Efficacy of the oral nucleoside prodrug GS-5245 (Obeldesivir) against SARS-CoV-2 and coronaviruses with pandemic potential
Preprint
Abstract
Despite the wide availability of several safe and effective vaccines that can prevent severe COVID-19 disease, the emergence of SARS-CoV-2 variants of concern (VOC) that can partially evade vaccine immunity remains a global health concern. In addition, the emergence of highly mutated and neutralization-resistant SARS-CoV-2 VOCs such as BA.1 and BA.5 that can partially or fully evade ( 1 ) many therapeutic monoclonal antibodies in clinical use underlines the need for additional effective treatment strategies. Here, we characterize the antiviral activity of GS-5245, Obeldesivir (ODV), an oral prodrug of the parent nucleoside GS-441524, which targets the highly conserved RNA-dependent viral RNA polymerase (RdRp). Importantly, we show that GS-5245 is broadly potent in vitro against alphacoronavirus HCoV-NL63, severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-related Bat-CoV RsSHC014, Middle East Respiratory Syndrome coronavirus (MERS-CoV), SARS-CoV-2 WA/1, and the highly transmissible SARS-CoV-2 BA.1 Omicron variant in vitro and highly effective as antiviral therapy in mouse models of SARS-CoV, SARS-CoV-2 (WA/1), MERS-CoV and Bat-CoV RsSHC014 pathogenesis. In all these models of divergent coronaviruses, we observed protection and/or significant reduction of disease metrics such as weight loss, lung viral replication, acute lung injury, and degradation in pulmonary function in GS-5245-treated mice compared to vehicle controls. Finally, we demonstrate that GS-5245 in combination with the main protease (M pro ) inhibitor nirmatrelvir had increased efficacy in vivo against SARS-CoV-2 compared to each single agent. Altogether, our data supports the continuing clinical evaluation of GS-5245 in humans infected with COVID-19, including as part of a combination antiviral therapy, especially in populations with the most urgent need for more efficacious and durable interventions.Keywords
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