MG-101, a cysteine protease inhibitor identified through high-throughput screening, exhibits in vivo efficacy and synergy with remdesivir against SARS-CoV-2

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has underscored the need for broad and potent antiviral agents. Although overall disease severity has diminished, the persistent risk of reinfection highlights the continued demand for novel therapeutic options. In this study, we performed an image-based high-throughput screening campaign of 11,030 small molecules-including nucleoside analogs, known antivirals, and diverse bioactives-to identify inhibitors of SARS-CoV-2 infection. Using an immunofluorescence assay that quantified viral proteins and assessed cell viability by Hoechst nuclear staining, we identified 97 primary hits in infected Vero cells. Dose-response evaluation confirmed 18 compounds active against both ancestral and Omicron variants, and subsequent validation in human lung cell lines (A549-hACE2-TMPRSS2 and Calu-3) highlighted multiple cysteine protease inhibitors as strong antiviral candidates. Among these, MG-101 emerged as a potent cysteine protease inhibitor with favorable pharmacokinetics, metabolic stability, and robust in vivo antiviral efficacy. Docking analysis and enzymatic assays demonstrated that MG-101 inhibits the SARS-CoV-2 3CL protease, and combination studies revealed in vitro synergistic antiviral activity with remdesivir. Together, these findings establish MG-101 as a potential therapeutic lead for COVID-19 and illustrate the value of image-based high-throughput screening for accelerating antiviral drug discovery.

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Publication Details

Journal
Biomedicine & Pharmacotherapy
Published
2026-02-02
DOI
https://doi.org/10.1016/j.biopha.2026.119076
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

MG-101, a cysteine protease inhibitor identified through high-throughput screening, exhibits in vivo efficacy and synergy with remdesivir against SARS-CoV-2

Sangeun Jeon, Seong Cheol Min, Ju Hwan Jeong, Young Mi Kim et al.
Biomedicine & Pharmacotherapy
Computational Drug Discovery Methods
article

MG-101, a cysteine protease inhibitor identified through high-throughput screening, exhibits in vivo efficacy and synergy with remdesivir against SARS-CoV-2

Sangeun Jeon, Seong Cheol Min, Ju Hwan Jeong, Young Mi Kim, Soonju Park, Jinyeong Heo, Honggun Lee, Jiho Kim, Dawoon Lee, David Shum, Inhee Choi, Seungtaek Kim, Yeonguk Jeon
article en

Abstract

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has underscored the need for broad and potent antiviral agents. Although overall disease severity has diminished, the persistent risk of reinfection highlights the continued demand for novel therapeutic options. In this study, we performed an image-based high-throughput screening campaign of 11,030 small molecules-including nucleoside analogs, known antivirals, and diverse bioactives-to identify inhibitors of SARS-CoV-2 infection. Using an immunofluorescence assay that quantified viral proteins and assessed cell viability by Hoechst nuclear staining, we identified 97 primary hits in infected Vero cells. Dose-response evaluation confirmed 18 compounds active against both ancestral and Omicron variants, and subsequent validation in human lung cell lines (A549-hACE2-TMPRSS2 and Calu-3) highlighted multiple cysteine protease inhibitors as strong antiviral candidates. Among these, MG-101 emerged as a potent cysteine protease inhibitor with favorable pharmacokinetics, metabolic stability, and robust in vivo antiviral efficacy. Docking analysis and enzymatic assays demonstrated that MG-101 inhibits the SARS-CoV-2 3CL protease, and combination studies revealed in vitro synergistic antiviral activity with remdesivir. Together, these findings establish MG-101 as a potential therapeutic lead for COVID-19 and illustrate the value of image-based high-throughput screening for accelerating antiviral drug discovery.

Biomedicine & PharmacotherapyVol. 196
Institut Pasteur Korea (KR), Chungbuk National University (KR), Korea Research Institute of Bioscience and Biotechnology (KR)
Good health and well-being
Openalex Percentile: Top 68%
Computational Drug Discovery Methods
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