Brilacidin, a COVID-19 Drug Candidate, Exhibits Potent In Vitro Antiviral Activity Against SARS-CoV-2
Allison Bakovic, Kenneth Risner, Nishank Bhalla, Farhang Alem, Theresa L. Chang, Warren Weston, Jane A. Harness, Aarthi Narayanan
Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the newly emergent causative agent of coronavirus disease-19 (COVID-19), has resulted in more than one million deaths worldwide since it was first detected in 2019. There is a critical global need for therapeutic intervention strategies that can be deployed to safely treat COVID-19 disease and reduce associated morbidity and mortality. Increasing evidence shows that both natural and synthetic antimicrobial peptides (AMPs), also referred to as Host Defense Proteins/Peptides (HDPs), can inhibit SARS-CoV-2, paving the way for the potential clinical use of these molecules as therapeutic options. In this manuscript, we describe the potent antiviral activity exerted by brilacidin—a de novo designed synthetic small molecule that captures the biological properties of HDPs—on SARS-CoV-2 in a human lung cell line (Calu-3) and a monkey cell line (Vero). These data suggest that SARS-CoV-2 inhibition in these cell culture models is primarily a result of the impact of brilacidin on viral entry and its disruption of viral integrity. Brilacidin has demonstrated synergistic antiviral activity when combined with remdesivir. Collectively, our data demonstrate that brilacidin exerts potent inhibition of SARS-CoV-2 and thus supports brilacidin as a promising COVID-19 drug candidate.
CORDITE (CORona Drug InTEractions database) collects and aggregates data from PubMed, MedRxiv, BioRxiv, ChemRxiv and PMC for SARS-CoV-2. Its main focus is set on drug interactions either addressing viral proteins or human proteins that could be used to treat COVID.
It collects and provides up-to-date information on computational predictions, in vitro, as well as in vivo study data.
The information provided is for research only and we cannot guarantee the correctness of the data.
