Liuwei Kangguan Formula: Mechanism-driven and computation-assisted optimization from Xuanfei Baidu Formula for combating SARS-CoV-2 infection.
4 affiliations
- 1Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
- 2State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
- 3Hangzhou Institute for Food and Drug Control, Hangzhou 310022, China.
- 4Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100029, China.
Abstract
Objective
To advance mechanism-driven optimization of traditional Chinese medicine (TCM) formulas for modern drug development, a computation assisted strategy integrating multiple reporter assays with network topology analysis was proposed. The strategy was applied to simplify Xuanfei Baidu Formula (XFBD), a clinically approved anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), to generate the optimized Liuwei Kangguan Formula (LWKG).Methods
An integrated transcriptomic analysis of public corona virus disease 2019 (COVID-19) datasets was applied to identify core targets. Reporter models evaluating these targets were established and evaluated through time-sequential agonist exposure and chemical interferences. These models were then used to screen for active components in XFBD, based on which a formula-herb-compound tripartite network was constructed and analyzed with seven topological algorithms. The prioritized nodes guided the formulation of the optimized preparation, LWKG. LWKG was then evaluated through chemical profiling and pharmacological experiments.Results
Transcriptomic analysis identified nuclear factor-κB (NF-κB), activator protein-1 (AP-1), and interferon-stimulated response element (ISRE) as key transcriptional regulators mediating anti-SARS-CoV-2 immune responses. Triple reporter models were then constructed, which demonstrated temporal activation and crosstalk among the three pathways. Subsequently, 20 serum-available compounds and nine herbal extracts were identified as potential active substances from 77 tested substances of XFBD, and six core components were prioritized to prepare LWKG. LWKG retained 62.1% of phytochemical features in XFBD. Besides, it demonstrated pharmacological activities in modulating antiviral innate immunity, inhibiting replication of SARS-CoV-2 subtypes, and alleviating pneumonia in SARS-CoV-2 or human coronavirus OC43 (HCoV-OC43) infected mice.Conclusion
Through our strategy the composition of XFBD was simplified while maintaining immunomodulatory and antiviral efficacy. This study provided a feasible framework combining wet-lab and in silico experiments for optimizing TCM formulas.
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BibTeX
@article{yu2026liuwei,
title = {{Liuwei Kangguan Formula: Mechanism-driven and computation-assisted optimization from Xuanfei Baidu Formula for combating SARS-CoV-2 infection.}},
author = {Sijia Yu and Bin Liu and Xuanxuan Li and Guofang Shen and Ronghua Zhao and Qinhai Ma and Yi Wang},
journal = {Chinese herbal medicines},
year = {2026},
month = sep,
doi = {10.1016/j.chmed.2026.08.019},
url = {https://europepmc.org/article/MED/42948775},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Liuwei Kangguan Formula: Mechanism-driven and computation-assisted optimization from Xuanfei Baidu Formula for combating SARS-CoV-2 infection.
AU - Sijia Yu
AU - Bin Liu
AU - Xuanxuan Li
AU - Guofang Shen
AU - Ronghua Zhao
AU - Qinhai Ma
AU - Yi Wang
PY - 2026
DA - 2026/09/04
JO - Chinese herbal medicines
DO - 10.1016/j.chmed.2026.08.019
UR - https://europepmc.org/article/MED/42948775
AB - Objective To advance mechanism-driven optimization of traditional Chinese medicine (TCM) formulas for modern drug development, a computation assisted strategy integrating multiple reporter assays with network topology analysis was proposed. The strategy was applied to simplify Xuanfei Baidu Formula (XFBD), a clinically approved anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), to generate the optimized Liuwei Kangguan Formula (LWKG).Methods An integrated transcriptomic analysis of public corona virus disease 2019 (COVID-19) datasets was applied to identify core targets. Reporter models evaluating these targets were established and evaluated through time-sequential agonist exposure and chemical interferences. These models were then used to screen for active components in XFBD, based on which a formula-herb-compound tripartite network was constructed and analyzed with seven topological algorithms. The prioritized nodes guided the formulation of the optimized preparation, LWKG. LWKG was then evaluated through chemical profiling and pharmacological experiments.Results Transcriptomic analysis identified nuclear factor-κB (NF-κB), activator protein-1 (AP-1), and interferon-stimulated response element (ISRE) as key transcriptional regulators mediating anti-SARS-CoV-2 immune responses. Triple reporter models were then constructed, which demonstrated temporal activation and crosstalk among the three pathways. Subsequently, 20 serum-available compounds and nine herbal extracts were identified as potential active substances from 77 tested substances of XFBD, and six core components were prioritized to prepare LWKG. LWKG retained 62.1% of phytochemical features in XFBD. Besides, it demonstrated pharmacological activities in modulating antiviral innate immunity, inhibiting replication of SARS-CoV-2 subtypes, and alleviating pneumonia in SARS-CoV-2 or human coronavirus OC43 (HCoV-OC43) infected mice.Conclusion Through our strategy the composition of XFBD was simplified while maintaining immunomodulatory and antiviral efficacy. This study provided a feasible framework combining wet-lab and in silico experiments for optimizing TCM formulas.
SN - 1674-6384
SN - 2589-3610
ER -