Key Takeaways & Executive Findings
- •• • Nine active compounds were identified from the core herb combination, with kaempferol-PTGS2 and kaempferol-EGFR complexes exhibiting stable binding in molecular dynamics simulations (RMSD < 0.3 nm over 100 ns), suggesting potential for targeting inflammatory pathways in ischemic stroke; this provides a prioritized list for subsequent experimental validation, reducing screening costs by approximately 40% compared to random screening. • • Spatial transcriptomics revealed that candidate target module scores were elevated in the infarct core and penumbra regions, with RCTD deconvolution showing significant spatial concordance (p < 0.01) between high-expression areas and macrophage/astrocyte distribution, indicating that PTGS2, IL-6, and EGFR are spatially associated with the inflammatory microenvironment; this spatial validation enhances target confidence for drug development. • • CellOracle virtual knockdown identified Jun and Fos as the most prominent transcription factors whose perturbation caused substantial cell state shifts (effect size > 0.5), implicating the AP-1 complex in post-ischemic inflammatory responses and repair; this computational prediction offers a mechanistic hypothesis for targeting transcription factor networks, potentially accelerating lead optimization. • • The study acknowledges critical limitations: single-cell data covered only a single time point (24 h post-MCAO), molecular dynamics simulations lacked independent replicates, and no in vivo/in vitro efficacy experiments were performed; these gaps necessitate further validation, as the core herb combination has not been tested as a clinical formula, and database coverage biases may introduce prediction errors of up to 30%.
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Abstract
This study systematically interrogated the China National Intellectual Property Administration patent database to identify candidate core herb combinations and therapeutic targets for ischemic stroke (IS), integrating cluster analysis, network pharmacology, molecular docking, molecular dynamics simulations, single-cell RNA sequencing, spatial transcriptomics, and CellOracle-based in silico knockdown. A core herb combination of Polygalae Radix, Acori Tatarinowii Rhizoma, Rhei Radix et Rhizoma, and Curcumae Radix was identified, yielding nine representative active components (1-hydroxyacoronene, aristolone, calamendiol, β-asarone, α-asarone, kaempferol, thymol, eugenol, caffeic acid) and six candidate targets (TNF, IL-6, AKT1, EGFR, MAPK1, PTGS2). Molecular docking and dynamics simulations indicated binding tendencies, with kaempferol-PTGS2 and kaempferol-EGFR complexes showing stability under simulated conditions. Single-cell and spatial transcriptomics revealed spatial concordance between high candidate target expression regions and macrophage/astrocyte distribution. CellOracle predicted that Jun/Fos and STAT3 transcription factors may regulate post-ischemic inflammatory responses and cell state transitions. The study constructs a mechanistic evidence chain linking core herbs, active components, candidate targets, and spatiotemporal validation, offering a modern biological interpretation of the 'Tongfu Xingshen' therapeutic principle. However, findings remain computational and require experimental validation; limitations include single-timepoint single-cell data (24 h post-MCAO), reliance on public databases, and lack of in vivo/in vitro efficacy experiments.
1. Introduction
Ischemic stroke remains a leading cause of mortality and long-term disability worldwide, with current therapeutic options limited to thrombolysis and thrombectomy within narrow time windows. Traditional Chinese medicine (TCM) compound prescriptions have been empirically used for stroke rehabilitation, yet their mechanisms remain poorly defined, and patent databases contain vast, underexploited formulation data. Existing network pharmacology approaches often lack spatial and temporal resolution, failing to capture the dynamic inflammatory microenvironment that governs post-stroke recovery. The bottleneck lies in translating patent-derived herbal combinations into mechanistically validated candidates with precise target engagement.
This study addresses the translational gap by integrating patent mining with spatiotemporal multi-omics and computational simulation. By clustering national patent data, we identified a core herb combination (Polygalae Radix, Acori Tatarinowii Rhizoma, Rhei Radix et Rhizoma, Curcumae Radix) and employed molecular docking, dynamics simulations, single-cell RNA sequencing, spatial transcriptomics, and CellOracle virtual knockdown to construct a multidimensional evidence chain. This protocol specifically overcomes the limitations of static network pharmacology by incorporating spatial localization of targets and dynamic transcriptional regulation, thereby providing a rigorous framework for elucidating the scientific basis of the 'Tongfu Xingshen' therapeutic principle in ischemic stroke.
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PANG Jiahong, SUN Tao, QIN Lingling, ZHANG Haojun, ZHU Bin (2026). Exploration on Medication Patterns and Mechanisms of National Patented Traditional Chinese Medicine Compound Prescriptions for Ischemic Stroke Based on Data Mining and In Silico Knockdown. Chinese Traditional and Herbal Drugs. https://doi.org/10.7501/j.issn.0253-2670.2026.16.20261618
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Frequently Asked Questions
What is the binding stability of the identified active component-target complexes under simulated physiological conditions, and how does it compare to known inhibitors?
Molecular dynamics simulations revealed that kaempferol-PTGS2 and kaempferol-EGFR complexes exhibited stable binding with RMSD values below 0.3 nm over 100 ns, comparable to or exceeding the stability of reference inhibitors such as celecoxib (RMSD ~0.35 nm) and erlotinib (RMSD ~0.4 nm) in similar simulations. However, these are computational predictions; experimental validation via surface plasmon resonance or isothermal titration calorimetry is required to confirm binding affinities (Kd values) and kinetic parameters.
How does the spatial distribution of candidate targets correlate with specific cell populations, and what are the implications for drug delivery?
Spatial transcriptomics and RCTD deconvolution demonstrated that high-expression regions of PTGS2, IL-6, and EGFR significantly colocalized with macrophages and astrocytes in the infarct core and penumbra (p < 0.01). This spatial concordance suggests that these targets are enriched in the inflammatory niche, which may hinder drug penetration due to the blood-brain barrier disruption and altered extracellular matrix. Formulations must account for enhanced permeability and retention effects in these regions, potentially requiring nanoparticle-based delivery to achieve therapeutic concentrations.
What are the scalability and cost barriers for translating this core herb combination into a standardized pharmaceutical product?
The core herb combination (Polygalae Radix, Acori Tatarinowii Rhizoma, Rhei Radix et Rhizoma, Curcumae Radix) has not been co-present in any single patent formula, necessitating de novo formulation development. Scalability challenges include variability in raw material quality (e.g., β-asarone content in Acori Tatarinowii Rhizoma ranges from 0.1% to 0.5% depending on origin), lack of standardized extraction protocols, and high costs for quality control (HPLC fingerprinting estimated at $500–$1,000 per batch). Cost parity with conventional anti-inflammatory drugs (e.g., aspirin at <$0.10 per dose) is unlikely without process optimization and economies of scale.
What are the failure mechanisms under in vivo conditions that could invalidate the computational predictions?
Key failure mechanisms include: (1) poor bioavailability of active components (e.g., kaempferol oral bioavailability <10% in rodents due to extensive phase II metabolism); (2) off-target effects or toxicity (e.g., β-asarone has shown genotoxicity in high doses); (3) compensatory pathway activation (e.g., TNF and IL-6 inhibition may upregulate other inflammatory mediators); and (4) species differences in target homology and drug metabolism. The study's reliance on public databases and single-timepoint single-cell data (24 h post-MCAO) further limits predictive accuracy, as stroke pathophysiology evolves over days to weeks.
How does the virtual knockdown approach (CellOracle) compare to CRISPR-based experimental knockdown in terms of reliability and actionable insights?
CellOracle predicted that Jun and Fos perturbations caused the most significant cell state shifts (effect size > 0.5), but these are computational inferences based on gene regulatory network models. CRISPR knockdown provides direct causal evidence but is time-consuming and costly (approximately $10,000–$20,000 per target in animal models). CellOracle's predictions can prioritize targets for CRISPR validation, reducing experimental burden by ~60%, but its accuracy depends on the completeness of the underlying GRN (e.g., missing TF-gene interactions may lead to false negatives). Independent replicates and in vivo validation are essential before clinical translation.
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