Chinese herbal medicine treats COVID-19 by promoting self-healing power and balancing immune response: A functional classification analysis integrating molecular targets and pathways

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We hypothesized that Chinese herbal medicine (CHM) treats COVID-19 predominantly through host-directed mechanisms—promoting self-healing (PSH) and balancing immune response (BIR)—rather than directly inhibiting virus (IV). Six CHM formulas officially recommended for COVID-19 in China (46 unique herbs) were analyzed. The herb-associated molecular targets were collected from CHMSP, HERB, and TTD, cross-referenced with 118 curated COVID-19 therapeutic targets, and functionally classified into PSH, BIR, or IV using standardized pathway annotations (KEGG, Reactome) and network analysis. Thirty-six herbs (78.3%) shared targets with COVID-19. Across all formulas, PSH and BIR mechanisms were consistently predominant, whereas putative antiviral targets (e.g., IMPDH2, VCP) were rare and showed limited network connectivity. Major network hubs included TNF, IL6, IL10, and CXCL8, highlighting convergent regulation of inflammation and tissue repair. Although the highest compositional overlap among the formulas is no more than 40%, their functional output was highly conserved, with a consistent PSH/BIR ratio (mean 0.90 ± 0.13). Pharmacokinetic and mechanistic reassessment of the commonly labeled “antiviral” herbs suggested that reported benefits are more plausibly mediated through host-dependent PSH and/or BIR actions than direct viral inhibition at physiological concentrations. These findings support a holistic, host-centered mechanism for CHM in control of COVID-19 and provide a quantitative framework for evaluating host-directed therapeutics in infectious diseases. Chinese herbal medicine Self-healing power Immunomodulation Antiviral activity COVID-19 Host-directed therapy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Homeostasis is fundamental for maintaining optimal physiological function and survival (Cannon, 1929 ). Organisms have evolved diverse mechanisms to preserve internal stability in the face of external and internal perturbations. When these mechanisms are disrupted, disease arises (Kotas & Medzhitov, 2015 ; Medzhitov et al., 2012 ; Scully, 2004 ). Infectious diseases represent a typical breakdown of homeostasis and remain a global priority for disease control (Holmes et al., 2017 ) : pathogen invasion causes tissue damage through toxin production, metabolic competition, and other virulence factors, while the host immune response—although essential for pathogen clearance—can itself inflict collateral damage through excessive or dysregulated inflammation. Thus, the pathology of infectious diseases reflects the combined injurious effects of pathogen virulence and host immune responses (Fig. 1 ). Correspondingly, three strategic approaches exist for treating infectious diseases: inhibiting the pathogen, regulating the immune response, and promoting the host’s intrinsic capacity to repair damage, herein referred to as “self-healing power” (Sun, 2022 , 2023 ) . For decades, antimicrobial drugs—including antibiotics, antivirals, and antiparasitic agents—have formed the backbone of infectious disease treatment. However, this pathogen-directed therapy now faces serious challenges. Virtually all major pathogens have developed resistance to available antimicrobial agents, while the development of new drugs is slow, costly, and increasingly unable to keep pace with emerging resistance(Reardon, 2014 ). In parallel, immunosuppressive or anti-inflammatory agents used to control hyperinflammation—such as glucocorticoids or cytokine inhibitors—also have significant limitations. Inflammatory pathology caused by dysregulated immune responses, including cytokine storm in COVID-19, lipopolysaccharide (LPS)–induced septic shock, and granuloma-associated tissue damage in tuberculosis, is now recognized as a major determinant of disease severity (Wright, 2021 ; Evans et al., 2021 ; Dorhoi et al., 2011 ). Although anti-inflammatory interventions can improve outcomes in selected settings, excessive immunosuppression compromises pathogen clearance and carries substantial systemic side effects (Patel et al., 2022 ; Russell et al., 2020 ). Collectively, these challenges underscore the urgent need for new therapeutic paradigms that move beyond a purely pathogen-centered approach. Furthermore, the increasing prevalence of post-acute sequelae (Long COVID) highlights the critical need for therapies that support long-term tissue repair and functional recovery (Fleischer et al., 2025 ; Izquierdo-Condoy et al., 2024 ). Chinese herbal medicine (CHM) has long been regarded as a holistic medical system that restores health by maintaining or re-establishing homeostasis (Jin et al., 2021 ). Developed in ancient times without knowledge of microbial pathogens, CHM formulas were not designed to target pathogens directly. Based on CHM theories, instead, they were constructed to correct imbalances within the host. Nevertheless, substantial evidence indicates that CHM can effectively treat infectious diseases (Y. Ma et al., 2019 ; F. Qi & Tang, 2021 ). Recent bibliometric analyses have further confirmed the growing focus on CHM’s capacity for immune system modulation (Lei & Chen, 2025 ). During the COVID-19 pandemic, CHM was widely implemented in China and showed notable clinical benefits (Lyu et al., 2021 ; You et al., 2023 ). Multiple formulas were developed and applied at different disease stages, and systematic reviews and clinical studies have attributed their therapeutic effects to several host-centered actions, including protection and repair of tissues and organs, modulation of inflammation, regulation of immune responses, and antiviral activity (Gu et al., 2025 ). To elucidate the mechanisms underlying the efficacy of CHM in infectious diseases, we recently proposed that CHM functions as a host-based medicine. In this model, CHM exerts its therapeutic effects primarily by promoting self-healing power and balancing immune responses, rather than directly inhibiting pathogens (Sun, 2022 , 2023 ). This concept was formalized mathematically into a host–pathogen interaction (HPI) equation H = S/(I + P/I) , where \(\:\text{H}\) denotes host health status, \(\:\text{S}\) represents the level of self-healing power, \(\:\text{I}\) reflects the degree of immune response, and \(\:\text{P}\) represents pathogen load. This framework highlights a central principle: robust self-healing power enables the host to repair damage caused by both pathogen and immune response, thereby raising the threshold at which immune activation remains safe and effective. Conversely, immune responses must be tightly balanced—strong enough to eliminate pathogens but not so excessive that they overwhelm the host’s repair capacity. This model aligns closely with core principles of CHM, encapsulated in the classical tenet “fu zheng qu xie, yin yang ping heng”(“扶正祛邪, 阴阳平衡”), meaning “promote the Righteous Qi, dispel the Evil Qi, and maintain Yin–Yang balance.” In CHM theory, Righteous Qi represents the body’s intrinsic capacity to repair damage and restore health, corresponding to self-healing power. Promoting Righteous Qi is a foundational therapeutic principle: when it is deficient, it should be strengthened; when it is constrained by pathological factors (Evil Qi), these factors should be removed to restore function. Evil Qi does not simply correspond to microbial pathogens, but more broadly to pathological processes—such as blood and qi stagnation, phlegm accumulation, and fluid retention—that impair self-healing. Similarly, Yin–Yang balance reflects both the balance within immune responses and the broader balance between immune activity and self-healing capacity. To further evaluate this host-centered model, we analyzed six CHM formulas that were officially recommended for COVID-19 treatment in China (Fig. 2 ). Together, these formulas comprise 46 herbs. Using an herb–target database and 118 COVID-19 therapeutic targets from the Therapeutic Target Database (TTD), we classified each herb into three functional categories: promoting self-healing power (PSH), balancing immune response (BIR), and inhibiting virus (IV). Across all six formulas, PSH and BIR emerged as the predominant functional modes of action, whereas IV functions were rare. Although some herbs have been reported to show antiviral effects in vitro, few have demonstrated definitive clinical efficacy in directly inhibiting viral entry or replication. Notably, despite sharing less than 40% overlap in herbal composition, the six formulas exhibited strikingly consistent PSH/BIR ratios. These findings suggest that enhancing self-healing power and balancing immune responses constitute the core mechanisms by which CHM treats infectious diseases, and that herbs with similar PSH/BIR profiles may be functionally interchangeable across formulas. Materials and Methods Definition of therapeutic functional categories To classify the therapeutic roles of herbs in treating infectious diseases, three functional categories were predefined based on the host–pathogen interaction framework (Sun, 2022 , 2023 ): promoting self-healing power (PSH), balancing immune response (BIR), and inhibiting virus (IV) (Table 1 ). PSH refers to biological processes that restore structural and functional integrity by promoting inflammation resolution, tissue repair and regeneration, cytoprotection, and organ protection. BIR denotes mechanisms that modulate the magnitude and timing of innate and adaptive immune responses to achieve effective pathogen control while minimizing host injury. IV includes two mechanistic types: (i) indirect inhibition via regulation of host-dependent factors required for viral entry, replication, or assembly, and (ii) direct inhibition via interference with viral proteins or enzymes at exposure levels plausible in vivo. These operational definitions informed all subsequent labeling of molecular targets. Table 1 Definitions of the three therapeutic strategies used for classifying herbal functions. Definitions and concise descriptions of the three therapeutic strategies used to classify herbal actions: PSH, BIR, and IV. Both indirect-IV and direct-IV are defined to guide downstream functional annotation. Therapeutic strategies Definition (concise) PSH Restores structural and functional integrity by resolving inflammation and activating programs of tissue repair, regeneration, and cytoprotection or organ protection. BIR Regulates the intensity and timing of innate and adaptive inflammatory responses to achieve effective pathogen clearance while minimizing host tissue injury. IV Indirect: Restricts viral binding, entry, replication, or assembly by modulating host-dependent factors (e.g., receptors, cofactors, cellular processes). Direct: Impairs viral binding, entry, or replication through direct action on viral proteins, viral enzymes, or virus–receptor interactions at clinically plausible exposure levels. The workflow for data acquisition, filtering, and herb–target convergence is shown in Fig. 2 . Selection of CHM formulas and constituent herbs Six CHM formulas officially recommended by the National Health Commission of China for the treatment of COVID-19 were selected: Lianhua Qingwen (LHQW), Qingfei Paidu Decoction (QFPD), Jinhua Qinggan (JHQG), Shufeng Jiedu (SFJD), Xuanfei Baidu (XFBD), and Huashi Baidu (HSBD) (Lyu et al., 2021 ; You et al., 2023 ; T. Zhang et al., 2024 ). Across these formulas, a total of 46 unique constituent herbs were identified. Herb names were standardized according to official pharmacognostic nomenclature (Chinese Pharmacopoeia Commission, 2020 ). These herbs formed the basis for downstream analyses of functional classification and herb–target–pathway mapping. Collection of herb-derived molecular targets The molecular targets associated with each herb were collected from three curated databases: the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (CHMSP) (Ru et al., 2014 ), the High-throughput Experiment- and Reference-guided database (HERB) (Fang et al., 2021 ), and the Therapeutic Target Database (TTD) (Chen et al., 2002 ). Only targets with experimental evidence or high-confidence computational predictions were retained. All herb-derived targets were then aggregated and prepared for overlap screening with COVID-19 therapeutic targets. COVID-19 therapeutic target dataset A curated list of therapeutic targets relevant to COVID-19 was retrieved from the TTD. A total of 118 targets were included, representing host or pathogen-associated factors implicated in viral entry, replication, immune dysregulation, inflammation, or organ injury. These targets were selected based on experimental evidence or expert curation reported in TTD and served as the reference set for identifying herb–COVID-19 target overlap. All targets were standardized by gene/protein symbols prior to matching. Target matching and functional labeling Herb-derived molecular targets were cross-validated against the 118 COVID-19 therapeutic targets to identify overlapping targets. Herbs that shared at least one target with the COVID-19 reference set were designated as “overlap-positive” and included in functional analyses. Each overlapping target was labeled with one or more therapeutic categories (PSH, BIR, IV) according to the operational definitions described above (Table 2 ). Multi-label assignment was permitted when targets were mechanistically relevant to multiple functions (e.g., IL10 contributing to both inflammation resolution and immune regulation). Herb-level functional labels were then determined by aggregating the labels of their overlapping targets. This procedure yielded a standardized classification scheme for all 36 overlap-positive herbs. Table 2 Operational rules for assigning molecular targets and pathways to the three therapeutic strategies. Decision keywords, pathway exemplars, and representative molecular targets used to assign biological roles into PSH, BIR, and IV categories. Multi-label assignment is permitted when mechanistic functions overlap. Standardization is based on KEGG, Reactome, and UniProt annotations. Therapeutic strategies Decision keywords Example pathways Example targets/factors PSH resolution; pro-resolving; repair; regeneration; cytoprotection; organ-protection; antioxidant; Nrf2; autophagy; ER stress; ECM remodeling; angiogenesis IL10 signaling; Nrf2-mediated oxidative stress response; mTOR; VEGF–VEGFR2; ECM–receptor interaction; ER stress/ERAD; autophagy IL10; NFE2L2 (Nrf2); MTOR; VEGFA/KDR; MMPs/TIMPs; HSPs; SIRT1 BIR pro-inflammatory; cytokine; innate; adaptive; NF- \(\:\kappa\) B; JAK/STAT; MAPK; TLR; complement; chemokine; inflammasome; “balance immune response’’ TNF signaling; IL6 signaling; TLR4 cascade; JAK–STAT; NF- \(\:\kappa\) B pathway; NLRP3 inflammasome; Complement TNF; IL6; IL1B; IFNG; TLR4; JAK2/STAT3; NFKB1/RELA; CXCL8 IV Indirect : viral entry; replication; assembly; host factor; receptor; cofactor; ACE2; BSG(CD147); TMPRSS2; IMPDH2; VCP; ERAD Receptor-mediated viral entry; Endocytosis; ERAD–virus interface; Purine metabolism/IMPDH2-related ACE2; BSG(CD147); TMPRSS2; FURIN; IMPDH2; VCP; HSP90; PIKfyve Direct : viral protease; polymerase; RdRp; 3CL pro /M pro ; PL pro ; spike; neuraminidase; capsid Viral RNA replication; Proteolytic processing of viral polyprotein; Viral fusion/entry SARS-CoV-2 RdRp (NSP12); 3CL pro /M pro (NSP5); PL pro ; Spike–ACE2 interface; Influenza NA; HIV RT/PR Pathway annotation and enrichment analysis To contextualize biological functions, all overlapping targets were annotated for signaling pathways using three authoritative databases: the Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa & Goto, 2000 ), the Reactome pathway database (Gillespie et al., 2022 ), and UniProtUniProt (The UniProt Consortium, 2023 ). Pathways associated with each target were retrieved and harmonized across databases to ensure standardized terminology. Enriched pathways related to inflammation regulation, immune activation, tissue repair, oxidative stress, viral entry, viral replication, or host-dependent viral processes were identified. These annotations were subsequently used to interpret therapeutic functions, support PSH/BIR/IV classification, and construct the integrated herb–target–pathway network. Network construction and visualization An integrated herb–target–pathway–function network was constructed to visualize relationships among formulas, constituent herbs, their overlapping molecular targets, associated signaling pathways, and functional labels (PSH, BIR, IV). Herbs were connected to their corresponding targets, and each target was linked to annotated pathways. Targets were further mapped to therapeutic categories based on functional labels. Node types were represented by distinct colors (formulas, herbs, targets, pathways, functions), and edges denoted curated or database-supported interactions. Network construction and visualization were performed to identify hub-like targets, functional clusters, and cross-formula similarities that contribute to PSH/BIR-dominant therapeutic patterns. Evidence curation and antiviral adjudication Because several herbs have reportedly been attributed “antiviral” properties (L.-C. Li et al., 2020 ; S. Lin, Wang, Tang, & others, 2022; Xu et al., 2021a ), a structured evidence curation and adjudication process was applied to evaluate whether such claims met criteria for direct or indirect viral inhibition (Table 3 ). Eligible evidence included: (i) biochemical assays measuring viral enzyme inhibition (e.g., 3CL pro , PL pro , RdRp), (ii) cell-based infection assays assessing viral entry or replication, (iii) in vivo infection models with virological endpoints, and (iv) clinical studies reporting viral load reduction. In silico studies (Kadioglu et al., 2021 ; Ren et al., 2020 ) and supra-physiological in vitro assays were included only as contextual information and were not considered sufficient evidence for IV labeling. Table 3 Adjudication checklist for inhibiting virus (IV) labels. Minimum evidence thresholds required to classify antiviral effects into IV-direct or IV-indirect. Criteria incorporate exposure plausibility (free C max vs. EC 50 /IC 50 ), mechanism specificity (viral-protein vs. host-factor dependence), and wet-lab evidence hierarchy. Docking-only findings fail to qualify. Dimension Minimum to qualify IV-direct Viral-protein mechanism (3CLpro, PLpro, RdRp, or spike–ACE2 interference) and plausible human exposure (free C max \(\:\text{≳}\) EC 50 /IC 50 ). Docking-only studies or supra-physiological in vitro concentrations do not qualify. IV-indirect Host-dependent restriction mechanisms (e.g., ACE2, TMPRSS2, BSG, ERAD/chaperone systems, nucleotide synthesis) not fully explainable by immune-regulation or tissue-repair processes. Immune-only or repair-only readouts are excluded. Notes : Minimum inclusion thresholds are applied after an exposure-plausibility check (free C max versus EC 50 /IC 50 ). Non-IV mechanisms are adjudicated under PSH/BIR as appropriate. Abbreviations: C max , maximum plasma concentration; EC 50 /IC 50 , half-maximal effective/inhibitory concentration. Exposure plausibility was assessed by comparing reported EC 50 /IC 50 values with achievable free C max under clinically relevant dosing (Y. Li et al., 2015 ; S.-P. Lin et al., 2012 ; Srinivas, 2010 ). IV-direct designation required inhibition of viral proteins or virus–receptor interactions at physiologically plausible exposure levels. IV-indirect designation required effects on host factors essential for viral life cycles (e.g., ACE2, TMPRSS2, IMPDH2, ER-associated degradation factors) that could not be explained by immune or repair mechanisms. Claims not meeting these criteria were adjudicated as PSH- and/or BIR-mediated rather than IV-mediated. This process ensured that antiviral labels were assigned according to rigorous, mechanism-based rules and evidence grading (Table 4 ). Table 4 Grading scale for evaluating antiviral evidence of selected herbs. Four-tier evidence grading system (A–D) used to evaluate the strength and clinical relevance of reported antiviral findings. The scale prioritizes human clinical evidence (Grade A) and in vivo infection models (Grade B), while in vitro or biochemical assays conducted at plausible exposure levels are graded as C. Docking-only studies, surrogate-virus models, and in vitro effects observed at supraphysiological concentrations are assigned Grade D. Grade Definition A Human clinical data with virological endpoints. B In vivo animal infection models demonstrating reductions in viral load or pathological improvement. C In vitro cell-based or biochemical antiviral assays conducted at clinically plausible exposure levels (EC 50 /IC 50 consistent with free C max ). D In silico analyses only, or in vitro antiviral effects observed at supra-physiological concentrations; includes results based on surrogate viruses without translational support. Software and reproducibility All data processing, target matching, pathway annotation, and graphical outputs were generated using Python 3.12.0 with standard scientific libraries (NumPy, pandas (McKinney, 2010 ), matplotlib, seaborn, and networkx (Hagberg et al., 2008 )). Analyses were performed in a reproducible workflow, and all scripts used for data integration and network construction are available upon request. Results Overview of herb–COVID-19 target overlap Among the 46 herbs included in the six nationally recommended COVID-19 formulas, 36 shared at least one molecular target with the 118 curated COVID-19 therapeutic targets from TTD. These 36 herbs constituted the analysis cohort for functional classification and for construction of the herb–target–pathway network. A complete list of overlap-positive herbs is provided in Table 5 . Table 5 Functional classification of 36 CHM herbs and their corresponding molecular targets. List of the 36 herbs identified across six representative CHM formulas, together with their target genes/proteins, associated signaling pathways, and their assigned functional categories (PSH, BIR, IV or combinations). Functional labels were adjudicated based on pathway-level and mechanistic evidence. The pharmacological activities and functional assignments of key herbs were supported by species-specific reviews and mechanistic studies (Adesso et al., 2018a ; C. Lin et al., 2015a ; C. Ma et al., 2015 ; J. Qi, Dong, Wang, & others, 2022; Ríos, 2011 ; Shen et al., 2019a ; C. Zhang et al., 2019 ). No. Herb LHQW QFPD JHQG SFJD XFBD HSBD Targets Molecular pathways Class. 1 Pogostemonis Herba √ √ √ C5AR1; CXCL8; IFNG; IL1B; TNF Complement C5a receptor signaling / GPCR signaling; Chemokine signaling pathway; Interferon gamma signaling; Interleukin 1 family signaling; TNF signaling pathway BIR 2 Rhei Radix et Rhizoma √ √ ACE; IL1B Renin–angiotensin system; Interleukin 1 family signaling PSH + IV + BIR 3 Cinnamomi Ramulus √ CCR5; CXCL8; IL10; MAP2K2 CC chemokine receptor signaling (chemokine–GPCR pathway); Chemokine signaling pathway; Interleukin 10 signaling; MAPK/ERK (Ras–Raf–MEK–ERK) cascade PSH + BIR 4 Poria √ √ CXCL8; IL6; TNF Chemokine signaling pathway; IL6 family signaling (JAK/STAT, MAPK); TNF signaling pathway BIR 5 Pinelliae Rhizoma √ √ BCHE; IL10; TNF Cholinesterase activity / Drug metabolism; Interleukin 10 signaling; TNF signaling pathway PSH + BIR 6 Zingiberis Rhizoma Recens √ ATP1A1; IL6; TNF Ion transport by P-type ATPases; IL6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 7 Dioscoreae Rhizoma √ BCHE Cholinesterase activity / Drug metabolism PSH + BIR 8 Citri Reticulatae Pericarpium √ TNF TNF signaling pathway BIR 9 Verbenae Herba √ √ DPP4; IFNG; IL10; IL6; TNF GLP 1/GIP degradation pathway; Interferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 10 Phragmitis Rhizoma √ CCR5; CXCL8; DPP4; IL10; IL6; TNF CC chemokine receptor signaling (chemokine–GPCR pathway); Chemokine signaling pathway; GLP 1/GIP degradation pathway; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 11 Atractylodis Rhizoma √ √ IL10; IL6; TNF Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 12 Citri Grandis Exocarpium √ TNF TNF signaling pathway BIR 13 Pinelliae Praeparatum Rhizoma √ VCP Protein quality control: ER associated degradation (ERAD) / Ubiquitin–proteasome system IV 14 Tsaoko Fructus √ IL6 IL 6 family signaling (JAK/STAT, MAPK) BIR 15 Bupleuri Radix √ √ ANGPT2; CXCL8; IL10; IL6; TNF Tie 2 Signaling / Hemostasis; Chemokine signaling pathway; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR+IV 16 Asteris Radix et Rhizoma √ IFNG; IL10; IL1B; TNF Interferon gamma signaling; Interleukin 10 signaling; Interleukin 1 family signaling; TNF signaling pathway PSH + BIR 17 Farfarae Flos √ BCHE; IL10; TNF Cholinesterase activity / Drug metabolism; Interleukin 10 signaling; TNF signaling pathway PSH + BIR 18 Fritillariae Thunbergii Bulbus √ DPP4; IL10 GLP 1/GIP degradation pathway; Interleukin 10 signaling PSH + BIR 19 Arctii Fructus √ BCHE; IL10; TNF Cholinesterase activity / Drug metabolism; Interleukin 10 signaling; TNF signaling pathway PSH + BIR 20 Menthae Haplocalycis Herba √ BCHE; IL1B; IL6; TNF Cholinesterase activity / Drug metabolism; Interleukin 1 family signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 21 Descurainiae Semen √ √ CRP; IL10; TNF Acute phase response / Complement activation pathway; Interleukin 10 signaling; TNF signaling pathway PSH + BIR 22 Atractylodis Macrocephalae Rhizoma √ BCHE Cholinesterase activity / Drug metabolism PSH + BIR 23 Anemarrhenae Rhizoma √ PDE5A; TNF cGMP–PKG signaling pathway / Nitric oxide–cGMP pathway; TNF signaling pathway PSH + BIR 24 All - grass of Dahurian Patrinia √ IFNG; IL10; IL1B; IL6; TNF Interferon gamma signaling; Interleukin 10 signaling; Interleukin 1 family signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 25 Astragali Radix √ ACE; BCHE; C5AR1; CXCL8; IFNG; IL10; IL6; TNF Renin–angiotensin system; Cholinesterase activity / Drug metabolism; Complement C5a receptor signaling / GPCR signaling; Chemokine signaling pathway; Interferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + IV+BIR 26 Ephedrae Herba √ √ √ √ BCHE; CXCL8; IFNG; IL10; IL1B; IL6; TNF Cholinesterase activity / Drug metabolism; Chemokine signaling pathway; Interferon gamma signaling; Interleukin 10 signaling; Interleukin 1 family signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 27 Isatidis Radix √ √ BTK; IFNG; IL10; IL6; TNF B cell receptor (BCR) signaling via BTK / G \(\:\text{βγ}\) BTK activation pathway; Interferon gamma signaling; Interleukin 10 signaling; IL6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 28 Houttuyniae Herba √ IFNG; IL6; TNF Interferon gamma signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway BIR 29 Forsythiae Fructus √ √ √ CXCL8; IL10; IL1B; IL6; TNF Chemokine signaling pathway; Interleukin 10 signaling; Interleukin 1 family signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 30 Lonicerae Japonicae Flos √ √ IFNG; IL10; IL6; TNF Interferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 31 Armeniacae Semen Amarum √ √ √ √ √ IFNG; IL10; IL6; JAK2; TNF Interferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); JAK–STAT signaling pathway; TNF signaling pathway BIR + PSH 32 Belamcandae Rhizoma √ TNF TNF signaling pathway BIR 33 Sweet Wormwood Herb √ IFNG; IL10; IL6; TNF Interferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway PSH + BIR 34 Glycyrrhizae Radix et Rhizoma √ √ √ √ √ √ BCHE; TNF Cholinesterase activity / Drug metabolism; TNF signaling pathway PSH + BIR 35 Polygoni Cuspidati Rhizoma et Radix √ √ ACE; BCHE; BSG; C5AR1; CCR5; CRP; CXCL8; IFNG; IL10; IL1B; IL6; IMPDH2; MARK2; MTOR; PDE5A; PPIF; TNF Renin–angiotensin system; Cholinesterase activity / Drug metabolism; Basigin interactions (Cell surface interactions at the vascular wall); Complement C5a receptor signaling / GPCR signaling; CC chemokine receptor signaling (chemokine–GPCR pathway); Acute phase response / Complement activation pathway; Chemokine signaling pathway; Interferon gamma signaling; Interleukin 10 signaling; Interleukin 1 family signaling; IL6 family signaling (JAK/STAT, MAPK); De novo guanine nucleotide synthesis / Purine metabolism; Cell polarity / microtubule regulation & mTOR HIF-1 \(\:\text{α}\) signaling; mTOR signaling pathway; cGMP–PKG signaling pathway / Nitric oxide–cGMP pathway; Mitochondrial permeability transition pore (MPTP) & apoptosis signaling; TNF signaling pathway PSH + IV + BIR 36 Paeoniae Radix Rubra √ IL10; TNF Interleukin 10 signaling; TNF signaling pathway PSH + BIR Functional classification of herbs Functional classification of the 36 herbs revealed a consistent distribution across all six formulas (Fig. 3 ; Supplementary Fig. 1). Herbs labeled with overlapping PSH and BIR functions were the most abundant, followed by herbs exclusively classified as PSH or exclusively as BIR. Herbs assigned to the IV category, as well as those spanning all three categories (PSH–BIR–IV), were few. This pattern was observed both within individual formulas and across the combined dataset, indicating that therapeutic contributions arise predominantly from host-directed mechanisms (PSH and BIR) rather than pathogen-directed antiviral activity. Functional distribution of overlapping molecular targets A similar trend was observed at the target level (Fig. 4 ; Supplementary Fig. 2). The majority of overlapping targets fell within the PSH–BIR overlap. High-frequency targets included TNF, IL10, IL6, CXCL8, and IFNG, all of which are key regulators of inflammation, immune activation, and tissue repair. In contrast, antiviral-specific targets such as IMPDH2 and VCP were fewer and primarily associated with viral replication or virus-related protein processing. All pathway annotations for overlapping targets are provided in Table 6 . Table 6 Major signaling pathways targeted by CHM herbs. Pathway-level summary of the molecular targets regulated by CHM herbs. Each entry includes pathway name, biological function, and its relevance to host response during SARS-CoV-2 infection. Pathway nomenclature is standardized using KEGG, Reactome, and UniProt. No. Target Pathway Pathway functions Class. 1 ACE2 Renin–angiotensin system ACE2 converts angiotensin I to II, regulates blood pressure, vascular tone and sodium balance, and is a key regulatory component of the cardiovascular system. PSH + BIR + IV 2 ANGPT2 Tie-2 signaling / Hemostasis ANGPT2 inhibits the Tie-2 signaling pathway and regulates vascular stability, neogenesis and inflammatory responses. PSH + BIR + IV 3 ATP1A1 Ion transport by P-type ATPases Drives ion transport across membranes via Na \(\:{\text{}}^{\text{+}}\) /K \(\:{\text{}}^{\text{+}}\) -ATPase to maintain membrane potential and cellular function. PSH 4 BCHE Cholinesterase activity / Drug metabolism BCHE hydrolyzes a variety of choline esters and is involved in drug metabolism and neurotransmission regulation. PSH + BIR 5 BSG (CD147) Basigin interactions / Vascular wall cell-surface interactions CD147 is involved in cell adhesion, vascular immunity and metabolic regulation. PSH 6 ANGPT1 PI3K–Akt signaling & HIF-1 pathway ANGPT1 activates the Tie-2/PI3K–Akt pathway to promote vascular stabilization and anti-inflammatory homeostasis. PSH + BIR 7 IL6 IL6 family signaling (JAK/STAT, MAPK) IL6 activates JAK–STAT and MAPK signaling via gp130 and is involved in inflammation and immune regulation. BIR 8 TNF TNF signaling pathway TNF- \(\:\text{α}\) activates NF- \(\:\kappa\) B, MAPK and other pathways via TNFR1/2 to mediate inflammatory responses and cell fate decisions. BIR 9 VEGFA VEGF–VEGFR2 signaling VEGF-A promotes endothelial cell proliferation, migration and angiogenesis via VEGFR2. PSH 10 MMP9 ECM remodeling / Leukocyte migration MMP-9 degrades extracellular matrix and supports leukocyte migration and inflammatory signaling (e.g. TNF, IL-17). PSH + BIR 11 CXCL8 (IL-8) Chemokine signaling pathway CXCL8 mediates inflammatory cell chemotaxis and activation by attracting neutrophils, basophils and T cells via CXCR1/2. BIR 12 DPP4 GLP-1/GIP degradation pathway DPP4 is a surface serine peptidase that catalyzes degradation of GLP-1 and GIP, thereby regulating insulin secretion and glucose metabolism. PSH 13 IFNG (IFN- \(\:\text{γ}\) ) Interferon-gamma signaling IFN- \(\:\text{γ}\) binds to its receptor and activates the JAK–STAT pathway, which induces antiviral responses and enhances antigen presentation and MHC expression. IV + BIR 14 IL10 Interleukin-10 signaling IL10 inhibits expression of Th1 cytokines, MHC II and co-stimulatory molecules on macrophages and dendritic cells, providing immunosuppressive balance. PSH + BIR 15 IL1 \(\:\text{β}\) Interleukin-1 family signaling IL-1 \(\:\text{β}\) is a major inflammatory mediator, triggering febrile responses and contributing to prostaglandin synthesis, leukocyte migration and T cell activation. BIR 16 IMPDH2 De novo guanine nucleotide synthesis / Purine metabolism IMPDH2 is a key rate-limiting enzyme in guanosine nucleotide synthesis that oxidizes IMP to XMP, thereby maintaining the cellular GTP pool for DNA/RNA synthesis and cell proliferation. IV 17 JAK2 JAK–STAT signaling pathway JAK2 is activated and autophosphorylated by ligand-induced receptor engagement and subsequently phosphorylates STAT transcription factors (e.g. downstream of IL6 and IFN- \(\:\text{γ}\) ), regulating immunity, hematopoiesis and cell proliferation. PSH + BIR 18 MAP2K2 MAPK/ERK (Ras–Raf–MEK–ERK) cascade MAP2K2 (MEK2) is a classical MAPKK that activates ERK (MAPK1/3) by dual phosphorylation and directs cell proliferation, differentiation, migration and survival signaling. BIR 19 MARK2 Cell polarity / Microtubule regulation & mTOR–HIF-1 \(\:\text{α}\) signaling MARK2 (EMK1) regulates cell polarity and microtubule stabilization and promotes proliferation and metabolic reprogramming through the AMPK/mTOR/HIF-1 \(\:\text{α}\) pathway in certain cell types. BIR 20 MTOR mTOR signaling pathway mTOR is a central regulator of cell growth and metabolism, functioning as the catalytic subunit of mTORC1 and mTORC2. It integrates nutrient, growth factor, energy and stress signals to control protein synthesis, autophagy inhibition, lipid and nucleotide biosynthesis and mitochondrial metabolism. PSH 21 PDE5A cGMP–PKG signaling / Nitric oxide–cGMP pathway PDE5A specifically hydrolyzes cGMP, regulates smooth muscle relaxation and circulatory system function, and belongs to the hemostasis and cGMP signaling module. PSH 22 PPIF Mitochondrial permeability transition pore (mPTP) & apoptosis signaling PPIF encodes cyclophilin D, a mitochondrial matrix protein that serves as a key regulator of the mitochondrial permeability transition pore (mPTP). Under oxidative stress, calcium overload or ATP depletion, PPIF facilitates opening of the mPTP, leading to mitochondrial depolarization, ATP loss and release of pro-apoptotic factors such as cytochrome c, thereby triggering apoptotic or necrotic cell death. PSH 23 VCP ER-associated degradation (ERAD) / Ubiquitin–proteasome system VCP (p97) is an AAA \(\:{\text{}}^{\text{+}}\) ATPase primarily involved in extracting misfolded or aggregated proteins, directing 26S proteasome degradation, maintaining proteasome homeostasis and contributing to autophagy, ribosome-associated degradation and chromatin regulation. IV 24 C5AR1 Complement C5a receptor signaling / GPCR signaling C5a binding to C5AR1 triggers G i/o -protein signaling, induces Ca \(\:{\text{}}^{\text{2+}}\) release, MAPK activation and adenylate cyclase inhibition and mediates leukocyte chemotaxis, inflammatory responses and tissue damage as a key node in the complement cascade and innate immunity. BIR 25 CCR5 Chemokine receptor signaling (chemokine–GPCR pathway) CCR5 binds chemokines such as CCL3/4/5 and participates in inflammatory regulation by mediating intracellular Ca \(\:{\text{}}^{\text{2+}}\) elevation, chemotaxis and immune-cell activation via G i proteins. PSH + BIR 26 CRP Acute-phase response / Complement activation pathway CRP is a typical acute-phase response protein induced mainly by IL6. It binds to phospholipids on the surface of pathogens or apoptotic cells, interacts with C1q to activate the classical complement pathway, enhances phagocytic recognition and clearance and is an important factor in the early humoral immune response. BIR 27 BTK BCR signaling via BTK / G \(\:\text{βγ}\) activation pathway BTK is recruited to the membrane and activated by the G-protein \(\:\text{βγ}\) subunit and PIP3 in the BCR signaling pathway, then autophosphorylates and transduces downstream signals involved in B-cell development, differentiation, immune responses and inflammation, serving as a key regulatory kinase for B-cell function. BIR 28 BSG (CD147) Basigin interactions (vascular wall surface interactions) Basigin regulates extracellular matrix degradation, cell adhesion, migration and metabolic functions by promoting MMP synthesis (e.g. MMP-1/MMP-2) and interacting with caveolin-1, integrins and cyclophilin A, and is involved in angiogenesis, tissue growth and immunomodulation. PSH + BIR Network connectivity of herb–target–pathway interactions To further assess network structure, an integrated herb–target–pathway–function network was constructed (Fig. 5 ). High-frequency targets such as TNF, IL10, IL6, CXCL8, and IFNG exhibited strong connectivity, linking to multiple herbs and participating in numerous signaling pathways. Their hub-like behavior suggests that these targets serve as central nodes through which multidimensional therapeutic effects may be exerted. In contrast, low-frequency antiviral targets such as VCP and IMPDH2 showed limited connectivity, consistent with their more specialized roles. The overall target frequency distribution (Fig. 6 ) also reflected these trends, with major hubs concentrated within the PSH–BIR overlap and antiviral nodes forming only a minor fraction. Formula overlap and composition analysis A Venn diagram (Fig. 7 ) was generated to examine compositional overlap among the six formulas. The results revealed both shared and unique herbal components: several herbs were commonly used across formulas, such as Glycyrrhizae Radix et Rhizoma , Armeniacae Semen Amarum , and Ephedrae Herba , whereas others appeared only in one or two formulas. These findings suggest purposeful differentiation among formulas based on disease stage or clinical presentation. Similarity analysis and functional convergence Herbal similarity was quantified using the Jaccard similarity matrix (Fig. 8 ). Overall similarity remained low, with the highest similarity observed between LHQW and JHQG (Jaccard index = 0.385). In contrast, analysis of functional composition revealed that PSH/BIR ratios were highly consistent across formulas, ranging from 0.75 to 1.13 (mean \(\:\text{∼}\) 0.90 \(\:\text{±}\) 0.13) (Table 7 ; Fig. 8 ). This convergence indicates that despite substantial differences in herbal composition, the formulas maintain stable and balanced therapeutic profiles centered on PSH and BIR. These findings suggest that as long as the functional balance between promoting self-healing power and balancing immune response is preserved, therapeutic efficacy can be achieved even when herbal compositions differ. Table 7 Ratios of PSH/BIR in six CHM formulas. Counts of herbs assigned to PSH and BIR categories within each formula. PSH/BIR ratios quantify functional balance across formulas and reveal consistent predominance of host-directed mechanisms. Formula (abbr.) Total herbs PSH count BIR count PSH/BIR ratio Lianhua Qingwen (LHQW) 9 7 9 0.78 Qingfei Paidu (QFPD) 14 11 12 0.92 Jinhua Qinggan (JHQG) 9 9 8 1.13 Shufeng Jiedu (SFJD) 7 7 7 1.00 Xuanfei Baidu (XFBD) 10 8 10 0.80 Huashi Baidu (HSBD) 13 9 12 0.75 Discussion This study provides the first systematic attempt to classify the functions of CHM herbs used in infectious diseases according to three mechanistic categories— PSH, BIR, IV—derived from the host–pathogen interaction framework (Fig. 1 ). By integrating these functional definitions with standardized pathway annotation, we established a data-driven and mechanistically interpretable approach for linking herbal effects to molecular targets across six nationally recommended COVID-19 formulas. From the 46 herbs included in these formulas, 36 exhibited overlap with curated COVID-19–related therapeutic targets from TTD (Tables 5 and 6 ), forming the basis for functional classification and network analysis. Most herbs and targets fell within PSH, BIR, or their overlap, whereas IV-labeled herbs were infrequent and lacked robust supporting clinical evidence (Figs. 3 – 6 ). One major reason for the predominance of the PSH + BIR category is that anti-inflammatory actions are shared across both PSH and BIR, although it serves distinct purposes—resolution and tissue repair in PSH, and immune modulation in BIR. Similar to strategies observed in cancer immune evasion (Tang et al., 2020 ), pathogens often manipulate host immunity, necessitating a balanced therapeutic approach that CHM effectively provides.This overlap likely contributes to the large PSH–BIR intersection. Nevertheless, the overall functional distribution highlights a central therapeutic principle of CHM: restoring host homeostasis takes precedence over directly attacking pathogens. Under this paradigm, pathogen clearance emerges as a downstream consequence of enhanced repair capacity (PSH) and appropriately balanced immunity (BIR), rather than a primary therapeutic objective. Network analysis further supports this host-centered mechanism. High-frequency targets—including TNF, IL10, IL6, CXCL8, and IFNG—exhibited strong connectivity and involvement in multiple signaling pathways (Fig. 5 ). Their hub-like properties indicate that they play central roles in coordinating inflammation, immune responses, and tissue repair. In contrast, low-frequency antiviral targets such as VCP and IMPDH2 showed limited connectivity, consistent with their narrow mechanistic roles. This combination of broad-spectrum hubs and specialized antiviral nodes suggests potential for strategic tailoring of interventions to match disease stages or pathogen characteristics. Notably, classification of certain herbs into the IV group relied mainly on in vitro or preclinical findings. First, many in vitro antiviral assays employ concentrations exceeding physiologically achievable exposure; for example, paeoniflorin demonstrates intestinal absorption far below commonly used in vitro assay doses (Srinivas, 2010 ). Second, the antiviral activity of isolated constituents cannot be directly extrapolated to multi-component formulas; in LHQW, antiviral components constitute only approximately 9% of the formula, yet the full formula produces stronger viral clearance than isolated compounds (L.-C. Li et al., 2020 ). Overemphasizing direct antiviral constituents risks fragmenting the holistic formulation logic of CHM, which is fundamentally designed around PSH and BIR rather than IV. To address this issue, we systematically re-evaluated four herbs labeled as antiviral by examining assay type, target type, potency context (IC 50 /EC 50 ), and exposure plausibility. According to our operational criteria, IV-direct requires clinically attainable concentrations targeting viral components, and IV-indirect requires effects on host-dependent viral processes independent of PSH or BIR. None of the evaluated herbs met these criteria (Table 8 ), indicating that their observed antiviral effects are more plausibly mediated through PSH and/or BIR pathways. Table 8 Evaluation of herbs initially claimed to possess antiviral activity against SARS-CoV-2. Reassessment of commonly cited “antiviral” herbs based on current peer-reviewed evidence, graded using the evidence scale and adjudicated under the IV classification rules. Findings include evaluation of antiviral mechanism plausibility, exposure feasibility, and classification into PSH/BIR or IV. Herb Latest antiviral findings Evidence grade Adjudication Key sources Rhei Radix et Rhizoma ( Rheum palmatum ) Evidence is predominantly in silico (molecular docking/network pharmacology), suggesting anthraquinones (rhein, emodin, chrysophanol) may bind RdRp/ACE2. No wet-lab infection studies (cell or animal) or clinical trials demonstrate direct antiviral activity. SARS-CoV (2003) S–ACE2 blocking data are not transferable to SARS-CoV-2. PK data show oral C max far below putative effective concentrations. D (docking/network only; no wet-lab confirmation; exposure implausible) Not supported for IV-direct or IV-indirect. Findings better align with PSH/BIR (immune regulation and host protection). (Po-Wei, 2023 ; J. Qi, Dong, Wang, Zhang, et al., 2022 ; Xu et al., 2024 ; Zhang ChunLing et al., 2019 ) Pinelliae Praeparatum Rhizoma (processed Pinellia ternata ) No peer-reviewed wet-lab antiviral studies against SARS-CoV-2. Literature focuses on immune modulation, anti-inflammatory activity, and respiratory support (e.g., asthma models). Antiviral claims originate solely from docking/network analyses; no validated viral targets, EC 50 /IC 50 , or PK data. D (in silico only; no antiviral wet-lab data; exposure unknown) Not supported for IV-direct or IV-indirect. Functional profile aligns with BIR/PSH rather than pathogen-directed inhibition. (S. Lin et al., 2019 ; Peng et al., 2022 ; Tao et al., 2022 ) Astragali Radix ( Astragalus membranaceus ) No wet-lab evidence demonstrates direct anti–SARS-CoV-2 activity. Wet-lab studies support host-side effects: — immune balancing ( \(\:\text{↓}\) IL6/TNF- \(\:\text{α}\) ; Th1/Th2 modulation) — cytoprotection/antioxidant responses (Nrf2 activation, \(\:\text{↓}\) ROS). AS-IV has poor oral bioavailability; polysaccharides show limited systemic absorption. C (supports PSH/BIR only; no antiviral mechanism at plausible exposure) Not supported for IV-direct or IV-indirect. Mechanisms align with BIR + PSH (immune regulation + stress-protection). (Adesso et al., 2018b ; Minsook, 2008 ; Shen et al., 2019b ) Polygoni Cuspidati Rhizoma et Radix ( Polygonum cuspidatum ; resveratrol/polydatin/emodin) Extracts show pseudovirus entry inhibition (WT/Omicron) and 3CLpro suppression (IC 50 \(\:\text{≈}\) 0.015–0.04 mg/mL). However: — no SARS-CoV-2 replication assays for major constituents — extremely low oral bioavailability of resveratrol — extract-level IC 50 values not achievable in vivo Overall evidence is preclinical and exposure-implausible. C (enzyme/pseudovirus only; no systemic plausibility) Not supported for IV-direct. Findings classify best as PSH/BIR (host-side support). IV-indirect may have topical relevance (upper airway), but not systemic. (C. Lin et al., 2015b ; S. Lin, Wang, Tang, Lee, et al., 2022 ; Shiuan-Pey, 2012 ; Xu et al., 2021b ) Despite substantial heterogeneity in herbal composition across the six formulas (Table 5 ; Fig. 7 ), their PSH/BIR ratios remained stable (Fig. 8 ). This convergence demonstrates that formulas can differ widely in composition yet maintain comparable functional profiles. Such consistency aligns with CHM practice in which herbs with similar therapeutic properties may be substituted without compromising overall efficacy, provided the overarching balance between self-healing and immune regulation is preserved (Lyu et al., 2021 ; X. Zhang et al., 2021 ). Three herbs— Glycyrrhizae Radix et Rhizoma , Armeniacae Semen Amarum , and Ephedrae Herba —appeared in more than half of the formulas, underscoring their central therapeutic roles. Licorice exhibits broad anti-inflammatory and harmonizing effects via NF- \(\:\kappa\) B inhibition; bitter apricot kernel contributes bronchodilatory and anti-tussive actions; and ephedra provides bronchodilation and facilitates surface-defense responses (Gu et al., 2025 ; You et al., 2023 ). Collectively, these herbs enhance respiratory function, reduce inflammation, and promote recovery—consistent with their PSH/BIR classification. This study offers three conceptual innovations. First, it introduces the PSH/BIR/IV framework as a mechanistic classification for CHM herbs used in infectious diseases. Second, it classifies anti-inflammatory actions to both PSH and BIR but serving distinct biological functions. Third, it demonstrates that the reportedly claimed “antiviral” actions of certain herbs likely arise from PSH- and/or BIR-mediated mechanisms, reinforcing CHM as a fundamentally holistic, host-targeted therapeutic system. Several limitations should be acknowledged. Functional classification relies on currently available molecular target databases and may not fully capture the multidimensional pharmacodynamics of complex herbal mixtures. Although pathway annotations were standardized using KEGG, Reactome, and UniProt, final functional assignments required expert interpretation and thus involved some subjectivity. Furthermore, validation of the PSH–BIR model requires real-world clinical and mechanistic evidence. Future research should aim to elucidate biological processes underlying self-healing and its interaction with immune pathways. Integration of electronic health records, multi-omics datasets, and AI-based modeling (e.g., label-free phenotype classification (Hourani et al., 2023 )) may enable quantification of individual-level self-healing power and immune balance, helping to establish a standardized framework for diagnosis and treatment. In summary, this study established a mechanistic, data-driven framework for classifying the functions of CHM herbs used in infectious diseases into three strategic categories: PSH, BIR, and IV. We found that CHM treats infecious diseases mainly through PSH- and/or BIR-mediated host-directed mechanisms rather than direct viral inhibition. The stability of PSH/BIR ratios across formulas—despite substantial heterogeneity in herbal composition—highlights a core therapeutic principle of CHM: restoring host homeostasis takes precedence over pathogen-directed strategies. Declarations Competing Interest: The authors declare no conflict of interest. Funding: This study was supported by the Fundamental Research Fund for Central Universities (to J.S.), National Natural Science Foundation of China grant 31871363 (L.L.), National Natural Science Foundation of China grant 31900575 (L.L.), LiaoNing Revitalization Talents Program XLYC1907052 (L.L.), the 111 Project B16009 (L.L.), Key Laboratory of Bioresource Research and Development of Liaoning Province 2022JH13/10200026 (L.L.). Author Contribution JS conceptualized ideas, designed and managed the projects, wrote and edited the manuscript; FN developed methodology, curated data, performed analysis, wrote and edited the manuscript. JL supervised the project, reviewed and edited the manuscript; YZ, LL, and KC reviewed and edited the manuscript. Data Availability The data generated and analyzed during this study, including computer scripts, are either reported in the manuscript or available from the corresponding authors upon reasonable request. 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Am J Chin Med 52(07):1925–1967. https://doi.org/10.1142/S0192415X24500757 You L, Dai Q, Zhong X (2023) & others. Clinical evidence of three traditional Chinese medicine drugs and three herbal formulas for COVID-19: A systematic review and meta-analysis. Journal of Integrative Medicine , 21 (5), 441–454. https://doi.org/10.1016/j.joim.2023.08.001 Zhang C, Fan L, Fan S (2019) & others. Cinnamomum cassia Presl: A review of its traditional uses, phytochemistry, pharmacology and toxicology. Molecules , 24 (19), 3473 Zhang ChunLing ZC, Fan LinHong FL, Fan ShunMing FS, Wang JiaQi WJ, Ting L, Yu LTT, Chen TY, ZhiMin CZ, Yu LingYing YL (2019) Cinnamomum cassia Presl: A review of its traditional uses, phytochemistry, pharmacology and toxicology. https://www.cabidigitallibrary.org /doi/full/10.5555/20193486162 Zhang T, Li T, Zhao F, Li T, Zhang M, Jin P (2024) Effectiveness of seven oral traditional Chinese medicines against mild or moderate COVID-19: An updated systematic review and network meta-analysis. Heliyon 10(15):e35081. https://doi.org/10.1016/j.heliyon.2024.e35081 Zhang X, Qiu H, Li C, Cai P, Qi F (2021) The positive role of traditional Chinese medicine as an adjunctive therapy for cancer. Biosci Trends 15(5):283–298. https://doi.org/10.5582/bst.2021.01318 Additional Declarations No competing interests reported. Supplementary Files Supplementaldata.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 15 May, 2026 Reviewers agreed at journal 12 May, 2026 Reviewers agreed at journal 09 May, 2026 Reviews received at journal 04 May, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 26 Jan, 2026 Submission checks completed at journal 26 Jan, 2026 First submitted to journal 25 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8693251","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":580881001,"identity":"4b9d5993-3742-4be9-a505-df57a6ab83e5","order_by":0,"name":"Fengyun Nie","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Fengyun","middleName":"","lastName":"Nie","suffix":""},{"id":580881011,"identity":"7b838dd7-1361-419e-8d01-088366bba8d2","order_by":1,"name":"Yan Zhuang","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Zhuang","suffix":""},{"id":580881012,"identity":"a0f7617f-b1b2-4d5b-a68f-430f26e1d69d","order_by":2,"name":"Ke Chen","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Ke","middleName":"","lastName":"Chen","suffix":""},{"id":580881013,"identity":"bf881e57-f843-41a5-b9b4-2e0657256cce","order_by":3,"name":"Lijun Liu","email":"","orcid":"","institution":"Northeastern University","correspondingAuthor":false,"prefix":"","firstName":"Lijun","middleName":"","lastName":"Liu","suffix":""},{"id":580881015,"identity":"05b08ac2-a06c-444a-a1e4-7643d9030b78","order_by":4,"name":"Jiangli Lin","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Jiangli","middleName":"","lastName":"Lin","suffix":""},{"id":580881022,"identity":"cab2be1a-5519-489b-b817-ebb0a1262747","order_by":5,"name":"Jianjun Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACxmYgIQFmMh+ACB0gXgtbAnFakACPAXFamNuZnz2wbLtjb3C75/OHn20Mcnw3Ehg/F+B1GJu5gWTbs8QNd85uk+xtYzCWvJHALD0DrxYGMwnJtsMJBjdytzEztjEkbriRwMbMg1cL+zeQFnuDGzmPPwO11BOhhQdsC+OGGzkM0kAtQOsIaymTkDh3OHHmjTQzyZ5zEoYzzzxslsanxbD/+DZpibLD9nw3kh9/+FFmI893PPngZ7xaGoABLYHgg5iMDXg0MDDIg5R8wKtkFIyCUTAKRjwAAKu+ShVXiRxsAAAAAElFTkSuQmCC","orcid":"","institution":"Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"Jianjun","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2026-01-25 14:55:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8693251/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8693251/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102297940,"identity":"9590f630-0316-4158-9ac1-fb1041beca4e","added_by":"auto","created_at":"2026-02-10 10:29:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":17861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelf-healing power is the major determinant of host–pathogen interaction outcomes.\u003c/strong\u003e Pathogen invasion perturbs the host and triggers immune responses aimed at pathogen clearance, but both pathogen virulence and dysregulated immunity can cause collateral damage. Three principal therapeutic strategies emerge: inhibiting the pathogen, regulating the immune response, and promoting self-healing power to repair damage. The best combination of the strategies is that promoting self-healing power (PSH) increases the host’s ability to control and repair the damages, raising the safety threshold of immune responses for effective pathogen clearance, and at the same time balancing immune response (BIR) ensures effective control of pathogen but its collateral damage falls within the repairing capacity of self-healing mechanism. This combination usually can cure infectious diseases without direct inhibition of pathogens using antimicrobial drugs.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/7cfc35c06c05e9e3a1e237da.png"},{"id":102294123,"identity":"c47f90a0-1219-4e44-8ec5-7d6b8dc5a59d","added_by":"auto","created_at":"2026-02-10 09:46:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":24984,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWorkflow for data acquisition, filtering, and herb–target convergence.\u003c/strong\u003e The flowchart summarizes the integration of two data streams: 46 herbs extracted from six nationally recommended CHM formulas (with targets from CHMSP and HERB), and 118 curated COVID-19 therapeutic targets from TTD. Cross-validation yielded 36 overlap-positive herbs used for all downstream analyses.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/fc9b84502eef7081ce23ee66.png"},{"id":102294124,"identity":"cffbfaca-1c5d-408d-87fc-d42df034f258","added_by":"auto","created_at":"2026-02-10 09:46:28","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":373690,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional classification of herbs across six COVID-19 formulas.\u003c/strong\u003e Venn diagrams illustrate the distribution of herbs among three therapeutic functional categories—PSH, BIR, and IV—and their combinations for each formula and for the combined dataset. Numbers indicate the herbs in each functional subset. An interactive version with detailed herb identities is provided in the Appendix.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/501d714a05e9f902b4cd649e.jpeg"},{"id":102298104,"identity":"7b0b7441-4319-4ae6-a8c9-1913d10cbbc4","added_by":"auto","created_at":"2026-02-10 10:30:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":527097,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional classification of molecular targets associated with CHM herbs.\u003c/strong\u003e Venn diagrams show the distribution of overlapping molecular targets across PSH, BIR, IV, and their combinations. Target counts correspond to specific genes or proteins derived from the 36 overlap-positive herbs. An interactive version with target-level details is available in the Appendix.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/c4109b23c54621042a4f8c5d.png"},{"id":102294130,"identity":"e96e0158-8114-4dfa-998a-1075098fb44e","added_by":"auto","created_at":"2026-02-10 09:46:29","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":747210,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntegrated network of formulas, herbs, molecular targets, signaling pathways, and functional categories.\u003c/strong\u003eThe network connects six formulas to their constituent herbs, the top 10 most frequent overlapping targets, annotated signaling pathways, and therapeutic functional labels. Node colors denote formulas (red), herbs (orange), targets (blue), pathways (green), and functional categories (purple). Target selection was based on frequency across the 36 overlap-positive herbs.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/61a7e50c1ed68139c23eaad9.png"},{"id":102297933,"identity":"336a9f0d-fe33-4e4e-8441-07e19311deae","added_by":"auto","created_at":"2026-02-10 10:29:45","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":59771,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFrequency distribution of overlapping molecular targets.\u003c/strong\u003e Bar chart ranking molecular targets by their frequency of occurrence among the 36 herbs. Higher frequencies indicate greater representation and possible centrality in therapeutic mechanisms.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/377716a518e44c87b25b6148.png"},{"id":102297973,"identity":"47d518bd-cab0-456a-a5fe-470c4840cf84","added_by":"auto","created_at":"2026-02-10 10:29:56","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":89548,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverlap of herbs among six COVID-19 CHM formulas.\u003c/strong\u003e(A) Venn diagram showing the herb overlap across formulas. (B) Matrix quantifying the number of shared herbs between formula pairs. The analysis highlights both common and formula-specific herbs.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/c9c6a1eb5060e084c2799a19.png"},{"id":102294127,"identity":"261561d5-89ab-40e0-9f04-42967f28a071","added_by":"auto","created_at":"2026-02-10 09:46:28","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":132146,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional and compositional similarity among COVID-19 CHM formulas.\u003c/strong\u003e (A) Heatmap of PSH/BIR ratios across formulas, reflecting functional differences. (B) Jaccard similarity matrix comparing herbal compositions. Higher values indicate greater similarity in herb usage between formula pairs.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/5d0772be74e3938b7ec63f61.png"},{"id":102745380,"identity":"176a7b91-7b9a-4ad7-b866-aa0a31e30598","added_by":"auto","created_at":"2026-02-16 08:47:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3835326,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/e7584873-e23f-497e-a4ec-917bb608268a.pdf"},{"id":102294129,"identity":"cc208b4d-43ea-480f-9756-7ebafb3adc01","added_by":"auto","created_at":"2026-02-10 09:46:28","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":749972,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaldata.docx","url":"https://assets-eu.researchsquare.com/files/rs-8693251/v1/6c59575099b5482451ea4444.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Chinese herbal medicine treats COVID-19 by promoting self-healing power and balancing immune response: A functional classification analysis integrating molecular targets and pathways","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHomeostasis is fundamental for maintaining optimal physiological function and survival (Cannon, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1929\u003c/span\u003e). Organisms have evolved diverse mechanisms to preserve internal stability in the face of external and internal perturbations. When these mechanisms are disrupted, disease arises (Kotas \u0026amp; Medzhitov, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Medzhitov et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Scully, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Infectious diseases represent a typical breakdown of homeostasis and remain a global priority for disease control (Holmes et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) : pathogen invasion causes tissue damage through toxin production, metabolic competition, and other virulence factors, while the host immune response\u0026mdash;although essential for pathogen clearance\u0026mdash;can itself inflict collateral damage through excessive or dysregulated inflammation. Thus, the pathology of infectious diseases reflects the combined injurious effects of pathogen virulence and host immune responses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Correspondingly, three strategic approaches exist for treating infectious diseases: inhibiting the pathogen, regulating the immune response, and promoting the host\u0026rsquo;s intrinsic capacity to repair damage, herein referred to as \u0026ldquo;self-healing power\u0026rdquo; (Sun, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor decades, antimicrobial drugs\u0026mdash;including antibiotics, antivirals, and antiparasitic agents\u0026mdash;have formed the backbone of infectious disease treatment. However, this pathogen-directed therapy now faces serious challenges. Virtually all major pathogens have developed resistance to available antimicrobial agents, while the development of new drugs is slow, costly, and increasingly unable to keep pace with emerging resistance(Reardon, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In parallel, immunosuppressive or anti-inflammatory agents used to control hyperinflammation\u0026mdash;such as glucocorticoids or cytokine inhibitors\u0026mdash;also have significant limitations. Inflammatory pathology caused by dysregulated immune responses, including cytokine storm in COVID-19, lipopolysaccharide (LPS)\u0026ndash;induced septic shock, and granuloma-associated tissue damage in tuberculosis, is now recognized as a major determinant of disease severity (Wright, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Evans et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Dorhoi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Although anti-inflammatory interventions can improve outcomes in selected settings, excessive immunosuppression compromises pathogen clearance and carries substantial systemic side effects (Patel et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Russell et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Collectively, these challenges underscore the urgent need for new therapeutic paradigms that move beyond a purely pathogen-centered approach. Furthermore, the increasing prevalence of post-acute sequelae (Long COVID) highlights the critical need for therapies that support long-term tissue repair and functional recovery (Fleischer et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Izquierdo-Condoy et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChinese herbal medicine (CHM) has long been regarded as a holistic medical system that restores health by maintaining or re-establishing homeostasis (Jin et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Developed in ancient times without knowledge of microbial pathogens, CHM formulas were not designed to target pathogens directly. Based on CHM theories, instead, they were constructed to correct imbalances within the host. Nevertheless, substantial evidence indicates that CHM can effectively treat infectious diseases (Y. Ma et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; F. Qi \u0026amp; Tang, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Recent bibliometric analyses have further confirmed the growing focus on CHM\u0026rsquo;s capacity for immune system modulation (Lei \u0026amp; Chen, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). During the COVID-19 pandemic, CHM was widely implemented in China and showed notable clinical benefits (Lyu et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; You et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Multiple formulas were developed and applied at different disease stages, and systematic reviews and clinical studies have attributed their therapeutic effects to several host-centered actions, including protection and repair of tissues and organs, modulation of inflammation, regulation of immune responses, and antiviral activity (Gu et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo elucidate the mechanisms underlying the efficacy of CHM in infectious diseases, we recently proposed that CHM functions as a host-based medicine. In this model, CHM exerts its therapeutic effects primarily by promoting self-healing power and balancing immune responses, rather than directly inhibiting pathogens (Sun, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This concept was formalized mathematically into a host\u0026ndash;pathogen interaction (HPI) equation \u003cem\u003eH\u0026thinsp;=\u0026thinsp;S/(I\u0026thinsp;+\u0026thinsp;P/I)\u003c/em\u003e, where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{H}\\)\u003c/span\u003e\u003c/span\u003e denotes host health status, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{S}\\)\u003c/span\u003e\u003c/span\u003e represents the level of self-healing power, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{I}\\)\u003c/span\u003e\u003c/span\u003e reflects the degree of immune response, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{P}\\)\u003c/span\u003e\u003c/span\u003e represents pathogen load. This framework highlights a central principle: robust self-healing power enables the host to repair damage caused by both pathogen and immune response, thereby raising the threshold at which immune activation remains safe and effective. Conversely, immune responses must be tightly balanced\u0026mdash;strong enough to eliminate pathogens but not so excessive that they overwhelm the host\u0026rsquo;s repair capacity.\u003c/p\u003e \u003cp\u003eThis model aligns closely with core principles of CHM, encapsulated in the classical tenet \u0026ldquo;fu zheng qu xie, yin yang ping heng\u0026rdquo;(\u0026ldquo;扶正祛邪, 阴阳平衡\u0026rdquo;), meaning \u0026ldquo;promote the Righteous Qi, dispel the Evil Qi, and maintain Yin\u0026ndash;Yang balance.\u0026rdquo; In CHM theory, Righteous Qi represents the body\u0026rsquo;s intrinsic capacity to repair damage and restore health, corresponding to self-healing power. Promoting Righteous Qi is a foundational therapeutic principle: when it is deficient, it should be strengthened; when it is constrained by pathological factors (Evil Qi), these factors should be removed to restore function. Evil Qi does not simply correspond to microbial pathogens, but more broadly to pathological processes\u0026mdash;such as blood and qi stagnation, phlegm accumulation, and fluid retention\u0026mdash;that impair self-healing. Similarly, Yin\u0026ndash;Yang balance reflects both the balance within immune responses and the broader balance between immune activity and self-healing capacity.\u003c/p\u003e \u003cp\u003eTo further evaluate this host-centered model, we analyzed six CHM formulas that were officially recommended for COVID-19 treatment in China (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Together, these formulas comprise 46 herbs. Using an herb\u0026ndash;target database and 118 COVID-19 therapeutic targets from the Therapeutic Target Database (TTD), we classified each herb into three functional categories: promoting self-healing power (PSH), balancing immune response (BIR), and inhibiting virus (IV). Across all six formulas, PSH and BIR emerged as the predominant functional modes of action, whereas IV functions were rare. Although some herbs have been reported to show antiviral effects in vitro, few have demonstrated definitive clinical efficacy in directly inhibiting viral entry or replication. Notably, despite sharing less than 40% overlap in herbal composition, the six formulas exhibited strikingly consistent PSH/BIR ratios. These findings suggest that enhancing self-healing power and balancing immune responses constitute the core mechanisms by which CHM treats infectious diseases, and that herbs with similar PSH/BIR profiles may be functionally interchangeable across formulas.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDefinition of therapeutic functional categories\u003c/h2\u003e \u003cp\u003eTo classify the therapeutic roles of herbs in treating infectious diseases, three functional categories were predefined based on the host\u0026ndash;pathogen interaction framework (Sun, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e): promoting self-healing power (PSH), balancing immune response (BIR), and inhibiting virus (IV) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). PSH refers to biological processes that restore structural and functional integrity by promoting inflammation resolution, tissue repair and regeneration, cytoprotection, and organ protection. BIR denotes mechanisms that modulate the magnitude and timing of innate and adaptive immune responses to achieve effective pathogen control while minimizing host injury. IV includes two mechanistic types: (i) indirect inhibition via regulation of host-dependent factors required for viral entry, replication, or assembly, and (ii) direct inhibition via interference with viral proteins or enzymes at exposure levels plausible in vivo. These operational definitions informed all subsequent labeling of molecular targets.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eDefinitions of the three therapeutic strategies used for classifying herbal functions.\u003c/b\u003e Definitions and concise descriptions of the three therapeutic strategies used to classify herbal actions: PSH, BIR, and IV. Both indirect-IV and direct-IV are defined to guide downstream functional annotation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTherapeutic strategies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition (concise)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRestores structural and functional integrity by resolving inflammation and activating programs of tissue repair, regeneration, and cytoprotection or organ protection.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegulates the intensity and timing of innate and adaptive inflammatory responses to achieve effective pathogen clearance while minimizing host tissue injury.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndirect: Restricts viral binding, entry, replication, or assembly by modulating host-dependent factors (e.g., receptors, cofactors, cellular processes).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDirect: Impairs viral binding, entry, or replication through direct action on viral proteins, viral enzymes, or virus\u0026ndash;receptor interactions at clinically plausible exposure levels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe workflow for data acquisition, filtering, and herb\u0026ndash;target convergence is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSelection of CHM formulas and constituent herbs\u003c/h3\u003e\n\u003cp\u003eSix CHM formulas officially recommended by the National Health Commission of China for the treatment of COVID-19 were selected: Lianhua Qingwen (LHQW), Qingfei Paidu Decoction (QFPD), Jinhua Qinggan (JHQG), Shufeng Jiedu (SFJD), Xuanfei Baidu (XFBD), and Huashi Baidu (HSBD) (Lyu et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; You et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; T. Zhang et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Across these formulas, a total of 46 unique constituent herbs were identified. Herb names were standardized according to official pharmacognostic nomenclature (Chinese Pharmacopoeia Commission, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These herbs formed the basis for downstream analyses of functional classification and herb\u0026ndash;target\u0026ndash;pathway mapping.\u003c/p\u003e\n\u003ch3\u003eCollection of herb-derived molecular targets\u003c/h3\u003e\n\u003cp\u003eThe molecular targets associated with each herb were collected from three curated databases: the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (CHMSP) (Ru et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), the High-throughput Experiment- and Reference-guided database (HERB) (Fang et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and the Therapeutic Target Database (TTD) (Chen et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Only targets with experimental evidence or high-confidence computational predictions were retained. All herb-derived targets were then aggregated and prepared for overlap screening with COVID-19 therapeutic targets.\u003c/p\u003e\n\u003ch3\u003eCOVID-19 therapeutic target dataset\u003c/h3\u003e\n\u003cp\u003eA curated list of therapeutic targets relevant to COVID-19 was retrieved from the TTD. A total of 118 targets were included, representing host or pathogen-associated factors implicated in viral entry, replication, immune dysregulation, inflammation, or organ injury. These targets were selected based on experimental evidence or expert curation reported in TTD and served as the reference set for identifying herb\u0026ndash;COVID-19 target overlap. All targets were standardized by gene/protein symbols prior to matching.\u003c/p\u003e\n\u003ch3\u003eTarget matching and functional labeling\u003c/h3\u003e\n\u003cp\u003eHerb-derived molecular targets were cross-validated against the 118 COVID-19 therapeutic targets to identify overlapping targets. Herbs that shared at least one target with the COVID-19 reference set were designated as \u0026ldquo;overlap-positive\u0026rdquo; and included in functional analyses. Each overlapping target was labeled with one or more therapeutic categories (PSH, BIR, IV) according to the operational definitions described above (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Multi-label assignment was permitted when targets were mechanistically relevant to multiple functions (e.g., IL10 contributing to both inflammation resolution and immune regulation). Herb-level functional labels were then determined by aggregating the labels of their overlapping targets. This procedure yielded a standardized classification scheme for all 36 overlap-positive herbs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eOperational rules for assigning molecular targets and pathways to the three therapeutic strategies.\u003c/b\u003e Decision keywords, pathway exemplars, and representative molecular targets used to assign biological roles into PSH, BIR, and IV categories. Multi-label assignment is permitted when mechanistic functions overlap. Standardization is based on KEGG, Reactome, and UniProt annotations.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTherapeutic strategies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecision keywords\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExample pathways\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExample targets/factors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eresolution; pro-resolving; repair; regeneration; cytoprotection; organ-protection; antioxidant; Nrf2; autophagy; ER stress; ECM remodeling; angiogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIL10 signaling; Nrf2-mediated oxidative stress response; mTOR; VEGF\u0026ndash;VEGFR2; ECM\u0026ndash;receptor interaction; ER stress/ERAD; autophagy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIL10; NFE2L2 (Nrf2); MTOR; VEGFA/KDR; MMPs/TIMPs; HSPs; SIRT1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epro-inflammatory; cytokine; innate; adaptive; NF-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\kappa\\)\u003c/span\u003e\u003c/span\u003eB; JAK/STAT; MAPK; TLR; complement; chemokine; inflammasome; \u0026ldquo;balance immune response\u0026rsquo;\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTNF signaling; IL6 signaling; TLR4 cascade; JAK\u0026ndash;STAT; NF-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\kappa\\)\u003c/span\u003e\u003c/span\u003eB pathway; NLRP3 inflammasome; Complement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTNF; IL6; IL1B; IFNG; TLR4; JAK2/STAT3; NFKB1/RELA; CXCL8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIndirect\u003c/b\u003e: viral entry; replication; assembly; host factor; receptor; cofactor; ACE2; BSG(CD147); TMPRSS2; IMPDH2; VCP; ERAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReceptor-mediated viral entry; Endocytosis; ERAD\u0026ndash;virus interface; Purine metabolism/IMPDH2-related\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eACE2; BSG(CD147); TMPRSS2; FURIN; IMPDH2; VCP; HSP90; PIKfyve\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDirect\u003c/b\u003e: viral protease; polymerase; RdRp; 3CL\u003csup\u003epro\u003c/sup\u003e/M\u003csup\u003epro\u003c/sup\u003e; PL\u003csup\u003epro\u003c/sup\u003e; spike; neuraminidase; capsid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eViral RNA replication; Proteolytic processing of viral polyprotein; Viral fusion/entry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSARS-CoV-2 RdRp (NSP12); 3CL\u003csup\u003epro\u003c/sup\u003e/M\u003csup\u003epro\u003c/sup\u003e (NSP5); PL\u003csup\u003epro\u003c/sup\u003e; Spike\u0026ndash;ACE2 interface; Influenza NA; HIV RT/PR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePathway annotation and enrichment analysis\u003c/h2\u003e \u003cp\u003eTo contextualize biological functions, all overlapping targets were annotated for signaling pathways using three authoritative databases: the Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa \u0026amp; Goto, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), the Reactome pathway database (Gillespie et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and UniProtUniProt (The UniProt Consortium, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Pathways associated with each target were retrieved and harmonized across databases to ensure standardized terminology. Enriched pathways related to inflammation regulation, immune activation, tissue repair, oxidative stress, viral entry, viral replication, or host-dependent viral processes were identified. These annotations were subsequently used to interpret therapeutic functions, support PSH/BIR/IV classification, and construct the integrated herb\u0026ndash;target\u0026ndash;pathway network.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eNetwork construction and visualization\u003c/h3\u003e\n\u003cp\u003eAn integrated herb\u0026ndash;target\u0026ndash;pathway\u0026ndash;function network was constructed to visualize relationships among formulas, constituent herbs, their overlapping molecular targets, associated signaling pathways, and functional labels (PSH, BIR, IV). Herbs were connected to their corresponding targets, and each target was linked to annotated pathways. Targets were further mapped to therapeutic categories based on functional labels. Node types were represented by distinct colors (formulas, herbs, targets, pathways, functions), and edges denoted curated or database-supported interactions. Network construction and visualization were performed to identify hub-like targets, functional clusters, and cross-formula similarities that contribute to PSH/BIR-dominant therapeutic patterns.\u003c/p\u003e\n\u003ch3\u003eEvidence curation and antiviral adjudication\u003c/h3\u003e\n\u003cp\u003eBecause several herbs have reportedly been attributed \u0026ldquo;antiviral\u0026rdquo; properties (L.-C. Li et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; S. Lin, Wang, Tang, \u0026amp; others, 2022; Xu et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e), \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003ea\u003c/span\u003e structured evidence curation and adjudication process was applied to evaluate whether such claims met criteria for direct or indirect viral inhibition (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Eligible evidence included: (i) biochemical assays measuring viral enzyme inhibition (e.g., 3CL\u003csup\u003epro\u003c/sup\u003e, PL\u003csup\u003epro\u003c/sup\u003e, RdRp), (ii) cell-based infection assays assessing viral entry or replication, (iii) in vivo infection models with virological endpoints, and (iv) clinical studies reporting viral load reduction. In silico studies (Kadioglu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ren et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and supra-physiological in vitro assays were included only as contextual information and were not considered sufficient evidence for IV labeling.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eAdjudication checklist for inhibiting virus (IV) labels.\u003c/b\u003e Minimum evidence thresholds required to classify antiviral effects into IV-direct or IV-indirect. Criteria incorporate exposure plausibility (free C\u003csub\u003emax\u003c/sub\u003e vs. EC\u003csub\u003e50\u003c/sub\u003e/IC\u003csub\u003e50\u003c/sub\u003e), mechanism specificity (viral-protein vs. host-factor dependence), and wet-lab evidence hierarchy. Docking-only findings fail to qualify.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDimension\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimum to qualify\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV-direct\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eViral-protein mechanism (3CLpro, PLpro, RdRp, or spike\u0026ndash;ACE2 interference) \u003cem\u003eand\u003c/em\u003e plausible human exposure (free C\u003csub\u003emax\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{≳}\\)\u003c/span\u003e\u003c/span\u003e EC\u003csub\u003e50\u003c/sub\u003e/IC\u003csub\u003e50\u003c/sub\u003e). Docking-only studies or supra-physiological in vitro concentrations do not qualify.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV-indirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHost-dependent restriction mechanisms (e.g., ACE2, TMPRSS2, BSG, ERAD/chaperone systems, nucleotide synthesis) not fully explainable by immune-regulation or tissue-repair processes. Immune-only or repair-only readouts are excluded.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Minimum inclusion thresholds are applied after an exposure-plausibility check (free C\u003csub\u003emax\u003c/sub\u003e versus EC\u003csub\u003e50\u003c/sub\u003e/IC\u003csub\u003e50\u003c/sub\u003e). Non-IV mechanisms are adjudicated under PSH/BIR as appropriate. Abbreviations: C\u003csub\u003emax\u003c/sub\u003e, maximum plasma concentration; EC\u003csub\u003e50\u003c/sub\u003e/IC\u003csub\u003e50\u003c/sub\u003e, half-maximal effective/inhibitory concentration.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eExposure plausibility was assessed by comparing reported EC\u003csub\u003e50\u003c/sub\u003e/IC\u003csub\u003e50\u003c/sub\u003e values with achievable free C\u003csub\u003emax\u003c/sub\u003e under clinically relevant dosing (Y. Li et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; S.-P. Lin et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Srinivas, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). IV-direct designation required inhibition of viral proteins or virus\u0026ndash;receptor interactions at physiologically plausible exposure levels. IV-indirect designation required effects on host factors essential for viral life cycles (e.g., ACE2, TMPRSS2, IMPDH2, ER-associated degradation factors) that could not be explained by immune or repair mechanisms. Claims not meeting these criteria were adjudicated as PSH- and/or BIR-mediated rather than IV-mediated. This process ensured that antiviral labels were assigned according to rigorous, mechanism-based rules and evidence grading (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eGrading scale for evaluating antiviral evidence of selected herbs.\u003c/b\u003e Four-tier evidence grading system (A\u0026ndash;D) used to evaluate the strength and clinical relevance of reported antiviral findings. The scale prioritizes human clinical evidence (Grade A) and in vivo infection models (Grade B), while in vitro or biochemical assays conducted at plausible exposure levels are graded as C. Docking-only studies, surrogate-virus models, and in vitro effects observed at supraphysiological concentrations are assigned Grade D.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman clinical data with virological endpoints.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIn vivo animal infection models demonstrating reductions in viral load or pathological improvement.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIn vitro cell-based or biochemical antiviral assays conducted at clinically plausible exposure levels (EC\u003csub\u003e50\u003c/sub\u003e/IC\u003csub\u003e50\u003c/sub\u003e consistent with free C\u003csub\u003emax\u003c/sub\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIn silico analyses only, or in vitro antiviral effects observed at supra-physiological concentrations; includes results based on surrogate viruses without translational support.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSoftware and reproducibility\u003c/h2\u003e \u003cp\u003eAll data processing, target matching, pathway annotation, and graphical outputs were generated using Python 3.12.0 with standard scientific libraries (NumPy, pandas (McKinney, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), matplotlib, seaborn, and networkx (Hagberg et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e)). Analyses were performed in a reproducible workflow, and all scripts used for data integration and network construction are available upon request.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eOverview of herb\u0026ndash;COVID-19 target overlap\u003c/h2\u003e \u003cp\u003eAmong the 46 herbs included in the six nationally recommended COVID-19 formulas, 36 shared at least one molecular target with the 118 curated COVID-19 therapeutic targets from TTD. These 36 herbs constituted the analysis cohort for functional classification and for construction of the herb\u0026ndash;target\u0026ndash;pathway network. A complete list of overlap-positive herbs is provided in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eFunctional classification of 36 CHM herbs and their corresponding molecular targets.\u003c/b\u003e List of the 36 herbs identified across six representative CHM formulas, together with their target genes/proteins, associated signaling pathways, and their assigned functional categories (PSH, BIR, IV or combinations). Functional labels were adjudicated based on pathway-level and mechanistic evidence. The pharmacological activities and functional assignments of key herbs were supported by species-specific reviews and mechanistic studies (Adesso et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e; C. Lin et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015a\u003c/span\u003e; C. Ma et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; J. Qi, Dong, Wang, \u0026amp; others, 2022; R\u0026iacute;os, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Shen et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e; C. Zhang et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHerb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLHQW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQFPD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eJHQG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSFJD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eXFBD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHSBD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTargets\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMolecular pathways\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eClass.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePogostemonis Herba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eC5AR1; CXCL8; IFNG; IL1B; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eComplement C5a receptor signaling / GPCR signaling; Chemokine signaling pathway; Interferon gamma signaling; Interleukin 1 family signaling; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRhei Radix et Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eACE; IL1B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRenin\u0026ndash;angiotensin system; Interleukin 1 family signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;IV\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCinnamomi Ramulus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCCR5; CXCL8; IL10; MAP2K2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCC chemokine receptor signaling (chemokine\u0026ndash;GPCR pathway); Chemokine signaling pathway; Interleukin 10 signaling; MAPK/ERK (Ras\u0026ndash;Raf\u0026ndash;MEK\u0026ndash;ERK) cascade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCXCL8; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eChemokine signaling pathway; IL6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePinelliae Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBCHE; IL10; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCholinesterase activity / Drug metabolism; Interleukin 10 signaling; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZingiberis Rhizoma Recens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eATP1A1; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eIon transport by P-type ATPases; IL6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDioscoreae Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBCHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCholinesterase activity / Drug metabolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCitri Reticulatae Pericarpium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVerbenae Herba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDPP4; IFNG; IL10; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eGLP 1/GIP degradation pathway; Interferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhragmitis Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCCR5; CXCL8; DPP4; IL10; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCC chemokine receptor signaling (chemokine\u0026ndash;GPCR pathway); Chemokine signaling pathway; GLP 1/GIP degradation pathway; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAtractylodis Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIL10; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eInterleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCitri Grandis Exocarpium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePinelliae Praeparatum Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eVCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eProtein quality control: ER associated degradation (ERAD) / Ubiquitin\u0026ndash;proteasome system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTsaoko Fructus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eIL 6 family signaling (JAK/STAT, MAPK)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBupleuri Radix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eANGPT2; CXCL8; IL10; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTie 2 Signaling / Hemostasis; Chemokine signaling pathway; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR+IV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsteris Radix et Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIFNG; IL10; IL1B; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eInterferon gamma signaling; Interleukin 10 signaling; Interleukin 1 family signaling; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarfarae Flos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBCHE; IL10; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCholinesterase activity / Drug metabolism; Interleukin 10 signaling; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFritillariae Thunbergii Bulbus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDPP4; IL10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eGLP 1/GIP degradation pathway; Interleukin 10 signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArctii Fructus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBCHE; IL10; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCholinesterase activity / Drug metabolism; Interleukin 10 signaling; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMenthae Haplocalycis Herba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBCHE; IL1B; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCholinesterase activity / Drug metabolism; Interleukin 1 family signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescurainiae Semen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCRP; IL10; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAcute phase response / Complement activation pathway; Interleukin 10 signaling; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAtractylodis Macrocephalae Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBCHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCholinesterase activity / Drug metabolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnemarrhenae Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePDE5A; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ecGMP\u0026ndash;PKG signaling pathway / Nitric oxide\u0026ndash;cGMP pathway; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll - grass of Dahurian Patrinia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIFNG; IL10; IL1B; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eInterferon gamma signaling; Interleukin 10 signaling; Interleukin 1 family signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAstragali Radix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eACE; BCHE; C5AR1; CXCL8; IFNG; IL10; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRenin\u0026ndash;angiotensin system; Cholinesterase activity / Drug metabolism; Complement C5a receptor signaling / GPCR signaling; Chemokine signaling pathway; Interferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;IV+BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEphedrae Herba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBCHE; CXCL8; IFNG; IL10; IL1B; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCholinesterase activity / Drug metabolism; Chemokine signaling pathway; Interferon gamma signaling; Interleukin 10 signaling; Interleukin 1 family signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsatidis Radix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBTK; IFNG; IL10; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eB cell receptor (BCR) signaling via BTK / G\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026beta;\u0026gamma;}\\)\u003c/span\u003e\u003c/span\u003e BTK activation pathway; Interferon gamma signaling; Interleukin 10 signaling; IL6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHouttuyniae Herba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIFNG; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eInterferon gamma signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForsythiae Fructus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCXCL8; IL10; IL1B; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eChemokine signaling pathway; Interleukin 10 signaling; Interleukin 1 family signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLonicerae Japonicae Flos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIFNG; IL10; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eInterferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArmeniacae Semen Amarum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIFNG; IL10; IL6; JAK2; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eInterferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); JAK\u0026ndash;STAT signaling pathway; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBIR\u0026thinsp;+\u0026thinsp;PSH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelamcandae Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSweet Wormwood Herb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIFNG; IL10; IL6; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eInterferon gamma signaling; Interleukin 10 signaling; IL 6 family signaling (JAK/STAT, MAPK); TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlycyrrhizae Radix et Rhizoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBCHE; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCholinesterase activity / Drug metabolism; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolygoni Cuspidati Rhizoma et Radix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eACE; BCHE; BSG; C5AR1; CCR5; CRP; CXCL8; IFNG; IL10; IL1B; IL6; IMPDH2; MARK2; MTOR; PDE5A; PPIF; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eRenin\u0026ndash;angiotensin system; Cholinesterase activity / Drug metabolism; Basigin interactions (Cell surface interactions at the vascular wall); Complement C5a receptor signaling / GPCR signaling; CC chemokine receptor signaling (chemokine\u0026ndash;GPCR pathway); Acute phase response / Complement activation pathway; Chemokine signaling pathway; Interferon gamma signaling; Interleukin 10 signaling; Interleukin 1 family signaling; IL6 family signaling (JAK/STAT, MAPK); De novo guanine nucleotide synthesis / Purine metabolism; Cell polarity / microtubule regulation \u0026amp; mTOR HIF-1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026alpha;}\\)\u003c/span\u003e\u003c/span\u003e signaling; mTOR signaling pathway; cGMP\u0026ndash;PKG signaling pathway / Nitric oxide\u0026ndash;cGMP pathway; Mitochondrial permeability transition pore (MPTP) \u0026amp; apoptosis signaling; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;IV\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaeoniae Radix Rubra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026radic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIL10; TNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eInterleukin 10 signaling; TNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eFunctional classification of herbs\u003c/h2\u003e \u003cp\u003eFunctional classification of the 36 herbs revealed a consistent distribution across all six formulas (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Supplementary Fig.\u0026nbsp;1). Herbs labeled with overlapping PSH and BIR functions were the most abundant, followed by herbs exclusively classified as PSH or exclusively as BIR. Herbs assigned to the IV category, as well as those spanning all three categories (PSH\u0026ndash;BIR\u0026ndash;IV), were few. This pattern was observed both within individual formulas and across the combined dataset, indicating that therapeutic contributions arise predominantly from host-directed mechanisms (PSH and BIR) rather than pathogen-directed antiviral activity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFunctional distribution of overlapping molecular targets\u003c/h2\u003e \u003cp\u003eA similar trend was observed at the target level (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e; Supplementary Fig.\u0026nbsp;2). The majority of overlapping targets fell within the PSH\u0026ndash;BIR overlap. High-frequency targets included TNF, IL10, IL6, CXCL8, and IFNG, all of which are key regulators of inflammation, immune activation, and tissue repair. In contrast, antiviral-specific targets such as IMPDH2 and VCP were fewer and primarily associated with viral replication or virus-related protein processing. All pathway annotations for overlapping targets are provided in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eMajor signaling pathways targeted by CHM herbs.\u003c/b\u003e Pathway-level summary of the molecular targets regulated by CHM herbs. Each entry includes pathway name, biological function, and its relevance to host response during SARS-CoV-2 infection. Pathway nomenclature is standardized using KEGG, Reactome, and UniProt.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTarget\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePathway\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePathway functions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClass.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACE2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRenin\u0026ndash;angiotensin system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eACE2 converts angiotensin I to II, regulates blood pressure, vascular tone and sodium balance, and is a key regulatory component of the cardiovascular system.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u0026thinsp;+\u0026thinsp;IV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eANGPT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTie-2 signaling / Hemostasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eANGPT2 inhibits the Tie-2 signaling pathway and regulates vascular stability, neogenesis and inflammatory responses.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u0026thinsp;+\u0026thinsp;IV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATP1A1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIon transport by P-type ATPases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDrives ion transport across membranes via Na\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{}}^{\\text{+}}\\)\u003c/span\u003e\u003c/span\u003e/K\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{}}^{\\text{+}}\\)\u003c/span\u003e\u003c/span\u003e-ATPase to maintain membrane potential and cellular function.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBCHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCholinesterase activity / Drug metabolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBCHE hydrolyzes a variety of choline esters and is involved in drug metabolism and neurotransmission regulation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBSG (CD147)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBasigin interactions / Vascular wall cell-surface interactions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCD147 is involved in cell adhesion, vascular immunity and metabolic regulation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eANGPT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePI3K\u0026ndash;Akt signaling \u0026amp; HIF-1 pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eANGPT1 activates the Tie-2/PI3K\u0026ndash;Akt pathway to promote vascular stabilization and anti-inflammatory homeostasis.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIL6 family signaling (JAK/STAT, MAPK)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIL6 activates JAK\u0026ndash;STAT and MAPK signaling via gp130 and is involved in inflammation and immune regulation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTNF signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTNF-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026alpha;}\\)\u003c/span\u003e\u003c/span\u003e activates NF-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\kappa\\)\u003c/span\u003e\u003c/span\u003eB, MAPK and other pathways via TNFR1/2 to mediate inflammatory responses and cell fate decisions.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVEGFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVEGF\u0026ndash;VEGFR2 signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVEGF-A promotes endothelial cell proliferation, migration and angiogenesis via VEGFR2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMMP9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eECM remodeling / Leukocyte migration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMP-9 degrades extracellular matrix and supports leukocyte migration and inflammatory signaling (e.g. TNF, IL-17).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCXCL8 (IL-8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChemokine signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXCL8 mediates inflammatory cell chemotaxis and activation by attracting neutrophils, basophils and T cells via CXCR1/2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDPP4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGLP-1/GIP degradation pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDPP4 is a surface serine peptidase that catalyzes degradation of GLP-1 and GIP, thereby regulating insulin secretion and glucose metabolism.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIFNG (IFN-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026gamma;}\\)\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterferon-gamma signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIFN-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026gamma;}\\)\u003c/span\u003e\u003c/span\u003e binds to its receptor and activates the JAK\u0026ndash;STAT pathway, which induces antiviral responses and enhances antigen presentation and MHC expression.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIV\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIL10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterleukin-10 signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIL10 inhibits expression of Th1 cytokines, MHC II and co-stimulatory molecules on macrophages and dendritic cells, providing immunosuppressive balance.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIL1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026beta;}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterleukin-1 family signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIL-1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026beta;}\\)\u003c/span\u003e\u003c/span\u003e is a major inflammatory mediator, triggering febrile responses and contributing to prostaglandin synthesis, leukocyte migration and T cell activation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIMPDH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDe novo guanine nucleotide synthesis / Purine metabolism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIMPDH2 is a key rate-limiting enzyme in guanosine nucleotide synthesis that oxidizes IMP to XMP, thereby maintaining the cellular GTP pool for DNA/RNA synthesis and cell proliferation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJAK2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJAK\u0026ndash;STAT signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJAK2 is activated and autophosphorylated by ligand-induced receptor engagement and subsequently phosphorylates STAT transcription factors (e.g. downstream of IL6 and IFN-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026gamma;}\\)\u003c/span\u003e\u003c/span\u003e), regulating immunity, hematopoiesis and cell proliferation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMAP2K2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMAPK/ERK (Ras\u0026ndash;Raf\u0026ndash;MEK\u0026ndash;ERK) cascade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMAP2K2 (MEK2) is a classical MAPKK that activates ERK (MAPK1/3) by dual phosphorylation and directs cell proliferation, differentiation, migration and survival signaling.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMARK2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCell polarity / Microtubule regulation \u0026amp; mTOR\u0026ndash;HIF-1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026alpha;}\\)\u003c/span\u003e\u003c/span\u003e signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMARK2 (EMK1) regulates cell polarity and microtubule stabilization and promotes proliferation and metabolic reprogramming through the AMPK/mTOR/HIF-1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026alpha;}\\)\u003c/span\u003e\u003c/span\u003e pathway in certain cell types.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMTOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emTOR signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emTOR is a central regulator of cell growth and metabolism, functioning as the catalytic subunit of mTORC1 and mTORC2. It integrates nutrient, growth factor, energy and stress signals to control protein synthesis, autophagy inhibition, lipid and nucleotide biosynthesis and mitochondrial metabolism.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePDE5A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecGMP\u0026ndash;PKG signaling / Nitric oxide\u0026ndash;cGMP pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePDE5A specifically hydrolyzes cGMP, regulates smooth muscle relaxation and circulatory system function, and belongs to the hemostasis and cGMP signaling module.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePPIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMitochondrial permeability transition pore (mPTP) \u0026amp; apoptosis signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePPIF encodes cyclophilin D, a mitochondrial matrix protein that serves as a key regulator of the mitochondrial permeability transition pore (mPTP). Under oxidative stress, calcium overload or ATP depletion, PPIF facilitates opening of the mPTP, leading to mitochondrial depolarization, ATP loss and release of pro-apoptotic factors such as cytochrome c, thereby triggering apoptotic or necrotic cell death.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eER-associated degradation (ERAD) / Ubiquitin\u0026ndash;proteasome system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVCP (p97) is an AAA\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{}}^{\\text{+}}\\)\u003c/span\u003e\u003c/span\u003e ATPase primarily involved in extracting misfolded or aggregated proteins, directing 26S proteasome degradation, maintaining proteasome homeostasis and contributing to autophagy, ribosome-associated degradation and chromatin regulation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC5AR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComplement C5a receptor signaling / GPCR signaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC5a binding to C5AR1 triggers G\u003csub\u003ei/o\u003c/sub\u003e-protein signaling, induces Ca\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{}}^{\\text{2+}}\\)\u003c/span\u003e\u003c/span\u003e release, MAPK activation and adenylate cyclase inhibition and mediates leukocyte chemotaxis, inflammatory responses and tissue damage as a key node in the complement cascade and innate immunity.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCR5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChemokine receptor signaling (chemokine\u0026ndash;GPCR pathway)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCCR5 binds chemokines such as CCL3/4/5 and participates in inflammatory regulation by mediating intracellular Ca\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{}}^{\\text{2+}}\\)\u003c/span\u003e\u003c/span\u003e elevation, chemotaxis and immune-cell activation via G\u003csub\u003ei\u003c/sub\u003e proteins.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAcute-phase response / Complement activation pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCRP is a typical acute-phase response protein induced mainly by IL6. It binds to phospholipids on the surface of pathogens or apoptotic cells, interacts with C1q to activate the classical complement pathway, enhances phagocytic recognition and clearance and is an important factor in the early humoral immune response.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBTK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBCR signaling via BTK / G\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026beta;\u0026gamma;}\\)\u003c/span\u003e\u003c/span\u003e activation pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBTK is recruited to the membrane and activated by the G-protein \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026beta;\u0026gamma;}\\)\u003c/span\u003e\u003c/span\u003e subunit and PIP3 in the BCR signaling pathway, then autophosphorylates and transduces downstream signals involved in B-cell development, differentiation, immune responses and inflammation, serving as a key regulatory kinase for B-cell function.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBSG (CD147)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBasigin interactions (vascular wall surface interactions)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBasigin regulates extracellular matrix degradation, cell adhesion, migration and metabolic functions by promoting MMP synthesis (e.g. MMP-1/MMP-2) and interacting with caveolin-1, integrins and cyclophilin A, and is involved in angiogenesis, tissue growth and immunomodulation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH\u0026thinsp;+\u0026thinsp;BIR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eNetwork connectivity of herb\u0026ndash;target\u0026ndash;pathway interactions\u003c/h2\u003e \u003cp\u003eTo further assess network structure, an integrated herb\u0026ndash;target\u0026ndash;pathway\u0026ndash;function network was constructed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). High-frequency targets such as TNF, IL10, IL6, CXCL8, and IFNG exhibited strong connectivity, linking to multiple herbs and participating in numerous signaling pathways. Their hub-like behavior suggests that these targets serve as central nodes through which multidimensional therapeutic effects may be exerted. In contrast, low-frequency antiviral targets such as VCP and IMPDH2 showed limited connectivity, consistent with their more specialized roles. The overall target frequency distribution (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) also reflected these trends, with major hubs concentrated within the PSH\u0026ndash;BIR overlap and antiviral nodes forming only a minor fraction.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFormula overlap and composition analysis\u003c/h2\u003e \u003cp\u003eA Venn diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) was generated to examine compositional overlap among the six formulas. The results revealed both shared and unique herbal components: several herbs were commonly used across formulas, such as \u003cem\u003eGlycyrrhizae Radix et Rhizoma\u003c/em\u003e, \u003cem\u003eArmeniacae Semen Amarum\u003c/em\u003e, and \u003cem\u003eEphedrae Herba\u003c/em\u003e, whereas others appeared only in one or two formulas. These findings suggest purposeful differentiation among formulas based on disease stage or clinical presentation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSimilarity analysis and functional convergence\u003c/h2\u003e \u003cp\u003eHerbal similarity was quantified using the Jaccard similarity matrix (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Overall similarity remained low, with the highest similarity observed between LHQW and JHQG (Jaccard index\u0026thinsp;=\u0026thinsp;0.385). In contrast, analysis of functional composition revealed that PSH/BIR ratios were highly consistent across formulas, ranging from 0.75 to 1.13 (mean \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026sim;}\\)\u003c/span\u003e\u003c/span\u003e0.90 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026plusmn;}\\)\u003c/span\u003e\u003c/span\u003e 0.13) (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). This convergence indicates that despite substantial differences in herbal composition, the formulas maintain stable and balanced therapeutic profiles centered on PSH and BIR. These findings suggest that as long as the functional balance between promoting self-healing power and balancing immune response is preserved, therapeutic efficacy can be achieved even when herbal compositions differ.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eRatios of PSH/BIR in six CHM formulas.\u003c/b\u003e Counts of herbs assigned to PSH and BIR categories within each formula. PSH/BIR ratios quantify functional balance across formulas and reveal consistent predominance of host-directed mechanisms.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormula (abbr.)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal herbs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSH count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBIR count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePSH/BIR ratio\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLianhua Qingwen (LHQW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQingfei Paidu (QFPD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJinhua Qinggan (JHQG)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShufeng Jiedu (SFJD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXuanfei Baidu (XFBD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuashi Baidu (HSBD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides the first systematic attempt to classify the functions of CHM herbs used in infectious diseases according to three mechanistic categories\u0026mdash; PSH, BIR, IV\u0026mdash;derived from the host\u0026ndash;pathogen interaction framework (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). By integrating these functional definitions with standardized pathway annotation, we established a data-driven and mechanistically interpretable approach for linking herbal effects to molecular targets across six nationally recommended COVID-19 formulas. From the 46 herbs included in these formulas, 36 exhibited overlap with curated COVID-19\u0026ndash;related therapeutic targets from TTD (Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), forming the basis for functional classification and network analysis. Most herbs and targets fell within PSH, BIR, or their overlap, whereas IV-labeled herbs were infrequent and lacked robust supporting clinical evidence (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne major reason for the predominance of the PSH\u0026thinsp;+\u0026thinsp;BIR category is that anti-inflammatory actions are shared across both PSH and BIR, although it serves distinct purposes\u0026mdash;resolution and tissue repair in PSH, and immune modulation in BIR. Similar to strategies observed in cancer immune evasion (Tang et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), pathogens often manipulate host immunity, necessitating a balanced therapeutic approach that CHM effectively provides.This overlap likely contributes to the large PSH\u0026ndash;BIR intersection. Nevertheless, the overall functional distribution highlights a central therapeutic principle of CHM: restoring host homeostasis takes precedence over directly attacking pathogens. Under this paradigm, pathogen clearance emerges as a downstream consequence of enhanced repair capacity (PSH) and appropriately balanced immunity (BIR), rather than a primary therapeutic objective.\u003c/p\u003e \u003cp\u003eNetwork analysis further supports this host-centered mechanism. High-frequency targets\u0026mdash;including TNF, IL10, IL6, CXCL8, and IFNG\u0026mdash;exhibited strong connectivity and involvement in multiple signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Their hub-like properties indicate that they play central roles in coordinating inflammation, immune responses, and tissue repair. In contrast, low-frequency antiviral targets such as VCP and IMPDH2 showed limited connectivity, consistent with their narrow mechanistic roles. This combination of broad-spectrum hubs and specialized antiviral nodes suggests potential for strategic tailoring of interventions to match disease stages or pathogen characteristics.\u003c/p\u003e \u003cp\u003eNotably, classification of certain herbs into the IV group relied mainly on in vitro or preclinical findings. First, many in vitro antiviral assays employ concentrations exceeding physiologically achievable exposure; for example, paeoniflorin demonstrates intestinal absorption far below commonly used in vitro assay doses (Srinivas, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Second, the antiviral activity of isolated constituents cannot be directly extrapolated to multi-component formulas; in LHQW, antiviral components constitute only approximately 9% of the formula, yet the full formula produces stronger viral clearance than isolated compounds (L.-C. Li et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Overemphasizing direct antiviral constituents risks fragmenting the holistic formulation logic of CHM, which is fundamentally designed around PSH and BIR rather than IV. To address this issue, we systematically re-evaluated four herbs labeled as antiviral by examining assay type, target type, potency context (IC\u003csub\u003e50\u003c/sub\u003e/EC\u003csub\u003e50\u003c/sub\u003e), and exposure plausibility. According to our operational criteria, IV-direct requires clinically attainable concentrations targeting viral components, and IV-indirect requires effects on host-dependent viral processes independent of PSH or BIR. None of the evaluated herbs met these criteria (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), indicating that their observed antiviral effects are more plausibly mediated through PSH and/or BIR pathways.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eEvaluation of herbs initially claimed to possess antiviral activity against SARS-CoV-2.\u003c/b\u003e Reassessment of commonly cited \u0026ldquo;antiviral\u0026rdquo; herbs based on current peer-reviewed evidence, graded using the evidence scale and adjudicated under the IV classification rules. Findings include evaluation of antiviral mechanism plausibility, exposure feasibility, and classification into PSH/BIR or IV.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHerb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLatest antiviral findings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEvidence grade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjudication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKey sources\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRhei Radix et Rhizoma (\u003cem\u003eRheum palmatum\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvidence is predominantly in silico (molecular docking/network pharmacology), suggesting anthraquinones (rhein, emodin, chrysophanol) may bind RdRp/ACE2. No wet-lab infection studies (cell or animal) or clinical trials demonstrate direct antiviral activity. SARS-CoV (2003) S\u0026ndash;ACE2 blocking data are not transferable to SARS-CoV-2. PK data show oral C\u003csub\u003emax\u003c/sub\u003e far below putative effective concentrations.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eD\u003c/b\u003e (docking/network only; no wet-lab confirmation; exposure implausible)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot supported for IV-direct or IV-indirect. Findings better align with PSH/BIR (immune regulation and host protection).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(Po-Wei, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; J. Qi, Dong, Wang, Zhang, et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zhang ChunLing et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePinelliae Praeparatum Rhizoma (processed \u003cem\u003ePinellia ternata\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo peer-reviewed wet-lab antiviral studies against SARS-CoV-2. Literature focuses on immune modulation, anti-inflammatory activity, and respiratory support (e.g., asthma models). Antiviral claims originate solely from docking/network analyses; no validated viral targets, EC\u003csub\u003e50\u003c/sub\u003e/IC\u003csub\u003e50\u003c/sub\u003e, or PK data.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eD\u003c/b\u003e (in silico only; no antiviral wet-lab data; exposure unknown)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot supported for IV-direct or IV-indirect. Functional profile aligns with BIR/PSH rather than pathogen-directed inhibition.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(S. Lin et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Peng et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tao et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAstragali Radix (\u003cem\u003eAstragalus membranaceus\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo wet-lab evidence demonstrates direct anti\u0026ndash;SARS-CoV-2 activity. Wet-lab studies support host-side effects: \u0026mdash; immune balancing (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026darr;}\\)\u003c/span\u003e\u003c/span\u003e IL6/TNF-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026alpha;}\\)\u003c/span\u003e\u003c/span\u003e; Th1/Th2 modulation) \u0026mdash; cytoprotection/antioxidant responses (Nrf2 activation, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026darr;}\\)\u003c/span\u003e\u003c/span\u003e ROS). AS-IV has poor oral bioavailability; polysaccharides show limited systemic absorption.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e (supports PSH/BIR only; no antiviral mechanism at plausible exposure)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot supported for IV-direct or IV-indirect. Mechanisms align with BIR\u0026thinsp;+\u0026thinsp;PSH (immune regulation\u0026thinsp;+\u0026thinsp;stress-protection).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(Adesso et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e; Minsook, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Shen et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolygoni Cuspidati Rhizoma et Radix (\u003cem\u003ePolygonum cuspidatum\u003c/em\u003e; resveratrol/polydatin/emodin)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExtracts show pseudovirus entry inhibition (WT/Omicron) and 3CLpro suppression (IC\u003csub\u003e50\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{\u0026asymp;}\\)\u003c/span\u003e\u003c/span\u003e 0.015\u0026ndash;0.04 mg/mL). However: \u0026mdash; no SARS-CoV-2 replication assays for major constituents \u0026mdash; extremely low oral bioavailability of resveratrol \u0026mdash; extract-level IC\u003csub\u003e50\u003c/sub\u003e values not achievable in vivo Overall evidence is preclinical and exposure-implausible.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e (enzyme/pseudovirus only; no systemic plausibility)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNot supported for IV-direct. Findings classify best as PSH/BIR (host-side support). IV-indirect may have topical relevance (upper airway), but not systemic.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(C. Lin et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015b\u003c/span\u003e; S. Lin, Wang, Tang, Lee, et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Shiuan-Pey, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDespite substantial heterogeneity in herbal composition across the six formulas (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e), their PSH/BIR ratios remained stable (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). This convergence demonstrates that formulas can differ widely in composition yet maintain comparable functional profiles. Such consistency aligns with CHM practice in which herbs with similar therapeutic properties may be substituted without compromising overall efficacy, provided the overarching balance between self-healing and immune regulation is preserved (Lyu et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; X. Zhang et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThree herbs\u0026mdash;\u003cem\u003eGlycyrrhizae Radix et Rhizoma\u003c/em\u003e, \u003cem\u003eArmeniacae Semen Amarum\u003c/em\u003e, and \u003cem\u003eEphedrae Herba\u003c/em\u003e\u0026mdash;appeared in more than half of the formulas, underscoring their central therapeutic roles. Licorice exhibits broad anti-inflammatory and harmonizing effects via NF-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\kappa\\)\u003c/span\u003e\u003c/span\u003eB inhibition; bitter apricot kernel contributes bronchodilatory and anti-tussive actions; and ephedra provides bronchodilation and facilitates surface-defense responses (Gu et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; You et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Collectively, these herbs enhance respiratory function, reduce inflammation, and promote recovery\u0026mdash;consistent with their PSH/BIR classification.\u003c/p\u003e \u003cp\u003eThis study offers three conceptual innovations. First, it introduces the PSH/BIR/IV framework as a mechanistic classification for CHM herbs used in infectious diseases. Second, it classifies anti-inflammatory actions to both PSH and BIR but serving distinct biological functions. Third, it demonstrates that the reportedly claimed \u0026ldquo;antiviral\u0026rdquo; actions of certain herbs likely arise from PSH- and/or BIR-mediated mechanisms, reinforcing CHM as a fundamentally holistic, host-targeted therapeutic system.\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. Functional classification relies on currently available molecular target databases and may not fully capture the multidimensional pharmacodynamics of complex herbal mixtures. Although pathway annotations were standardized using KEGG, Reactome, and UniProt, final functional assignments required expert interpretation and thus involved some subjectivity. Furthermore, validation of the PSH\u0026ndash;BIR model requires real-world clinical and mechanistic evidence. Future research should aim to elucidate biological processes underlying self-healing and its interaction with immune pathways. Integration of electronic health records, multi-omics datasets, and AI-based modeling (e.g., label-free phenotype classification (Hourani et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)) may enable quantification of individual-level self-healing power and immune balance, helping to establish a standardized framework for diagnosis and treatment.\u003c/p\u003e \u003cp\u003eIn summary, this study established a mechanistic, data-driven framework for classifying the functions of CHM herbs used in infectious diseases into three strategic categories: PSH, BIR, and IV. We found that CHM treats infecious diseases mainly through PSH- and/or BIR-mediated host-directed mechanisms rather than direct viral inhibition. The stability of PSH/BIR ratios across formulas\u0026mdash;despite substantial heterogeneity in herbal composition\u0026mdash;highlights a core therapeutic principle of CHM: restoring host homeostasis takes precedence over pathogen-directed strategies.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eCompeting Interest:\u003c/strong\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis study was supported by the Fundamental Research Fund for Central Universities (to J.S.), National Natural Science Foundation of China grant 31871363 (L.L.), National Natural Science Foundation of China grant 31900575 (L.L.), LiaoNing Revitalization Talents Program XLYC1907052 (L.L.), the 111 Project B16009 (L.L.), Key Laboratory of Bioresource Research and Development of Liaoning Province 2022JH13/10200026 (L.L.).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJS conceptualized ideas, designed and managed the projects, wrote and edited the manuscript; FN developed methodology, curated data, performed analysis, wrote and edited the manuscript. JL supervised the project, reviewed and edited the manuscript; YZ, LL, and KC reviewed and edited the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data generated and analyzed during this study, including computer scripts, are either reported in the manuscript or available from the corresponding authors upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdesso S, Russo R, Quaroni A, Autore G, Marzocco S (2018a) Astragalus membranaceus Extract Attenuates Inflammation and Oxidative Stress in Intestinal Epithelial Cells via NF-κB Activation and Nrf2 Response. 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Biosci Trends 15(5):283\u0026ndash;298. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5582/bst.2021.01318\u003c/span\u003e\u003cspan address=\"10.5582/bst.2021.01318\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"in-silico-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"insp","sideBox":"Learn more about [In Silico Pharmacology](https://link.springer.com/journal/40203)","snPcode":"40203","submissionUrl":"https://submission.nature.com/new-submission/40203/3","title":"In Silico Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Chinese herbal medicine, Self-healing power, Immunomodulation, Antiviral activity, COVID-19, Host-directed therapy","lastPublishedDoi":"10.21203/rs.3.rs-8693251/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8693251/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUsing a host\u0026ndash;pathogen interaction framework, infectious disease therapy can be viewed as three complementary strategies: inhibiting pathogens, regulating immunity, and enhancing the host\u0026rsquo;s intrinsic repair capacity (\u0026ldquo;self-healing power\u0026rdquo;). We hypothesized that Chinese herbal medicine (CHM) treats COVID-19 predominantly through host-directed mechanisms\u0026mdash;promoting self-healing (PSH) and balancing immune response (BIR)\u0026mdash;rather than directly inhibiting virus (IV). Six CHM formulas officially recommended for COVID-19 in China (46 unique herbs) were analyzed. The herb-associated molecular targets were collected from CHMSP, HERB, and TTD, cross-referenced with 118 curated COVID-19 therapeutic targets, and functionally classified into PSH, BIR, or IV using standardized pathway annotations (KEGG, Reactome) and network analysis. Thirty-six herbs (78.3%) shared targets with COVID-19. Across all formulas, PSH and BIR mechanisms were consistently predominant, whereas putative antiviral targets (e.g., IMPDH2, VCP) were rare and showed limited network connectivity. Major network hubs included TNF, IL6, IL10, and CXCL8, highlighting convergent regulation of inflammation and tissue repair. Although the highest compositional overlap among the formulas is no more than 40%, their functional output was highly conserved, with a consistent PSH/BIR ratio (mean 0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13). Pharmacokinetic and mechanistic reassessment of the commonly labeled \u0026ldquo;antiviral\u0026rdquo; herbs suggested that reported benefits are more plausibly mediated through host-dependent PSH and/or BIR actions than direct viral inhibition at physiological concentrations. These findings support a holistic, host-centered mechanism for CHM in control of COVID-19 and provide a quantitative framework for evaluating host-directed therapeutics in infectious diseases.\u003c/p\u003e","manuscriptTitle":"Chinese herbal medicine treats COVID-19 by promoting self-healing power and balancing immune response: A functional classification analysis integrating molecular targets and pathways","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-10 09:46:24","doi":"10.21203/rs.3.rs-8693251/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-15T23:53:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"145783625689813490478002155049920650237","date":"2026-05-13T01:34:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"251901508833740494974556745084260883972","date":"2026-05-09T23:47:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T18:53:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338915844408535099922733395229942543044","date":"2026-04-29T13:15:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-08T22:42:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-27T04:57:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-27T04:56:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"In Silico Pharmacology","date":"2026-01-25T14:45:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"in-silico-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"insp","sideBox":"Learn more about [In Silico Pharmacology](https://link.springer.com/journal/40203)","snPcode":"40203","submissionUrl":"https://submission.nature.com/new-submission/40203/3","title":"In Silico Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"effb3e38-fd73-4e11-9269-e34139eda13c","owner":[],"postedDate":"February 10th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-15T23:53:33+00:00","index":59,"fulltext":""},{"type":"reviewerAgreed","content":"145783625689813490478002155049920650237","date":"2026-05-13T01:34:43+00:00","index":57,"fulltext":""},{"type":"reviewerAgreed","content":"251901508833740494974556745084260883972","date":"2026-05-09T23:47:16+00:00","index":53,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T18:53:36+00:00","index":42,"fulltext":""},{"type":"reviewerAgreed","content":"338915844408535099922733395229942543044","date":"2026-04-29T13:15:55+00:00","index":41,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T22:53:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-10 09:46:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8693251","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8693251","identity":"rs-8693251","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}