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Fig. 4 | BMC Biology

Fig. 4

From: A phenomics approach for antiviral drug discovery

Fig. 4

Identification of phenomics profiles of antiviral drugs efficient against coronavirus. a Unsupervised hierarchical clustering of morphological profiles of the indicated samples based on their proximity in feature space. Three main groups are shown, infected (+CoV-229E) in the presence of non-active compounds, i.e. Camostat, Favipiravir and Cathepsin L inhibitor, as well as control DMSO (vehicle); non-infected (-CoV-229E) in the presence of all compounds; and +CoV-229E in the presence of the compounds that displayed antiviral effect, i.e. Remdesivir, E-64d, TH3289, TH6477 and TH5487. For this analysis, all compound doses were mean averaged, with the exception of the 30 μM doses for TH3289, TH6744 and TH5487, and all doses of Bafilomycin A1, which resulted in cytotoxicity. Pearson’s correlation coefficients are indicated for each compound and calculated in comparison to DMSO in the absence or presence of CoV-229E. The profiles represent the aggregated mean per compound from two biological replicates and one (for Low dose) or two (for Mid and High doses) technical replicates. bg PCA analysis of morphological features upon treatment with Remdesivir, E-64d, TH3289, TH6477, TH5487 and Camostat in non-infected (-CoV-229E) and infected (+CoV-229E) conditions compared to DMSO control. Each dot in the PCA represents one image by taking the mean of all objects in the image. Each data point corresponds to the aggregated image mean from one (for Low dose) or two (for Mid and High doses) technical replicates, and two biological replicates. Percentage of variance explained is indicated by %

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