Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation
Abstract
1. Introduction
2. Result
2.1. Machine Learning Integration
2.2. The Inhibitory Effect of the Drug Candidate on the Virus In Vitro
2.3. Evaluation of Candidate Drugs on Mice Infected with H1N1 Lethal Virus
2.4. Protection of Glecaprevir and Everolimus at Different Concentrations in Mice Infected with H1N1 Lethal Virus
2.5. Molecular Mechanisms of Drug Candidates
2.6. Binding Mode of the Compounds with TRPV4 Receptor Protein
3. Discussion
4. Materials and Methods
4.1. Machine Learning Models
4.2. Molecular Docking for Compounds and Target
4.3. Cell Culture, Reagents, Virus
4.4. Cytotoxicity Test and In Vitro Antiviral Activity Determination
4.5. Immunofluorescence Staining (IF)
4.6. Infection in Mice and Determination of Lung Index
4.7. RNA Isolation and Quantitative RT-qPCR
4.8. EID50 Detection
4.9. Pathological Analysis
4.10. Western Blot (WB)
4.11. Statistical Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
293T | Human embryonic kidney 293T cells |
AUC | Area under the curve |
BA | Balanced accuracy |
BSA | Bovine serum albumin |
CADD | Computer-aided drug design |
CC50 | Maximum cytotoxic concentration |
CCK-8 | Cell counting kit-8 |
DPI | Days post-infection |
DMSO | Dimethyl sulfoxide |
DMEM | Dulbecco modified Eagle culture medium |
EID50 | 50% egg infectious dose |
FBS | Fetal bovine serum |
H&E | Hematoxylin and eosin |
HRP | Horseradish peroxidase |
HSV-2 | Herpes simplex virus type 2 |
IV | Influenza virus |
IAV | Influenza A virus |
IL-6 | Interleukin 6 |
IL-10 | Interleukin 10 |
IFN-β | Interferon β |
MDCK | Madin–Darby canine kidney |
M1 | Matrix protein 1 |
mTOR1 | Mammalian target of rapamycin complex 1 |
MLP | Multi-layer perceptron |
MCC | Matthews correlation coefficient |
MACCS | Molecular access system |
NP | Nucleoprotein |
PA | Polymerase acidic |
PDB | Protein data bank |
PFA | Paraformaldehyde |
RBC | Red blood cells |
RT-qPCR | Real-time quantitative fluorescent PCR |
RF | Random forest |
SPF-grade | Specific pathogen free-grade |
SMILES | Simplified molecular input line entry system |
SVM | Support vector machine |
TRPV4 | Transient receptor potential vanilloid 4 |
TNF-α | Tumor necrosis factor α |
TPSA | Topological polar surface areas |
WB | Western blot |
XGBoost | Extreme gradient boosting |
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Sun, Y.; Wu, J.; Shen, B.; Yang, H.; Cui, H.; Han, W.; Luo, R.; Zhang, S.; Li, H.; Qian, B.; et al. Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation. Int. J. Mol. Sci. 2025, 26, 1381. https://doi.org/10.3390/ijms26031381
Sun Y, Wu J, Shen B, Yang H, Cui H, Han W, Luo R, Zhang S, Li H, Qian B, et al. Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation. International Journal of Molecular Sciences. 2025; 26(3):1381. https://doi.org/10.3390/ijms26031381
Chicago/Turabian StyleSun, Yan, Jiajing Wu, Beilei Shen, Hengzheng Yang, Huizi Cui, Weiwei Han, Rongbo Luo, Shijun Zhang, He Li, Bingshuo Qian, and et al. 2025. "Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation" International Journal of Molecular Sciences 26, no. 3: 1381. https://doi.org/10.3390/ijms26031381
APA StyleSun, Y., Wu, J., Shen, B., Yang, H., Cui, H., Han, W., Luo, R., Zhang, S., Li, H., Qian, B., Fan, L., Zhang, J., Wang, T., Xia, X., Yan, F., & Gao, Y. (2025). Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation. International Journal of Molecular Sciences, 26(3), 1381. https://doi.org/10.3390/ijms26031381