A computational-experimental strategy identifies K-7174 against African swine fever.
- 1State Key Laboratory for Animal Disease Control and Prevention, College of Veterinary Medicine, Lanzhou University, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou 730000, China.
- 2Gansu Province Research Center for Basic Disciplines of Pathogen Biology, Lanzhou 730046, China.
Abstract
African swine fever (ASF), caused by the African swine fever virus (ASFV), poses a catastrophic threat to global swine production due to the absence of effective vaccines or therapeutics. Targeting the virally encoded RNA polymerase (RNAP), which is essential for viral transcription, offers a promising antiviral strategy. Capitalizing on our previously resolved high-resolution structure of ASFV RNAP, we conducted a rigorous structure-based virtual screening of two compound libraries (T001 and LF1000) to identify selective inhibitors. From 100 candidates validated in vitro, nine compounds identified at the genome level by qPCR demonstrated >98% inhibition of ASFV replication in porcine alveolar macrophages (PAMs). The lead compound, K-7174 - a repurposed agent known to modulate proteasome and GATA activity - exhibited potent, dose-dependent antiviral efficacy (IC50 = 2.502 µmol/L), minimal cytotoxicity, and high binding affinity for ASFV RNAP. Molecular docking simulations indicated potential interactions with key catalytic residues, including Glu1051 and Ala456, proposing a mechanism that may involve active-site disruption. However, definitive confirmation of this binding pose requires further experimental validation through high-resolution structural methods such as cryo-EM. Our study not only nominates K-7174 as a promising anti-ASFV candidate but also establishes an integrated computational-experimental framework for accelerating the discovery of antiviral agents targeting viral polymerases.
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BibTeX
@article{sun2026computationalexperimental,
title = {{A computational-experimental strategy identifies K-7174 against African swine fever.}},
author = {Bozhang Sun and Fei Xi and Zhirui Liu and Huanan Liu and Haiyang Song and Yifei Zhao and Zixiang Zhu and Haixue Zheng and Guoliang Zhu},
journal = {Biophysics reports},
year = {2026},
month = oct,
doi = {10.52601/bpr.2025.250054},
url = {https://europepmc.org/article/MED/42997079},
note = {CC BY},
}
RIS
TY - JOUR
TI - A computational-experimental strategy identifies K-7174 against African swine fever.
AU - Bozhang Sun
AU - Fei Xi
AU - Zhirui Liu
AU - Huanan Liu
AU - Haiyang Song
AU - Yifei Zhao
AU - Zixiang Zhu
AU - Haixue Zheng
AU - Guoliang Zhu
PY - 2026
DA - 2026/10/31
JO - Biophysics reports
DO - 10.52601/bpr.2025.250054
UR - https://europepmc.org/article/MED/42997079
AB - African swine fever (ASF), caused by the African swine fever virus (ASFV), poses a catastrophic threat to global swine production due to the absence of effective vaccines or therapeutics. Targeting the virally encoded RNA polymerase (RNAP), which is essential for viral transcription, offers a promising antiviral strategy. Capitalizing on our previously resolved high-resolution structure of ASFV RNAP, we conducted a rigorous structure-based virtual screening of two compound libraries (T001 and LF1000) to identify selective inhibitors. From 100 candidates validated in vitro, nine compounds identified at the genome level by qPCR demonstrated >98% inhibition of ASFV replication in porcine alveolar macrophages (PAMs). The lead compound, K-7174 - a repurposed agent known to modulate proteasome and GATA activity - exhibited potent, dose-dependent antiviral efficacy (IC50 = 2.502 µmol/L), minimal cytotoxicity, and high binding affinity for ASFV RNAP. Molecular docking simulations indicated potential interactions with key catalytic residues, including Glu1051 and Ala456, proposing a mechanism that may involve active-site disruption. However, definitive confirmation of this binding pose requires further experimental validation through high-resolution structural methods such as cryo-EM. Our study not only nominates K-7174 as a promising anti-ASFV candidate but also establishes an integrated computational-experimental framework for accelerating the discovery of antiviral agents targeting viral polymerases.
SN - 2364-3439
SN - 2364-3420
ER -