A Systematic Host-Centric Approach to Identifying Repurposed Drugs for Viral Infections
<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d7181933e174">Today, most antiviral screening approaches evaluate the drug activity targeting virus proteins, while often overlooking the host proteins essential to virus replication. This virus-centric approach rapidly leads to therapy resistance due to mutation-prone viral genomes, underscoring the need of alternative antiviral strategies. Here, we explore host-targeting compounds, using SARS-CoV-2 as a model as an alternative approach. With systematic screening approaches, we have investigated the antiviral activity of 5275 compounds from the SPECS drug repurposing library. Our primary screening pipeline included: 1) host cell morphology changes by the phenomics assay Cell Painting (CP), 2) detecting SARS-CoV-2 infection rate by antibody-detection of, and 3) viability rescue, the gold standard for antiviral evaluation. We demonstrate how SARS-CoV-2 infection induced a specific phenotypic signature in Vero E6 and A549-ACE2 cells, which was reversed by antiviral controls such as remdesivir. Our unbiased host-focused approach identified 324 compounds with antiviral activity against SARS-CoV-2 (6% of SPECS library), including 150, 117, and 210 from respective screening assay. Compounds exhibiting antiviral activity were further validated in a dose-response manner by CP and counter screened using a live-cell assay assessing drug-induced phopholipidosis (DIPL). Validation screens identified 33 (0.6% of the SPECS library) compounds that restored host cell morphology without inducing DIPL, representing both new and previously investigated drug repurposing candidates against SARS-CoV-2 with activity to the host cell. This research establishes a systematic methodological approach to identify host-targeted antivirals, applicable to other emerging viruses in global need of antiviral drugs, while highlighting their potential to mitigate drug resistance.
Authors
- Flavio Ballante (ORCID: https://orcid.org/0000-0002-4831-3423)
- Hanna Axelsson (ORCID: https://orcid.org/0000-0003-2365-1749)
- Marianna Tampere (ORCID: https://orcid.org/0000-0001-5744-3206)
- Ola Spjuth (ORCID: https://orcid.org/0000-0002-8083-2864)
- Brinton A. Seashore-Ludlow (ORCID: https://orcid.org/0000-0001-8658-5967)
- Jonne Rietdijk (ORCID: https://orcid.org/0000-0003-3799-6684)
- Maris Lapins (ORCID: https://orcid.org/0000-0002-0122-6680)
- Duncan Njenda (ORCID: https://orcid.org/0000-0001-8276-9726)
- Jordi Carreras‐Puigvert (ORCID: https://orcid.org/0000-0002-7671-3707)
- Päivi Östling (ORCID: https://orcid.org/0000-0001-5501-466X)
- Adelinn Kalman (ORCID: https://orcid.org/0000-0002-1539-0633)
- Elin Asp
Institutions
- Uppsala University (SE)
- Science for Life Laboratory (SE)
- Karolinska Institutet (SE)
Publication Details
- Published
- 2025-04-12
- DOI
- https://doi.org/10.14293/idr.25.010ea
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00