Two birds with one stone? Possible dual-targeting H1N1 inhibitors from traditional Chinese medicine

• Published in: PLoS computational biology Vol. 7; no. 12; p. e1002315
• Main Authors: Chang, Su-Sen, Huang, Hung-Jin, Chen, Calvin Yu-Chian
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.12.2011; Public Library of Science (PLoS)
• Subjects: Antiviral Agents - chemistry; Antiviral Agents - pharmacology; Aporphines - chemistry; Aporphines - pharmacology; Artificial Intelligence; Biology; Chinese medicine; Computer Science; Databases, Factual; Development and progression; Diterpenes - chemistry; Diterpenes - pharmacology; Drug resistance; Drug Resistance, Viral; Drugs, Chinese Herbal - chemistry; Drugs, Chinese Herbal - pharmacology; Epidemics; Health aspects; Humans; Influenza; Influenza A Virus, H1N1 Subtype - drug effects; Influenza A Virus, H1N1 Subtype - genetics; Influenza, Human - drug therapy; Influenza, Human - virology; Medical research; Medicine; Medicine, Chinese; Medicine, Chinese Traditional; Molecular Dynamics Simulation; Mutation; Physics; Proteins; Support Vector Machine; Taiwan; Taiwan; Drugs, Chinese Herbal; Medicine, Chinese Traditional; Artificial Intelligence; Humans; Drug Resistance, Viral; Antiviral Agents; Support Vector Machines; Molecular Dynamics Simulation; Aporphines; Influenza, Human; Diterpenes; Influenza A Virus, H1N1 Subtype; Mutation; Databases, Factual
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1002315

The H1N1 influenza pandemic of 2009 has claimed over 18,000 lives. During this pandemic, development of drug resistance further complicated efforts to control and treat the widespread illness. This research utilizes traditional Chinese medicine Database@Taiwan (TCM Database@Taiwan) to screen for compounds that simultaneously target H1 and N1 to overcome current difficulties with virus mutations. The top three candidates were de novo derivatives of xylopine and rosmaricine. Bioactivity of the de novo derivatives against N1 were validated by multiple machine learning prediction models. Ability of the de novo compounds to maintain CoMFA/CoMSIA contour and form key interactions implied bioactivity within H1 as well. Addition of a pyridinium fragment was critical to form stable interactions in H1 and N1 as supported by molecular dynamics (MD) simulation. Results from MD, hydrophobic interactions, and torsion angles are consistent and support the findings of docking. Multiple anchors and lack of binding to residues prone to mutation suggest that the TCM de novo derivatives may be resistant to drug resistance and are advantageous over conventional H1N1 treatments such as oseltamivir. These results suggest that the TCM de novo derivatives may be suitable candidates of dual-targeting drugs for influenza.