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Article

Exploring CCND1 as a Key Target of Acorus calamus Against RSV Infection: Network Pharmacology, Molecular Docking, and Bioinformatics Analysis

1
Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
2
Clinical Medical Research Center for Plateau Gastroenterological Disease of Xizang Autonomous Region, School of Medicine, Xizang Minzu University, Xianyang 712082, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Curr. Issues Mol. Biol. 2025, 47(9), 695; https://doi.org/10.3390/cimb47090695
Submission received: 11 July 2025 / Revised: 9 August 2025 / Accepted: 24 August 2025 / Published: 27 August 2025
(This article belongs to the Section Molecular Pharmacology)

Abstract

Acorus calamus, a traditional Tibetan medicine with potential antiviral activity but undefined mechanisms, was studied for its anti-respiratory syncytial virus (RSV) mechanisms using network pharmacology and molecular docking, given RSV’s substantial disease burden and lack of specific therapies. The primary active compounds were identified and analyzed through a literature search, the PubChem database, and the SwissADME. Relevant targets were sifted through the SwissTargetPrediction platform, OMIM, and GeneCards databases. Common targets underwent enrichment analysis using Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Molecular docking and GEO datasets were used for further analysis. Among the screened data, 268 targets were associated with Acorus calamus compounds and 1633 with RSV. KEGG analysis of the shared targets revealed potential therapeutic roles via the PI3K–Akt and JAK–STAT signaling pathways. Molecular docking results demonstrated that CCND1, EGFR, and SRC exhibited relatively lower binding energies with compounds in comparison to other proteins, suggesting better interactions, and GEO-derived RSV datasets further validated CCND1’s significance. This study demonstrates Acorus calamus’s anti-RSV activity and its potential mechanism, providing a theoretical foundation for the effective active ingredients of Acorus calamus targeting CCND1 as a strategy to combat RSV infection.

1. Introduction

Respiratory syncytial virus (RSV) is the preeminent etiological agent of lower respiratory tract infections (LRTIs), particularly in the pediatric population [1]. It is the leading cause of hospital admissions for respiratory diseases among infants and children worldwide [2]. The global burden of disease due to RSV is significant, with substantial morbidity and mortality in infant and child populations. An annual total of over 3.6 million children under the age of five are hospitalized for RSV infections, and approximately 100,000 children under the age of five die from RSV infections [3]. Furthermore, findings from China’s acute respiratory infection surveillance further reveal that among children under 5 years old, the RSV positivity rate is as high as 25.7%, surpassing that of other viral pathogens and ranking first among all viral infections [4].
Despite its widespread prevalence and substantial disease burden, RSV is recognized as a preventable infection. In 2023, two new RSV vaccines for infants and children received approval [5,6], offering renewed optimism in the fight against RSV. However, evidence suggests that early onset and severe RSV infections can impinge on normal lung development, potentially culminating in long-term respiratory disorders [7,8]. Since vaccination does not confer complete protection against RSV infection and there remains a dearth of specific antiviral therapies for RSV, it is of utmost importance to identify targeted treatments. Consequently, there is an imperative need to develop effective treatment strategies for RSV, with a view to reducing the disease burden and the long-term effects of RSV infection.
Natural products represent a rich reservoir for drug development, with Tibetan medicine being an integral component [9]. Over time, Tibetan medical practitioners have established a comprehensive theoretical framework based on their extensive practical experiences [10]. Acorus calamus (ZangChangPu, ZCP) is a commonly used herb in Tibetan medicine and holds a significant place within this traditional medical system. Previous research has demonstrated that Acorus calamus can inhibit acute asthmatic reactions and is effective in treating chronic bronchitis [11]. Moreover, the traditional Tibetan medicine formula, Jiuwei Heiyao Fangwen powder, has exhibited remarkable potential in the prevention and management of Severe Acute Respiratory Syndrome (SARS), COVID-19, and Influenza Virus A (H1N1). Notably, Acorus calamus is one of the key ingredients in this formula [12]. Based on these findings, it can be hypothesized that Acorus calamus may possess value in the context of antiviral infections [13]. Nevertheless, current investigations into the antiviral properties of Acorus calamus remain limited, and the underlying mechanisms of its action against viruses are yet to be elucidated. Further research is warranted to explore the potential of Acorus calamus as an antiviral agent, which could contribute to the development of novel antiviral therapies.
In recent years, the advent and progression of network pharmacology have enabled in-depth exploration of the intricate relationships between herbal components and diseases. By comprehensively analyzing drug components, their corresponding disease-related targets, and elucidating the implicated biological processes and pathways, valuable insights into the mechanisms of drug therapy can be gleaned [14]. Against this backdrop, the present study adopted a network pharmacology-based approach to dissect the pharmacological effect network of Acorus calamus in the treatment of RSV infection. Concurrently, in an effort to explore the underlying mechanism of Acorus calamus in treating RSV at the molecular and pathway levels, this study integrated enrichment analysis, molecular docking, and dataset validation techniques. The overarching aim was to provide robust evidence for the utility of Acorus calamus in RSV treatment and to pioneer a novel approach for managing RSV infections.

2. Materials and Methods

2.1. Screening for Active Compounds and Their Corresponding Targets in Acorus calamus

The constituent compounds were obtained from a literature search for common constituents of Acorus calamus and checked in the PubChem database (https://pubchem.ncbi.nlm.nih.gov) [accessed on 15 March 2025] to confirm the compound structures and collect the common names and SMILES. The active compounds were then subjected to screening in SwissADME (http://www.swissADME.ch) [accessed on 15 March 2025] according to the criteria that (1) indicated high GI absorption and (2) received a score of 2 or greater in the druglikeness entries. The compounds meeting these criteria were identified as active compounds. The SwissTargetPrediction platform (http://swisstargetprediction.ch) [accessed on 15 March 2025] was then utilized to predict potential targets based on structural similarity between known ligands and compounds to be tested, with “Homo sapiens” selected and the retention parameter set to probability > 0.1.

2.2. Gathering of RSV-Related Targets

Two databases, Online Mendelian Inheritance in Man (OMIM: https://omim.org/) [accessed on 17 March 2025] and The Human Gene Database (GeneCards: https://www.genecards.org/) [accessed on 17 March 2025], were queried to obtain potential targets associated with RSV. We finally integrated all the targets and removed duplicates to obtain the full range of RSV-related targets.

2.3. Shared Targets Were Determined from the Intersection of Active Compound Targets and RSV-Associated Targets

Common targets shared between RSV-related and predicted Acorus calamus targets were identified and visualized in a Venn diagram using Venny 2.1.0 (https://bioinfogp.cnb.csic.es/tools/venny/index.html) [accessed on 20 March 2025]. The common targets were imported into Cytoscape 3.10.2 to construct a herb–compound–target network diagram.

2.4. Constructing a Network to Visualize PPI

The common targets were analyzed for protein–protein interaction (PPI) analysis using the STRING database (http://string-db.org) [accessed on 20 March 2025], with parameters set to Homo sapiens and a confidence score threshold of 0.4 to ensure data reliability. The analysis results were subsequently imported into Cytoscape 3.10.2 for visualization, and the core targets in the network were selected using the CytoHubba plugin. The Maximum Clique Centrality (MCC) algorithm was selected for network topology analysis, and the top 15 genes were identified as the core targets for subsequent analysis.

2.5. DO, GO, and KEGG Enrichment Analyses

Using R software (version 4.3.3), the shared targets underwent enrichment analyses for Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG), applying p-value and q-value cutoffs of 0.05. The results of KEGG enrichment analysis were imported into Cytoscape 3.10.2, and the compound–target–pathway network diagram was drawn. Core targets were identified based on three essential topological parameters: Degree, Closeness Centrality (CC), and Betweenness Centrality (BC).

2.6. Molecular Docking Verification

Ligand structures were sourced from PubChem, while the 3D crystal structures of the targets were acquired from the Universal Protein Resource Database (UniProt: https://www.uniprot.org/) [accessed on 21 March 2025]. Both datasets underwent preliminary processing and were imported into AutoDockTools 1.5.6 for molecular docking, with interaction visualizations generated using PyMOL. Intermolecular interactions, including hydrogen bonding and hydrophobic interactions, were further analyzed using LigPlot. The molecular docking binding energy results were then visualized using a heat map drawn with R 4.3.3.

2.7. RSV Datasets Acquisition and Target Validation

Differential expression analysis of RSV datasets GSE105450 and GSE77087 from Gene Expression Omnibus (GEO: https://www.ncbi.nlm.nih.gov/geo/) [accessed on 23 March 2025] was conducted in R 4.3.3 (|logFC| > 1, p < 0.05), and results were illustrated via volcano plots and heatmaps. The Venn diagram was employed to identify the common targets among the core targets and the two RSV datasets, GSE105450 and GSE77087. The expression of the common targets was presented as box plots.

3. Results

3.1. The Candidate Targets of Acorus calamus and Their Corresponding Active Compounds

Numbered lists can be added as follows: A total of 26 active compounds were identified in Acorus calamus gathered from the literature search and PubChem database (Table 1) [15,16,17,18,19,20]. We initially retrieved a total of 118 components from the literature. The PubChem database determined the structures and PubChem CIDs of a total of 78 of these components. Fifty-six of the components passed the SwissADME criteria for drug-likeness. Through a search in the SwissTargetPrediction platform, 451 potential targets associated with 26 compounds of Acorus calamus were obtained, and with duplicates removed, this led to the identification of 268 targets (Supplementary Table S1).

3.2. RSV-Related Targets

By merging data from GeneCards and OMIM and removing overlapping entries, 1633 unique targets related to RSV were identified. A total of 1633 RSV-related targets were identified as disease targets in a Venn diagram after the merger of GeneCards and OMIM (Figure 1).

3.3. Construction of Herb–Compound–Target Network

Venn diagram analysis (Figure 2) revealed 87 common targets shared by the active compounds of Acorus calamus and RSV-associated disease targets. The details were shown in Table 2. The identified common targets may serve as potential mediators of Acorus calamus’s therapeutic effects against RSV. A network was constructed using Cytoscape 3.10.2, incorporating 26 active compounds and 87 associated targets (Figure 3). In this network, edges represent the interactions between compounds and their respective targets, while node size and color intensity indicate the relative strength or significance of these interactions. One component in the figure may correspond to one or more targets, indicating that the pharmaceutical composition has multi-component and multi-target properties for the treatment of disease. The top 10 compounds, sorted by degree within the herb–compound–target network, were presented in Table 3.

3.4. Analysis of Herb–Compound–Target Network and Construction of PPI Network for Common Targets

In order to investigate the interaction underlying Acorus calamus with RSV, a PPI network was constructed using STRING and Cytoscape 3.10.2, with 87 common targets forming the foundation of this network (Figure 4 and Figure 5). Color gradients of the nodes, ranging from light to dark, indicate ascending node degree values. Subsequent analysis of the network identified the top 15 genes as the core targets for further investigation (Figure 6, Table 4). This analysis employed the CytoHubba plugin and the MCC algorithm for network topology analysis.

3.5. DO, GO, and KEGG Enrichment Analysis

Enrichment analyses (DO, GO, and KEGG) for the 87 drug–disease-related targets were conducted in R 4.3.3, employing p-value and q-value thresholds below 0.05 for significance. A total of 696 disease terms were enriched through DO analysis. The 30 categories with the highest levels of enrichment were displayed in bubble charts. Notably, high-ranking categories such as bronchial disease may be closely related to RSV development (Figure 7). Furthermore, a GO analysis was performed, resulting in the identification of 1721 GO terms, with the allocation of 1564 to Biological Processes (BP), 43 to Cellular Components (CC), and 114 to Molecular Functions (MF) (Figure 8). The most significantly enriched BP terms were mainly associated with chemotactic response, leukocyte migration, modulation of apoptotic signaling pathways, and oxidative stress response. The CC terms predominantly focus on the external side of the plasma membrane, the membrane raft, and the membrane microdomain. Additionally, a substantial proportion of the highly enriched MF terms pertain to DNA-binding, RNA polymerase II-specific DNA-binding, and transcription coregulator binding. KEGG enrichment analysis revealed 136 distinct signaling pathways. Among the top 30 pathways, the highest-ranking, including the C-type lectin receptor, PI3K-Akt, and JAK-STAT signaling pathways, showed strong associations with RSV onset and progression (Figure 9).

3.6. Construction of Compound–Target–Pathway Network and Identification of Core Targets for RSV

A compound–target–pathway network was established using Cytoscape 3.10.2, integrating all KEGG pathways along with their related targets and active compounds (Figure 10). The following three essential topological parameters were utilized: Degree, CC, and BC, to identify core targets. As shown in Table 5, the top 15 targets were ranked according to their degree values in the network. A Venn diagram analysis revealed six shared core targets, corresponding to the intersection between the top 15 targets from the PPI network and those previously identified (Figure 11).

3.7. Validation and Graphical Representation of Molecular Docking Outcomes

To validate the results of the aforementioned analysis, AutoDockTools 1.5.7 was employed to facilitate the molecular docking validation process [21]. This work sought to examine the binding relationships between the selected compound ligands and key target proteins. The molecular docking receptors were retrieved from the UniProt database, with gene names and related PDB IDs summarized in Table 6. The binding energy values, presented as a heatmap (Figure 12), revealed good binding between the target proteins and compounds when the energy was significantly lower than −4.5 kcal/mol. It is evident that CCND1, EGFR, and SRC exhibited lower docking scores with compounds in comparison to other proteins, suggesting that these proteins may serve as prospective binding targets of Acorus calamus in the management of RSV. Visualization of the interactions and binding modes of compounds and targets with high free binding energy scores was facilitated by PyMOL and LigPlot (Figure 13). The interactions included hydrogen bonds and hydrophobic interactions, maintaining a stable conformation. The results show that 2-Acetoxyacorenone-SRC interacts similarly with 2-Acetoxyacorenone-STAT3. This may be due to the presence of a region of structural homology between SRC and STAT3, to which 2-Acetoxyacorenone binds. More notably, the interaction of the molecule with RELA is particularly complex. This may be related to the functional diversity of RELA, an important member of the NF-κB family, which is involved in numerous physiological functions and has more corresponding binding sites.

3.8. Validation of Core Targets by RSV Datasets from GEO

The two RSV datasets, GSE105450 and GSE77087, from the GEO database were subjected to differential analysis to identify potential targets. Volcano plots (Figure 14a,c) illustrate the Differentially Expressed Genes (DEGs), with red dots signifying upregulated genes and blue dots representing downregulated ones. A heatmap was generated to illustrate the distribution of DEGs, with the top 50 further grouped for in-depth analysis (Figure 14b,d). By intersecting the core targets with the two datasets, CCND1 was identified as a common core target (Figure 14e). The CCND1 expressions of the two RSV datasets were visualized separately using box plots (Figure 15). In addition, we assessed the mRNA expression levels of CCND1 in different cells and tissues using data from the Biological Gene Expression Profiling and Annotation-Based Tissue-Oriented Portal database (BioGPS: https://biogps.org) (Figure 16). Consistent with our findings, the results showed that CCND1 expression was higher in lung tissue.

4. Discussion

In this study, the existing literature was thoroughly reviewed with the objective of identifying 26 active compounds and 268 associated targets of Acorus calamus. In addition, 1633 RSV-related targets were retrieved from the GeneCards and OMIM databases. Eventually, 87 common targets were identified and displayed in a network diagram. During the subsequent DO analysis, a strong association between bronchial disease and RSV infection was revealed, which is consistent with current knowledge. It was discovered that upon RSV infection, viral particles are released and transferred to the fine bronchial tubes of the respiratory tract or alveoli, causing bronchial diseases such as capillary bronchitis [22]. Research has demonstrated that RSV infection can cause abnormalities in human immune regulation and airway remodeling with persistent inflammation. These effects subsequently increase the risk of the development of asthma [23] and induce acute exacerbation of Chronic Obstructive Pulmonary Disease (COPD) [24].
In order to gain further insight into the molecular mechanism of interaction of Acorus calamus with RSV infection, a follow-up analysis was performed. GO annotation revealed the biological processes implicated in RSV infection, encompassing chemotaxis, leukocyte migration, regulation of apoptotic signaling pathways [25], and response to oxidative stress [26]. KEGG analysis indicated that the shared targets were predominantly enriched in pathways strongly associated with RSV, such as Leukocyte transendothelial migration [27], C-type lectin receptor signaling pathway [28], and Lipid and atherosclerosis [29]. Notably, within the KEGG analysis results, the majority of targets were centrally concentrated in cellular signaling and regulatory pathways, specifically the PI3K-Akt signaling pathway [30] and the JAK-STAT signaling pathway [31]. The PI3K-Akt signaling pathway has been demonstrated to promote the replication of RSV through the inhibition or delay of apoptosis in airway epithelial cells. Following the infection of respiratory epithelial cells by RSV, the host activates the JAK-STAT signaling pathway through the secretion of type I interferon (IFN) to inhibit viral replication and spread. Nevertheless, the concept of a function for the PI3K-Akt signaling pathway in lung injury remains a subject of debate. It has been shown by some studies that lung inflammation can be alleviated by activation of the PI3K-Akt signaling pathway [32].
Key proteins and compounds were validated through molecular docking to elucidate the therapeutic mechanism of Acorus calamus against RSV. Specifically, six RSV-associated core proteins (CCND1, EGFR, RELA, SRC, STAT3, and TNF) were docked with four bioactive molecules (2-Acetoxyacorenone, calamusin D, acoric acid, and isoeugenol) to assess their binding interactions. It becomes evident that CCND1, EGFR, and SRC have lower binding energies and show better binding affinity than other target proteins. Notably, the binding energy of EGFR to all four active molecular compounds was less than −4.5 kcal/mol.
Research has demonstrated that RSV infection significantly downregulates CCND1 expression. In contrast, L-sulforaphane (LSF) can alleviate RSV infection in human lung epithelial cells by upregulating CCND1 levels [33]. RSV, in its early infection stage, activates EGFR-driven survival signaling and directs the mitochondrial translocation of EGFR, thereby prolonging its functional state. The EGFR-mediated signaling cascade plays a critical role in the initial phase of RSV infection [34]. Additionally, Xu’s study [35] revealed that the RELA∙OGG1 complex influences the N-glycosylation modification of RSV glycoproteins. This modification is essential for the RSV-induced adaptive epithelial response and extracellular matrix remodeling, as well as being a key factor contributing to long-term lung developmental abnormalities following early-life RSV infection. Moreover, DTX3L can bind to SRC to mediate TBK1 phosphorylation, which enhances the type I interferon-mediated antiviral response against RSV [36]. Zhao’s research [37] concluded that STAT3-mediated anti-apoptotic signaling protects against severe RSV infection in infants and mitigates both infection severity and inflammation in the lungs of affected children. Other studies have provided evidence that elevated nasal TNF levels are positively associated with the severity of RSV infection, suggesting that TNF upregulation may induce an exaggerated inflammatory response in the airways, thereby worsening RSV infection [38]. Notably, SRC serves as an upstream regulator of EGFR activation and phosphorylation, processes that are integral to RSV infection dynamics [39].
Furthermore, analysis showed that both RSV datasets from the GEO repository shared CCND1, reinforcing its critical involvement in RSV pathogenesis. CCND1 serves as a critical regulator of the G1/S cell cycle transition, which is arrested following RSV infection [40,41]. Additionally, miR-34a has been shown to induce G1 phase arrest by down-regulating CCND1 [42]. Furthermore, RSV G protein-mediated miRNA let-7f can inhibit CCND1 translation [43]. These findings collectively elucidate the mechanism of CCND1 action during RSV infection: down-regulation of CCND1 results in G1/S phase transition arrest of the cell cycle, thereby promoting RSV replication. In addition, researchers have shown that knocking down CCND1 followed by inhibiting the PI3K/AKT/mTOR signaling pathway is effective [44], and that overexpressing CCND1 led to an enhancement in pathway activity [45]. Downregulation of CCND1 after RSV infection might result in the inhibition of the PI3K-Akt signaling pathway. This, in turn, inhibits the anti-inflammatory effects in the lungs that PI3K-Akt activation brings. Activation of the JAK-STAT signaling pathway has been demonstrated to induce a range of physiopathological processes, including cell proliferation, differentiation, and tumorigenesis [46]. These processes may be closely related to CCND1. Nevertheless, there have been no definitive studies conducted thus far to demonstrate a clear correlation between CCND1 and JAK-STAT. Furthermore, evidence has been found for a cross-interaction pattern between various signaling pathways [47]. In conclusion, CCND1 has a complex and close relationship with both the PI3K-Akt and JAK-STAT signaling pathways.
In the domain of RSV treatment, ribavirin was sanctioned by the US Food and Drug Administration (FDA) in 1986 and is the sole pharmaceutical agent authorized to date for the management of RSV infections [48]. Nevertheless, due to its substantial toxic side effects, its use is only of some value in immunodeficient patients and infants with severe RSV infection [49]. Monoclonal antibodies, on the other hand, are an effective option for the treatment of RSV infection. However, only one such antibody, Palivizumab (Synagis®), is currently licensed. Palivizumab (Synagis®) is effective in the treatment of RSV infections; however, its limited duration of action and the high cost of treatment limit its use [50]. Recently, a new monoclonal antibody, Nirsevimab (Beyfortus®), has demonstrated the potential for a more protracted protective effect [51]. Despite these advances, the field still lacks a definitive and highly effective treatment for RSV.
In this study, CCND1 exhibited significant docking activity with 2-Acetoxyacorenone, suggesting the potential efficacy of 2-Acetoxyacorenone as a therapeutic agent for RSV infection. Given the major limitations of existing drugs and methods for RSV treatment, this study proposes a novel approach: targeting CCND1 for the management of RSV infection. In addition, it is worth noting that despite its traditional use as a Tibetan medicinal herb, there has been a lack of in-depth investigation into the mechanisms of disease treatment using Acorus calamus and its active compounds. In the case of 2-Acetoxyacorenone, it was initially identified as a sesquiterpene constituent in Acorus calamus in earlier studies [52]; however, no further exploration of its bioactive role has been conducted to date. The present study elucidates the potential mechanism by which Acorus calamus may act against RSV infection and indicates that 2-Acetoxyacorenone could serve as a promising drug candidate for targeting CCND1 in RSV therapy. This work provides a solid foundation for future research aimed at uncovering the bioactive properties of 2-Acetoxyacorenone.

5. Conclusions

Our research conducted a systematic analysis of the molecular mechanisms underlying the interaction of Acorus calamus on RSV by integrating network pharmacology and the molecular docking technique. The results demonstrated that 2-Acetoxyacorenone, calamusin D, acoric acid, and isoeugenol might serve as effective components for RSV infection, with CCND1, EGFR, and SRC identified as core genes. Notably, 2-Acetoxyacorenone stood out as the most critical compound, acting as a potential drug candidate targeting CCND1. Furthermore, Acorus calamus’s therapeutic action against RSV encompasses various pathways, such as the PI3K-Akt signaling pathway and the JAK-STAT signaling pathway.
In conclusion, the present study revealed that Acorus calamus exhibits certain anti-RSV activity and holds promise as an effective drug for treating RSV infection within the Tibetan medicine system, demonstrating significant research and development value. This study has provided a new insight into the molecular basis of Acorus calamus in RSV infection and will act as a valuable reference point for future studies in this area.
The present study systematically and comprehensively analyzed the molecular mechanism of Acorus calamus in the infection of RSV by combining multiple analytical methods, thus providing a new basis for the treatment of RSV. However, it should be noted that this study is not without its limitations. Firstly, the sources of drug components and targets in this study were obtained from the literature and databases, and the accuracy of these data depends on the quality of the sources. Secondly, the reliability of the results may have been limited by our failure to use a positive control during molecular docking. Thirdly, our study lacks an Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) assessment of Acorus calamus, which represents a critical piece of information that should be incorporated in subsequent research. Finally, while this study provides a theoretical basis for the treatment of RSV, further verification of the correctness and practical value of the theory through animal experiments and clinical trials is necessary.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/cimb47090695/s1.

Author Contributions

Data curation, H.C. and H.L.; methodology, H.C., L.S. and K.T.; project administration, S.W. and B.X.; software, L.S. and X.C.; supervision, S.W. and W.L.; validation, K.T.; writing—original draft, H.C. and L.S.; writing—review and editing, S.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Key Research and Development Program of Xizang Autonomous Region, grant number XZ202301ZY0033G.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The authors confirm that the data supporting the findings of this study are available within this manuscript and the tables.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Verwey, C.; Madhi, S.A. Review and Update of Active and Passive Immunization Against Respiratory Syncytial Virus. BioDrugs 2023, 37, 295–309. [Google Scholar] [CrossRef] [PubMed]
  2. McMorrow, M.L.; Moline, H.L.; Toepfer, A.P.; Halasa, N.B.; Schuster, J.E.; Staat, M.A.; Williams, J.V.; Klein, E.J.; Weinberg, G.A.; Clopper, B.R.; et al. Respiratory Syncytial Virus-Associated Hospitalizations in Children < 5 Years: 2016–2022. Pediatrics 2024, 154, e2023065623. [Google Scholar] [CrossRef]
  3. Li, Y.; Wang, X.; Blau, D.M.; Caballero, M.T.; Feikin, D.R.; Gill, C.J.; Madhi, S.A.; Omer, S.B.; Simões, E.A.F.; Campbell, H.; et al. Global, regional, and national disease burden estimates of acute lower respiratory infections due to respiratory syncytial virus in children younger than 5 years in 2019: A systematic analysis. Lancet 2022, 399, 2047–2064. [Google Scholar] [CrossRef]
  4. Li, Z.J.; Zhang, H.Y.; Ren, L.L.; Lu, Q.B.; Ren, X.; Zhang, C.H.; Wang, Y.F.; Lin, S.H.; Zhang, X.A.; Li, J.; et al. Etiological and epidemiological features of acute respiratory infections in China. Nat. Commun. 2021, 12, 5026. [Google Scholar] [CrossRef] [PubMed]
  5. Buonsenso, D. Bivalent Prefusion F Vaccine in Pregnancy to Prevent RSV Illness in Infants. N. Engl. J. Med. 2023, 389, 1053. [Google Scholar] [CrossRef] [PubMed]
  6. Hammitt, L.L.; Dagan, R.; Yuan, Y.; Baca Cots, M.; Bosheva, M.; Madhi, S.A.; Muller, W.J.; Zar, H.J.; Brooks, D.; Grenham, A.; et al. Nirsevimab for Prevention of RSV in Healthy Late-Preterm and Term Infants. N. Engl. J. Med. 2022, 386, 837–846. [Google Scholar] [CrossRef]
  7. Carvajal, J.J.; Avellaneda, A.M.; Salazar-Ardiles, C.; Maya, J.E.; Kalergis, A.M.; Lay, M.K. Host Components Contributing to Respiratory Syncytial Virus Pathogenesis. Front. Immunol. 2019, 10, 2152. [Google Scholar] [CrossRef]
  8. Verwey, C.; Nunes, M.C.; Dangor, Z.; Madhi, S.A. Pulmonary function sequelae after respiratory syncytial virus lower respiratory tract infection in children: A systematic review. Pediatr. Pulmonol. 2020, 55, 1567–1583. [Google Scholar] [CrossRef]
  9. Sevindik, M.; Bal, C.; Eraslan, E.C.; Uysal, I.; Mohammed, F.S. Medicinal mushrooms: A comprehensive study on their antiviral potential. Prospect. Pharm. Sci. 2023, 21, 42–56. [Google Scholar] [CrossRef]
  10. Fu, K.; Xu, M.; Zhou, Y.; Li, X.; Wang, Z.; Liu, X.; Meng, X.; Zeng, Y.; Zhang, H. The Status quo and way forwards on the development of Tibetan medicine and the pharmacological research of tibetan materia Medica. Pharmacol. Res. 2020, 155, 104688. [Google Scholar] [CrossRef]
  11. Si, M.M.; Lou, J.S.; Zhou, C.X.; Shen, J.N.; Wu, H.H.; Yang, B.; He, Q.J.; Wu, H.S. Insulin releasing and alpha-glucosidase inhibitory activity of ethyl acetate fraction of Acorus calamus in vitro and in vivo. J. Ethnopharmacol. 2010, 128, 154–159. [Google Scholar] [CrossRef] [PubMed]
  12. Zhang, K.; Wang, L.; Peng, J.; Sangji, K.; Luo, Y.; Zeng, Y.; Zeweng, Y.; Fan, G. Traditional Tibetan medicine to fight against COVID-19: Basic theory and therapeutic drugs. Front. Pharmacol. 2023, 14, 1098253. [Google Scholar] [CrossRef] [PubMed]
  13. Lakhani, S.; Rojmala, J.V.; Chotai, N.M.; Waghela, B.N.; Thakor, P. Virtual screening and identification of potent phytoconstituents from Acorus calamus L. as inhibitors of Monkeypox virus infection. J. Genet. Eng. Biotechnol. 2025, 23, 100487. [Google Scholar] [CrossRef]
  14. Yuan, C.; Wang, M.H.; Wang, F.; Chen, P.Y.; Ke, X.G.; Yu, B.; Yang, Y.F.; You, P.T.; Wu, H.Z. Network pharmacology and molecular docking reveal the mechanism of Scopoletin against non-small cell lung cancer. Life Sci. 2021, 270, 119105. [Google Scholar] [CrossRef]
  15. Assaggaf, H.; Jeddi, M.; Mrabti, H.N.; Ez-Zoubi, A.; Qasem, A.; Attar, A.; Goh, B.H.; Tan, S.L.; Bouyahya, A.; Goh, K.W.; et al. Design of three-component essential oil extract mixture from Cymbopogon flexuosus, Carum carvi, and Acorus calamus with enhanced antioxidant activity. Sci. Rep. 2024, 14, 9195. [Google Scholar] [CrossRef]
  16. Huang, Y.; Li, Z.; Ma, Y.; Wu, Q.; Kong, J.; Zhao, L.; Li, S.; Li, J. Screening for Active Compounds of Acorus calamus against SARS-CoV-2 Viral Protease and Mechanism Prediction. Pharmaceuticals 2024, 17, 325. [Google Scholar] [CrossRef]
  17. Gupta, H.; Deeksha; Urvashi; Reddy, S.G.E. Insecticidal and Detoxification Enzyme Inhibition Activities of Essential Oils for the Control of Pulse Beetle, Callosobruchus maculatus (F.) and Callosobruchus chinensis (L.) (Coleoptera: Bruchidae). Molecules 2023, 28, 492. [Google Scholar] [CrossRef] [PubMed]
  18. Shalini, K.; Guleria, S.; Salaria, D.; Rolta, R.; Fadare, O.A.; Mehta, J.; Awofisayo, O.; Mandyal, P.; Shandilya, P.; Kaushik, N.; et al. Antimicrobial potential of phytocompounds of Acorus calamus: In silico approach. J. Biomol. Struct. Dyn. 2024, 42, 2726–2737. [Google Scholar] [CrossRef]
  19. Bai, D.; Li, X.; Wang, S.; Zhang, T.; Wei, Y.; Wang, Q.; Dong, W.; Song, J.; Gao, P.; Li, Y.; et al. Advances in extraction methods, chemical constituents, pharmacological activities, molecular targets and toxicology of volatile oil from Acorus calamus var. angustatus Besser. Front. Pharmacol. 2022, 13, 1004529. [Google Scholar] [CrossRef]
  20. Kumar, C.; Akhter, S.; Satti, N.K.; Gupta, V.K.; Meena, S.R.; Vishwakarma, R.; Hassan, Q.P.; Verma, M.K. Dereplication approach for the first time isolation of tatarinowin a and pentadecanoic acid from Acorus calamus L. by using GC-MS. Nat. Prod. Res. 2023, 37, 2632–2637. [Google Scholar] [CrossRef]
  21. Islamoglu, F. Molecular docking, bioactivity, ADME, toxicity risks, and quantum mechanical parameters of some 1,2dihydroquinoline derivatives were calculated theoretically for investigation of its use as a pharmaceutical active ingredient in the treatment of multiple sclerosis (MS). Prospect. Pharm. Sci. 2024, 22, 168–187. [Google Scholar] [CrossRef]
  22. Shang, Z.; Tan, S.; Ma, D. Respiratory syncytial virus: From pathogenesis to potential therapeutic strategies. Int. J. Biol. Sci. 2021, 17, 4073–4091. [Google Scholar] [CrossRef]
  23. Labrie, L.; McVea, R.C.; Karkout, R.; Aldossary, H.; Gaudreault, V.; Ward, B.J.; Fixman, E.D. Early-life RSV infection modulates innate immune events, preferentially enhancing allergen-induced type 2 lung inflammation in females. PLoS Pathog. 2025, 21, e1013340. [Google Scholar] [CrossRef]
  24. Yanik, S.D.; Jamal Jameel, K.; Rohde, S.; Bürger, P.; Bülthoff, E.; Grunwald, T.; Kronsbein, J.; Koch, A.; Edwards, M.R.; Tenbusch, M.; et al. Cytokine production of mononuclear leukocytes in response to respiratory syncytial virus is increased in COPD but suppressed in non-COPD tobacco smokers. Mol. Med. 2025, 31, 237. [Google Scholar] [CrossRef] [PubMed]
  25. Li, J.J.; Liu, M.L.; Lv, J.N.; Chen, R.L.; Ding, K.; He, J.Q. Polysaccharides from Platycodonis Radix ameliorated respiratory syncytial virus-induced epithelial cell apoptosis and inflammation through activation of miR-181a-mediated Hippo and SIRT1 pathways. Int. Immunopharmacol. 2022, 104, 108510. [Google Scholar] [CrossRef] [PubMed]
  26. Yang, X.; Liu, X.; Nie, Y.; Zhan, F.; Zhu, B. Oxidative stress and ROS-mediated cellular events in RSV infection: Potential protective roles of antioxidants. Virol. J. 2023, 20, 224. [Google Scholar] [CrossRef] [PubMed]
  27. Robinson, E.; Herbert, J.A.; Palor, M.; Ren, L.; Larken, I.; Patel, A.; Moulding, D.; Cortina-Borja, M.; Smyth, R.L.; Smith, C.M. Trans-epithelial migration is essential for neutrophil activation during RSV infection. J. Leukoc. Biol. 2023, 113, 354–364. [Google Scholar] [CrossRef]
  28. Stegmann, F.; Lepenies, B. Myeloid C-type lectin receptors in host-pathogen interactions and glycan-based targeting. Curr. Opin. Chem. Biol. 2024, 82, 102521. [Google Scholar] [CrossRef]
  29. Chen, L.; Zhang, J.; Xu, W.; Chen, J.; Tang, Y.; Xiong, S.; Li, Y.; Zhang, H.; Li, M.; Liu, Z. Cholesterol-rich lysosomes induced by respiratory syncytial virus promote viral replication by blocking autophagy flux. Nat. Commun. 2024, 15, 6311. [Google Scholar] [CrossRef]
  30. Yang, M.; Zhang, X.; Liu, Q.; Wang, Y. Network pharmacology, molecular docking, and untargeted metabolomics reveal molecular mechanisms of multi-targets effects of Qingfei Tongluo Plaster improving respiratory syncytial virus pneumonia. Chin. Herb. Med. 2024, 16, 638–655. [Google Scholar] [CrossRef]
  31. Efstathiou, C.; Zhang, Y.; Kandwal, S.; Fayne, D.; Molloy, E.J.; Stevenson, N.J. Respiratory syncytial virus NS1 inhibits anti-viral Interferon-α-induced JAK/STAT signaling, by limiting the nuclear translocation of STAT1. Front. Immunol. 2024, 15, 1395809. [Google Scholar] [CrossRef]
  32. Li, L.; Xu, W.; Luo, Y.; Lao, C.; Tong, X.; Du, J.; Huang, B.; Li, D.; Chen, J.; Ye, H.; et al. Aloe polymeric acemannan inhibits the cytokine storm in mouse pneumonia models by modulating macrophage metabolism. Carbohydr. Polym. 2022, 297, 120032. [Google Scholar] [CrossRef]
  33. Mazarakis, N.; Higgins, R.A.; Anderson, J.; Toh, Z.Q.; Luwor, R.B.; Snibson, K.J.; Karagiannis, T.C.; Do, L.A.H.; Licciardi, P.V. The effects of the dietary compound L-sulforaphane against respiratory pathogens. Int. J. Antimicrob. Agents 2021, 58, 106460. [Google Scholar] [CrossRef]
  34. Noh, S.S.; Shin, H.J. RSV Induces Activation of Intracellular EGFR on the Mitochondrial Membrane for Virus Propagation. Int. J. Mol. Sci. 2023, 24, 17431. [Google Scholar] [CrossRef] [PubMed]
  35. Xu, X.; Qiao, D.; Pan, L.; Boldogh, I.; Zhao, Y.; Brasier, A.R. RELA∙8-Oxoguanine DNA Glycosylase1 Is an Epigenetic Regulatory Complex Coordinating the Hexosamine Biosynthetic Pathway in RSV Infection. Cells 2022, 11, 2210. [Google Scholar] [CrossRef] [PubMed]
  36. Huang, J.; Chen, Z.; Ye, Y.; Shao, Y.; Zhu, P.; Li, X.; Ma, Y.; Xu, F.; Zhou, J.; Wu, M.; et al. DTX3L Enhances Type I Interferon Antiviral Response by Promoting the Ubiquitination and Phosphorylation of TBK1. J. Virol. 2023, 97, e0068723. [Google Scholar] [CrossRef] [PubMed]
  37. Zhao, C.; Bai, Y.; Wang, W.; Amonkar, G.M.; Mou, H.; Olejnik, J.; Hume, A.J.; Mühlberger, E.; Lukacs, N.W.; Fearns, R.; et al. Activation of STAT3-mediated ciliated cell survival protects against severe infection by respiratory syncytial virus. J. Clin. Invest. 2024, 134, e183978. [Google Scholar] [CrossRef]
  38. Santos, L.D.; Antunes, K.H.; Muraro, S.P.; de Souza, G.F.; da Silva, A.G.; Felipe, J.S.; Zanetti, L.C.; Czepielewski, R.S.; Magnus, K.; Scotta, M.; et al. TNF-mediated alveolar macrophage necroptosis drives disease pathogenesis during respiratory syncytial virus infection. Eur. Respir. J. 2021, 57, 2003764. [Google Scholar] [CrossRef]
  39. Lingemann, M.; McCarty, T.; Liu, X.; Buchholz, U.J.; Surman, S.; Martin, S.E.; Collins, P.L.; Munir, S. The alpha-1 subunit of the Na+,K+-ATPase (ATP1A1) is required for macropinocytic entry of respiratory syncytial virus (RSV) in human respiratory epithelial cells. PLoS Pathog. 2019, 15, e1007963. [Google Scholar] [CrossRef]
  40. Gibbs, J.D.; Ornoff, D.M.; Igo, H.A.; Zeng, J.Y.; Imani, F. Cell cycle arrest by transforming growth factor beta1 enhances replication of respiratory syncytial virus in lung epithelial cells. J. Virol. 2009, 83, 12424–12431. [Google Scholar] [CrossRef]
  41. Mohapatra, S.; Park, S.J.; Boyapalle, S.; Pastey, M.K.; Graham, B.S.; Blanck, G. Human respiratory syncytial virus reduces the number of cells in S-phase and increases GADD153 expression in HEp-2 cells. Acta Virol. 2009, 53, 207–211. [Google Scholar] [CrossRef] [PubMed]
  42. Sun, F.; Fu, H.; Liu, Q.; Tie, Y.; Zhu, J.; Xing, R.; Sun, Z.; Zheng, X. Downregulation of CCND1 and CDK6 by miR-34a induces cell cycle arrest. FEBS Lett. 2008, 582, 1564–1568. [Google Scholar] [CrossRef]
  43. Bakre, A.; Mitchell, P.; Coleman, J.K.; Jones, L.P.; Saavedra, G.; Teng, M.; Tompkins, S.M.; Tripp, R.A. Respiratory syncytial virus modifies microRNAs regulating host genes that affect virus replication. J. Gen. Virol. 2012, 93, 2346–2356. [Google Scholar] [CrossRef] [PubMed]
  44. Yao, J.; Wang, Z.; Cheng, Y.; Ma, C.; Zhong, Y.; Xiao, Y.; Gao, X.; Li, Z. M2 macrophage-derived exosomal microRNAs inhibit cell migration and invasion in gliomas through PI3K/AKT/mTOR signaling pathway. J. Transl. Med. 2021, 19, 99. [Google Scholar] [CrossRef] [PubMed]
  45. Wang, X.; Liu, X.; Yang, Y.; Yang, D. Cyclin D1 mediated by the nuclear translocation of nuclear factor kappa B exerts an oncogenic role in lung cancer. Bioengineered 2022, 13, 6866–6879. [Google Scholar] [CrossRef]
  46. Xue, C.; Yao, Q.; Gu, X.; Shi, Q.; Yuan, X.; Chu, Q.; Bao, Z.; Lu, J.; Li, L. Evolving cognition of the JAK-STAT signaling pathway: Autoimmune disorders and cancer. Signal Transduct. Target. Ther. 2023, 8, 204. [Google Scholar] [CrossRef]
  47. Guo, Q.; Jin, Y.; Chen, X.; Ye, X.; Shen, X.; Lin, M.; Zeng, C.; Zhou, T.; Zhang, J. NF-κB in biology and targeted therapy: New insights and translational implications. Signal Transduct. Target. Ther. 2024, 9, 53. [Google Scholar] [CrossRef]
  48. Shtro, A.A.; Petukhova, G.D.; Romanova, A.S. Protein and Peptide Substances in the Treatment of Respiratory Syncytial Infection: Current State. Molecules 2022, 27, 2263. [Google Scholar] [CrossRef]
  49. Mammas, I.N.; Drysdale, S.B.; Rath, B.; Theodoridou, M.; Papaioannou, G.; Papatheodoropoulou, A.; Koutsounaki, E.; Koutsaftiki, C.; Kozanidou, E.; Achtsidis, V.; et al. Update on current views and advances on RSV infection (Review). Int. J. Mol. Med. 2020, 46, 509–520. [Google Scholar] [CrossRef]
  50. Hu, M.; Bogoyevitch, M.A.; Jans, D.A. Impact of Respiratory Syncytial Virus Infection on Host Functions: Implications for Antiviral Strategies. Physiol. Rev. 2020, 100, 1527–1594. [Google Scholar] [CrossRef]
  51. Pantaleo, G.; Correia, B.; Fenwick, C.; Joo, V.S.; Perez, L. Antibodies to combat viral infections: Development strategies and progress. Nat. Rev. Drug Discov. 2022, 21, 676–696. [Google Scholar] [CrossRef] [PubMed]
  52. Nawamaki, K.; Kuroyanagi, M. Sesquiterpenoids from Acorus calamus as germination inhibitors. Phytochemistry 1996, 43, 1175–1182. [Google Scholar] [CrossRef]
Figure 1. Venn diagram of 1633 common disease targets after the merger of GeneCards and OMIM.
Figure 1. Venn diagram of 1633 common disease targets after the merger of GeneCards and OMIM.
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Figure 2. Visualization of 87 overlapping targets between Acorus calamus active compounds and RSV disease targets via Venn diagram.
Figure 2. Visualization of 87 overlapping targets between Acorus calamus active compounds and RSV disease targets via Venn diagram.
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Figure 3. Network between herb compounds and disease targets.
Figure 3. Network between herb compounds and disease targets.
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Figure 4. Common targets PPI network from STRING.
Figure 4. Common targets PPI network from STRING.
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Figure 5. PPI network topology analysis result by Cytoscape 3.10.2.
Figure 5. PPI network topology analysis result by Cytoscape 3.10.2.
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Figure 6. Top 15 core targets from PPI network using the CytoHubba plugin and MCC algorithm.
Figure 6. Top 15 core targets from PPI network using the CytoHubba plugin and MCC algorithm.
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Figure 7. Bubble diagram illustrating the top 30 diseases identified through DO enrichment.
Figure 7. Bubble diagram illustrating the top 30 diseases identified through DO enrichment.
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Figure 8. Bubble diagram representing GO functional enrichment outcomes.
Figure 8. Bubble diagram representing GO functional enrichment outcomes.
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Figure 9. Bubble plot showing the top 30 pathways identified through KEGG enrichment analysis.
Figure 9. Bubble plot showing the top 30 pathways identified through KEGG enrichment analysis.
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Figure 10. Compound–target–pathway network.
Figure 10. Compound–target–pathway network.
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Figure 11. Venn diagram depicting the overlap of core targets identified from PPI analysis and the drug–compound–target–pathway network.
Figure 11. Venn diagram depicting the overlap of core targets identified from PPI analysis and the drug–compound–target–pathway network.
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Figure 12. Heatmap of molecular docking scores between core targets and active compounds.
Figure 12. Heatmap of molecular docking scores between core targets and active compounds.
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Figure 13. Binding conformations between key targets and bioactive compounds.
Figure 13. Binding conformations between key targets and bioactive compounds.
Cimb 47 00695 g013aCimb 47 00695 g013bCimb 47 00695 g013cCimb 47 00695 g013d
Figure 14. Validation of core targets from datasets of GEO (GSE105450 and GSE77087). (a) Volcano plot of DEGs in GSE105450. (b) Heatmap of the top 50 DEGs in GSE105450. (c) Volcano plot of DEGs in GSE77087. (d) Heatmap of the top 50 DEGs in GSE77087. (e) Identification of the core gene CCND1.
Figure 14. Validation of core targets from datasets of GEO (GSE105450 and GSE77087). (a) Volcano plot of DEGs in GSE105450. (b) Heatmap of the top 50 DEGs in GSE105450. (c) Volcano plot of DEGs in GSE77087. (d) Heatmap of the top 50 DEGs in GSE77087. (e) Identification of the core gene CCND1.
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Figure 15. CCND1 expression in the two RSV datasets. (a) CCND1 expression of GSE105450. (b) CCND1 expression of GSE77087. ***p < 0.001 versus control.
Figure 15. CCND1 expression in the two RSV datasets. (a) CCND1 expression of GSE105450. (b) CCND1 expression of GSE77087. ***p < 0.001 versus control.
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Figure 16. mRNA expression levels of CCND1 in different cells and tissues from BioGPS.
Figure 16. mRNA expression levels of CCND1 in different cells and tissues from BioGPS.
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Table 1. Details of the 26 active compounds of Acorus calamus.
Table 1. Details of the 26 active compounds of Acorus calamus.
NO.Compound NamePubChem CIDStructure
12-Acetoxyacorenone 10850234 Cimb 47 00695 i001
2calamusin D 60156053 Cimb 47 00695 i002
3acoric acid 15558301 Cimb 47 00695 i003
4isoeugenol 853433 Cimb 47 00695 i004
5Methyl palmitate 8181 Cimb 47 00695 i005
6eugenol 3314 Cimb 47 00695 i006
7(Z)-Methyl isoeugenol 1549045 Cimb 47 00695 i007
8methyl isoeugenol 637776 Cimb 47 00695 i008
9Calamensesquiterpinenol 75250012 Cimb 47 00695 i009
10Calamusin F 60156148 Cimb 47 00695 i010
11 camphor 2537 Cimb 47 00695 i011
12 Calamusin E 60156054 Cimb 47 00695 i012
13 eugenyl acetate 7136 Cimb 47 00695 i013
14 bullatantriol 71430886 Cimb 47 00695 i014
15 2,4,5-Trimethoxybenzoic acid 10276 Cimb 47 00695 i015
16 Cedranone 111402 Cimb 47 00695 i016
17 Dehydroxy-isocalamendiol 535379 Cimb 47 00695 i017
18 cis –asarone 636822 Cimb 47 00695 i018
19 Calamusin I 60156151 Cimb 47 00695 i019
20 Isoacoramone 3083746 Cimb 47 00695 i020
21 β asarone 5281758 Cimb 47 00695 i021
22 acorone 5316254 Cimb 47 00695 i022
23 tau-Muurolol 6432221 Cimb 47 00695 i023
24 (E)-3-(2,4,5-Trimethoxyphenyl)acrylaldehyde 9813266 Cimb 47 00695 i024
25 oplodiol 12313756 Cimb 47 00695 i025
26 Thujopsanone 13893399 Cimb 47 00695 i026
Table 2. The 87 overlapping targets shared by active compounds and disease-associated targets.
Table 2. The 87 overlapping targets shared by active compounds and disease-associated targets.
NO.TargetNO.TargetNO.TargetNO.Target
1ABCB123CYP19A145ITGB267PIK3CD
2ABCG224CYP1A146JAK168PPARA
3ACE25CYP2C947JAK269PPARD
4ACHE26DYRK1A48KDR70PPP1CA
5AGTR227EGFR49KMO71PSMB5
6AHR28EPAS150MAPK1472PTGDR2
7ALOX529EZH251MAPKAPK273PTGES
8AOC330F252MDM274PTGS2
9APP31F2R53MIF75PTPN1
10AR32FABP454MMP276PTPN11
11BRD433FGFR155MPO77PTPN2
12CCNA234FLT156MTNR1A78RELA
13CCND135G6PD57MTNR1B79RHOA
14CCR136HDAC658NFE2L280SRC
15CDK137HMGCR59NLRP381STAT3
16CHRM138HSD11B160NOS282TACR1
17CNR239HSD11B261NR3C183TNF
18CREBBP40HSPA1A62NR3C284TRPV1
19CTSB41ICAM163PABPC185TYK2
20CTSL42ITGAL64PARP186VDR
21CXCL843ITGAV65PGR87VEGFA
22CXCR244ITGB166PIK3CB
Table 3. Details of the top 10 compounds in the network between herb compounds and disease targets.
Table 3. Details of the top 10 compounds in the network between herb compounds and disease targets.
RankCompound NamePubChem CIDDegree
12-Acetoxyacorenone 10850234 41
2calamusin D 60156053 24
3acoric acid 15558301 22
4isoeugenol 853433 21
5Methyl palmitate 8181 13
6eugenol 3314 9
7(Z)-Methyl isoeugenol 1549045 4
8methyl isoeugenol 637776 4
9Calamensesquiterpinenol 75250012 3
10Calamusin F 60156148 3
Table 4. Details of the top 15 core targets from PPI network.
Table 4. Details of the top 15 core targets from PPI network.
RankGene NameScore
1STAT31.66 × 109
2EGFR1.66 × 109
3TNF1.66 × 109
4CCND11.63 × 109
5PARP11.39 × 109
6MDM21.38 × 109
7EZH21.22 × 109
8AR1.21 × 109
9RELA1.17 × 109
10CREBBP1.10 × 109
11SRC1.06 × 109
12CDK11.04 × 109
13HDAC61.00 × 109
14BRD45.19 × 108
15MMP25.07 × 108
Table 5. Details of the top 15 core targets from compound–target–pathway network.
Table 5. Details of the top 15 core targets from compound–target–pathway network.
RankGene NameDegreeCCBC
1PIK3CB920.4989980.080407
2PIK3CD920.4989980.080407
3RELA720.4470380.061346
4MAPK14570.4241910.031357
5TNF550.4345550.045415
6EGFR440.3996790.020541
7SRC400.3958660.019708
8CCND1390.3755660.011924
9RHOA340.4035660.016991
10STAT3330.3872470.011039
11CXCL8320.3813170.013256
12JAK1280.3789950.007265
13JAK2260.3778450.007811
14VEGFA250.3744360.008855
15PTGS2210.3848530.011878
Table 6. Correspondence between gene names and PDB IDs.
Table 6. Correspondence between gene names and PDB IDs.
Gene NamePDB ID
CCND16p8e
EGFR8a27
RELA7let
SRC7ng7
STAT36njs
TNF5uui
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Chang, H.; Shao, L.; Tao, K.; Chen, X.; Liao, H.; Liao, W.; Xue, B.; Wang, S. Exploring CCND1 as a Key Target of Acorus calamus Against RSV Infection: Network Pharmacology, Molecular Docking, and Bioinformatics Analysis. Curr. Issues Mol. Biol. 2025, 47, 695. https://doi.org/10.3390/cimb47090695

AMA Style

Chang H, Shao L, Tao K, Chen X, Liao H, Liao W, Xue B, Wang S. Exploring CCND1 as a Key Target of Acorus calamus Against RSV Infection: Network Pharmacology, Molecular Docking, and Bioinformatics Analysis. Current Issues in Molecular Biology. 2025; 47(9):695. https://doi.org/10.3390/cimb47090695

Chicago/Turabian Style

Chang, Haojing, Li Shao, Ke Tao, Xiangjun Chen, Hehe Liao, Wang Liao, Bei Xue, and Shaokang Wang. 2025. "Exploring CCND1 as a Key Target of Acorus calamus Against RSV Infection: Network Pharmacology, Molecular Docking, and Bioinformatics Analysis" Current Issues in Molecular Biology 47, no. 9: 695. https://doi.org/10.3390/cimb47090695

APA Style

Chang, H., Shao, L., Tao, K., Chen, X., Liao, H., Liao, W., Xue, B., & Wang, S. (2025). Exploring CCND1 as a Key Target of Acorus calamus Against RSV Infection: Network Pharmacology, Molecular Docking, and Bioinformatics Analysis. Current Issues in Molecular Biology, 47(9), 695. https://doi.org/10.3390/cimb47090695

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