38 Potential COVID-19 Drugs Identified Using Novel Virtual Screening Strategy
A joint research team from KAIST and Institut Pasteur Korea has identified 38 potential repurposed drugs for COVID-19 treatment using a novel virtual screening strategy. This method, which employs pre- and post-docking filtering based on shape and interaction similarity, has shown promising results in reducing false positives and improving hit rates.
The research group began by screening 6,218 drugs, ultimately identifying 38 potential candidates for COVID-19 treatment. Their strategy involved a two-step filtering process: pre-docking filtering based on shape similarity to eliminate drugs unlikely to bind to the target, and post-docking filtering based on interaction similarity to focus on drugs with strong binding potential.
Seven of these compounds were found to inhibit SARS-CoV-2 replication in Vero cells, with three demonstrating anti-SARS-CoV-2 activity in human lung cells (Calu-3). This high hit rate of 18.4% underscores the effectiveness of the developed platform technology. The team's work not only aids in the rapid development of therapeutic medications for COVID-19 but also equips us to respond swiftly to new infectious diseases.
While further preclinical trials are planned to optimize drug concentrations and address toxicity issues, the identification of 38 potential repurposed drugs for COVID-19 treatment marks a significant milestone. This achievement highlights the practicality of drug repurposing, especially during global pandemics, and demonstrates the power of innovative virtual screening strategies in accelerating drug discovery.
