Estimation of virus-mediated cell fusion rate of SARS-CoV-2

Amidei, Ava; Dobrovolny, Hana M.

doi:10.1016/j.virol.2022.08.016

Cited by 5 publications

(2 citation statements)

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“…Quantifying the changes in the preference of the Omicron variant for different entry routes may help evaluate the efficacies of entry inhibitors in clinical development and optimise entry inhibitor-based treatments (Gunst et al, 2021; Zhuravel et al, 2021). Mathematical models of SARS-CoV-2 kinetics have provided valuable insights into COVID-19 disease progression, drug action, and the effectiveness of vaccines and treatments (Amidei and Dobrovolny, 2022; Chatterjee et al, 2022; Desikan et al, 2021; Garg et al, 2021; Gonçalves et al, 2020; Goyal et al, 2020; Ke et al, 2021; Kissler et al, 2021; Néant et al, 2021; Padmanabhan et al, 2022; Perelson and Ke, 2020). Here, adapting a previously developed mathematical model of SARS-CoV-2 entry (Padmanabhan et al, 2020) to the analysis of in vitro data on variants (Garcia-Beltran et al, 2021; Hoffmann and et al, 2021), we quantified the altered usage of host proteases required for entry by the Omicron variant relative to the original strain and the Delta variant.…”

Section: Discussionmentioning

confidence: 99%

Modelling how the altered usage of cell entry pathways by the SARS-CoV-2 Omicron variant may affect the efficacy and synergy of TMPRSS2 and Cathepsin B/L inhibitors

Padmanabhan

Dixit

2022

Preprint

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The SARS-CoV-2 Omicron variant appears to exhibit altered cell tropism and entry properties compared to other variants. Here, analysing recent data, we found a strong positive correlation between the entry efficiency of the Omicron variant and the relative usage of the host protease Cathepsin B/L by the original SARS-CoV-2 strain for cell entry. We developed a mathematical model to quantify entry efficiency in in vitro assays and found that the Omicron variant displayed >4-fold improved efficiency in using Cathepsin B/L for entry in 293T-ACE2 cells compared to the original strain. The preferential usage of Cathepsin B/L over TMPRSS2 for entry may explain the altered cell tropism of the Omicron variant and have implications for our understanding of its infectivity and transmissibility as well as for interventions.

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Section: Discussionmentioning

confidence: 99%

Modelling how the altered usage of cell entry pathways by the SARS-CoV-2 Omicron variant may affect the efficacy and synergy of TMPRSS2 and Cathepsin B/L inhibitors

Padmanabhan

Dixit

2022

Preprint

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“…Finally, fusion is the process by which a virus can merge directly with the cell membrane, thereby causing infection. Although this process occurs at a rate approximately one-tenth of the standard entry mechanism, it remains a crucial mechanism to target for inhibition (Amidei and Dobrovolny, 2022).…”

Section: Introductionmentioning

confidence: 99%

Identification of oral therapeutics using an AI platform against the virus responsible for COVID-19, SARS-CoV-2

Bess,

Berglind,

Mukhopadhyay

et al. 2023

Front. Pharmacol.

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Purpose: This study introduces a sophisticated computational pipeline, eVir, designed for the discovery of antiviral drugs based on their interactions within the human protein network. There is a pressing need for cost-effective therapeutics for infectious diseases (e.g., COVID-19), particularly in resource-limited countries. Therefore, our team devised an Artificial Intelligence (AI) system to explore repurposing opportunities for currently used oral therapies. The eVir system operates by identifying pharmaceutical compounds that mirror the effects of antiviral peptides (AVPs)—fragments of human proteins known to interfere with fundamental phases of the viral life cycle: entry, fusion, and replication. eVir extrapolates the probable antiviral efficacy of a given compound by analyzing its established and predicted impacts on the human protein-protein interaction network. This innovative approach provides a promising platform for drug repurposing against SARS-CoV-2 or any virus for which peptide data is available.Methods: The eVir AI software pipeline processes drug-protein and protein-protein interaction networks generated from open-source datasets. eVir uses Node2Vec, a graph embedding technique, to understand the nuanced connections among drugs and proteins. The embeddings are input a Siamese Network (SNet) and MLPs, each tailored for the specific mechanisms of entry, fusion, and replication, to evaluate the similarity between drugs and AVPs. Scores generated from the SNet and MLPs undergo a Platt probability calibration and are combined into a unified score that gauges the potential antiviral efficacy of a drug. This integrated approach seeks to boost drug identification confidence, offering a potential solution for detecting therapeutic candidates with pronounced antiviral potency. Once identified a number of compounds were tested for efficacy and toxicity in lung carcinoma cells (Calu-3) infected with SARS-CoV-2. A lead compound was further identified to determine its efficacy and toxicity in K18-hACE2 mice infected with SARS-CoV-2.Computational Predictions: The SNet confidently differentiated between similar and dissimilar drug pairs with an accuracy of 97.28% and AUC of 99.47%. Key compounds identified through these networks included Zinc, Mebendazole, Levomenol, Gefitinib, Niclosamide, and Imatinib. Notably, Mebendazole and Zinc showcased the highest similarity scores, while Imatinib, Levemenol, and Gefitinib also ranked within the top 20, suggesting their significant pharmacological potentials. Further examination of protein binding analysis using explainable AI focused on reverse engineering the causality of the networks. Protein interaction scores for Mebendazole and Imatinib revealed their effects on notable proteins such as CDPK1, VEGF2, ABL1, and several tyrosine protein kinases.Laboratory Studies: This study determined that Mebendazole, Gefitinib, Topotecan and to some extent Carfilzomib showed conventional drug-response curves, with IC50 values near or below that of Remdesivir with excellent confidence all above R2>0.91, and no cytotoxicity at the IC50 concentration in Calu-3 cells. Cyclosporine A showed antiviral activity, but also unconventional drug-response curves and low R2 which are explained by the non-dose dependent toxicity of the compound. Additionally, Niclosamide demonstrated a conventional drug-response curve with high confidence; however, its inherent cytotoxicity may be a confounding element that misrepresents true antiviral efficacy, by reflecting cellular damage rather than a genuine antiviral action. Remdesivir was used as a control compound and was evaluated in parallel with the submitted test article and had conventional drug-response curves validating the overall results of the assay. Mebendazole was identified from the cell studies to have efficacy at non-toxic concentrations and were further evaluated in mice infected with SARS-CoV-2. Mebendazole administered to K18-hACE2 mice infected with SARS-CoV-2, resulted in a 44.2% reduction in lung viral load compared to non-treated placebo control respectively. There were no significant differences in body weight and all clinical chemistry determinations evaluated (i.e., kidney and liver enzymes) between the different treatment groups.Conclusion: This research underscores the potential of repurposing existing compounds for treating COVID-19. Our preliminary findings underscore the therapeutic promise of several compounds, notably Mebendazole, in both in vitro and in vivo settings against SARS-CoV-2. Several of the drugs explored, especially Mebendazole, are off-label medication; their cost-effectiveness position them as economical therapies against SARS-CoV-2.

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Mathematical Modeling of Virus-Mediated Syncytia Formation: Past Successes and Future Directions

Dobrovolny

2023

Results and Problems in Cell Differentiation

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Estimation of virus-mediated cell fusion rate of SARS-CoV-2

Cited by 5 publications

References 69 publications

Modelling how the altered usage of cell entry pathways by the SARS-CoV-2 Omicron variant may affect the efficacy and synergy of TMPRSS2 and Cathepsin B/L inhibitors

Modelling how the altered usage of cell entry pathways by the SARS-CoV-2 Omicron variant may affect the efficacy and synergy of TMPRSS2 and Cathepsin B/L inhibitors

Identification of oral therapeutics using an AI platform against the virus responsible for COVID-19, SARS-CoV-2

Mathematical Modeling of Virus-Mediated Syncytia Formation: Past Successes and Future Directions

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