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NPJ Digit Med . Predictive modeling & mechanistic validation of synergistic pimodivir combinations for anti-influenza therapy via PB2cap affinity bo

tetano

Editor, Senior Moderator
NPJ Digit Med


. 2025 Nov 21;8(1):712.
doi: 10.1038/s41746-025-02083-2. Predictive modeling & mechanistic validation of synergistic pimodivir combinations for anti-influenza therapy via PB2cap affinity boost

Peng Luo[SUP] #[/SUP][SUP] 1 [/SUP], Kexin Li[SUP] #[/SUP][SUP] 1 [/SUP], Yubin Xie[SUP] #[/SUP][SUP] 1 [/SUP], Kun Huang[SUP] #[/SUP][SUP] 1 [/SUP], Zhenzhi Qin[SUP] 1 [/SUP], Jian-Piao Cai[SUP] 1 [/SUP], Yu Fu[SUP] 1 [/SUP], Jianli Cao[SUP] 1 [/SUP], Sihang Cao[SUP] 1 [/SUP], Ziyao Zhou[SUP] 2 [/SUP], Zi-Wei Ye[SUP] 3 [/SUP], Shuofeng Yuan[SUP] 4 5 6 7 [/SUP]



Affiliations
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.


 
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