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COVID-19

Researchers Develop New Approach to Identify Potential COVID-19 Treatments

Strategic Insights

— 1 min read

A team of researchers from the U.S. Food and Drug Administration has developed a new approach to identify potential treatments for COVID-19. The study, which was published in the journal Molecules, used a combination of machine learning, molecular dynamics, and molecular docking to identify potential inhibitors of the papain-like protease (PLpro) of SARS-CoV-2. The researchers identified five drugs as promising candidates for repurposing for COVID-19 treatment, and demonstrated the power of integrating computational modeling with machine learning to accelerate drug repurposing against emerging viral targets.

Key Takeaways:

  • The study used a combination of machine learning, molecular dynamics, and molecular docking to identify potential inhibitors of the papain-like protease (PLpro) of SARS-CoV-2.
  • The researchers identified five drugs as promising candidates for repurposing for COVID-19 treatment.
  • The approach demonstrated the power of integrating computational modeling with machine learning to accelerate drug repurposing against emerging viral targets.
  • The study was led by Ann Varghese, National Center for Toxicological Research, U.S. Food and Drug Administration (FDA), with additional authors Jie Liu, Tucker A. Patterson, Huixiao Hong.
  • The research was funded by the U.S. Food and Drug Administration (FDA).
  • The study used a training set of 127 compounds and a library of 1107 FDA-approved drugs.

Statistics:

  • 76.4% accuracy was achieved via leave-one-out cross-validation of the random forest model.
  • Five drugs were identified as promising candidates for repurposing for COVID-19 treatment.
  • 127 compounds were used in the training set.
  • 1107 FDA-approved drugs were used in the library.

Sources:

  • "Integrating Molecular Dynamics, Molecular Docking, and Machine Learning for Predicting SARS-CoV-2 Papain-like Protease Binders"

+ Molecules, 2025, 30(14):2985

+ doi: 10.3390/molecules30142985

+ https://www.mdpi.com/journal/molecules

  • NewsRx. "U.S. Food and Drug Administration (FDA) Researchers Add New Data to Research in COVID-19 (Integrating Molecular Dynamics, Molecular Docking, and Machine Learning for Predicting SARS-CoV-2 Papain-like Protease Binders)". Vaccine Weekly. August 13, 2025; p 496.

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