listed on the left of the heatmap. (b) Dose-response analysis of most potent compounds in (a) are shown, depicting both infectivity (black), cell number (red), and cellular EC50 values (also see ED6). (c) Compounds at indicated doses were combined with 800 nM remdesivir or a negative control (DMSO), and antiviral dose response relationships were determined in Vero E6 cells using experimental conditions described in (b). 800 nM remdesivir alone inhibited viral infection by 20 % (black dotted line). Predicted additive combinatorial activity of remdesvir and indicated compound (see materials and methods) is denoted by red dotted line. Observed activity of remdesivir in combination with the indicated compound is shown with a solid red line, and shaded portions of graph indicate differential of predicted and observed combinatorial activities. EC50s for compound alone (black lettering), predicted (pink lettering), and observed (red lettering) are also presented. Data are normalized to the average of DMSO-treated wells and represent mean ± SEM for n=3 (apilimod, MDL 28170, Z LVG CHN2, VBY-825, and SL-11128) (b,c) and n=5 (ONO 5334 ,clofazimine, DS-6930 and R82913) (b) independent experiments. * indicates compounds for which EC50 values were calculated based on observed values at the highest concentrations.

Figure 4.

Figure 4.. Apilimod and protease inhibitors block SARS-CoV-2 entry.

(a) Time-of-addition assay. To synchronize infection, Vero E6 were infected for 1 h with SARS-CoV-2, and the inoculum was then removed. Cells were also incubated with the indicated compound at a concentration of 2.5 μM at timepoints indicated. Infection was quantified 10 hpi after fixation and staining for CoV NP. Data are normalized to the average of DMSO-treated wells for each corresponding time point and are presented as mean ± SEM for n=3 independent experiments. Two-way ANOVA followed by Tukey post-test was performed as statistical analysis. Bafilomycin was used as a positive control. (b) Virus-like particle (VLP) assay. Vero E6 cells were pre-treated for 2 h with the indicated compounds (2.5 μM) and then infected for 2 h with SARS-CoV-2, MERS or VSV pseudotyped particles harboring firefly luciferase (see Materials and Methods). Inoculum was removed after another 2 h, and Firefly Luciferase signal was quantified 24 h post-inoculation. Error bars represent SEM for n=2 independent experiments. One-way ANOVA followed by Dunnett post-test was performed as statistical analysis. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001, **** P ≤ 0.0001.

Figure 5.

Figure 5.. Assessment of antiviral activity in human cell models.

HEK-293T (a) and Huh-7 cells (b) transduced with ACE2 were pre-treated for 16 h with increasing concentrations of the indicated compound and then infected with SARS-CoV-2 (MOI = 0.3). 24 h post-infection, cells were fixed, and immunostained, and imaged by immunofluorescent microscopy. For each condition, the percentage of infection was calculated as the ratio between the number of infected cells stained for CoV NP and the total amount of cells stained with DAPI. Compound concentrations ranged between 1 nM and 2.5 μM. Dose-response curves for infectivity (black) and cell number (red) are shown. Data are normalized to the average of DMSO-treated wells and represent mean ± SEM for n=4 independent experiments. EC50 for each compound was calculated as 4-parameter logistic non-linear regression model and is indicated. (c-e) iPSC-derived pneumocytes were incubated with 5 μM of the indicated compound two hours prior to infection, and then infected with 105 pfu of SARS-CoV-2. Two days post infection, cells were harvested, and viral infection was quantified by flow-cytometry (Cov NP staining). Data represent mean ± SEM for n=3 biological replicates. One-way ANOVA followed by Dunnett post-test was performed as statistical analysis. (f-g) Ex vivo lung tissues were infected with SARS-CoV-2 with an inoculum of 5×105 PFU. After two hours, the inoculum was removed, and the indicated compound was added at a 5 μM concentration. 24 hours post-infection, supernatants were collected for quantification of viral titer by plaque assay (f) and cells harvested for quantification of intracellular viral RNA (g). Error bars represent SEM for n=3 biological replicates. One-way ANOVA followed by Dunnett post-test was performed as statistical analysis. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001, **** P ≤ 0.0001.

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