Related Experiment Video
Updated: Jan 10, 2026

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit
Published on: June 28, 2013
Predictive modeling & mechanistic validation of synergistic pimodivir combinations for anti-influenza therapy via
Peng Luo1, Kexin Li1, Yubin Xie1
1Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
Abstract:
This study introduces a machine learning framework to predict effective antiviral combinations for influenza A. It identifies Pimodivir with Epinephrine or L-Adrenaline as synergistic agents, confirmed by experiments demonstrating increased binding affinity and viral suppression. Multiple synergy scoring methods validate these drug combinations' potential, offering a strategic pathway for designing rational combination therapies against influenza and other RNA viruses.
More Related Videos
09:07Using Zebrafish Models of Human Influenza A Virus Infections to Screen Antiviral Drugs and Characterize Host Immune Cell Responses
Published on: January 20, 2017
10:29Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025