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. 2025 Jun 17:16:1582374.
doi: 10.3389/fphar.2025.1582374. eCollection 2025.

Decoding the therapeutic mechanism of Conocarpus lancifolius in hepatocellular carcinoma: network pharmacology, molecular docking, and LC-MS QTOF insights

Poojaben M Prajapati  1 , Saumya K Patel  1 , Rakesh M Rawal  2 , Komal G Lakhani  3   4 , Rasmieh Hamid  5 , Bharat B Maitreya  1
Affiliations

Decoding the therapeutic mechanism of Conocarpus lancifolius in hepatocellular carcinoma: network pharmacology, molecular docking, and LC-MS QTOF insights

Poojaben M Prajapati et al. Front Pharmacol. .

Abstract

Hepatocellular carcinoma is a multifaceted and lethal malignancy, ranking third in cancer-related mortality and sixth in worldwide incidence. This study aimed to utilize LCMS-QTOF analysis to identify the phytoconstituents of C. lancifolius across three distinct seasons. The study also sought to elucidate the multi-layered mechanism of action against hepatocellular carcinoma using network pharmacology analysis, molecular docking, and molecular dynamics simulation. A total of 352 phytoconstituents were identified in the extract of Conocarpus lancifolius, of which 154 compounds were chosen for subsequent in silico analysis. Network construction and Gene Ontology (GO) enrichment analysis were performed using ShinyGo and the KEGG database, while Cytoscape 3.10.2 was employed for network visualization and analysis. Molecular docking analyses were conducted using YASARA software, and the highest-scoring compounds and targets underwent 100 ns molecular dynamics simulations via Schrödinger Desmond. CytoHubba identified ten key hub genes, including CASP3, STAT3, and EGFR. GO and KEGG analyses revealed significant biological processes, molecular functions, cellular components, and pathways, including PPAR signaling, thyroid cancer, and prolactin pathways. Notably, phytochemicals from C. lancifolius, particularly Alnusiin, Egrosine, and Yessotoxin, exhibited strong binding affinities with CASP3 and STAT3. The structural stability of Alnusiin in complex with these target proteins was confirmed through molecular dynamics simulation, indicating its potential as a promising anti-HCC agent. This study integrates network pharmacology, molecular docking, and molecular dynamics simulations to characterize the bioactive compounds in C. lancifolius and elucidate a plausible mechanism for its therapeutic action against hepatocellular carcinoma.

Keywords: C. lancifolius; LCMS QToF; molecular docking; molecular dynamic simulation; network pharmacology.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
(A) Protein–Protein Interaction (PPI) network of target genes predicted from LCMS-QTOF-identified compounds and (B) Top hub genes identified using the MCC algorithm via the CytoHubba plugin in Cytoscape.
FIGURE 2
FIGURE 2
Compound and Gene Network whereas pink shows the targeted gene and blue color shows the compound.
FIGURE 3
FIGURE 3
Gene ontology of proteins regulated by bioactives of C. lancifolius for (A) molecular function, (B) cellular components, and (C) biological process.
FIGURE 4
FIGURE 4
Kegg pathway enrichment analysis of top-targeted genes in Conocarpus.
FIGURE 5
FIGURE 5
Molecular docking interaction of CASP3 with top three bioactive compounds. (A) Alnusiin, (B) Yessotoxin and (C) Ergosine. The figure illustrates the binding conformations of each compound within the STAT3 active site, highlighting key residues involved in hydrogen bonding and hydrophobic interactions that contribute to binding stability.
FIGURE 6
FIGURE 6
Molecular docking interaction of STAT3 with top three bioactive compounds. (A) Alnusiin, (B) Apigenin 7-(3″-acetyl-6″-E-p-coumaroyl glucoside), and (C) Dukunolide D. The figure illustrates the binding conformations of each compound within the STAT3 active site, highlighting key residues involved in hydrogen bonding and hydrophobic interactions that contribute to binding stability.
FIGURE 7
FIGURE 7
RMSD values of Alnussin with receptor proteins. (A) RMSD of the C-alpha atoms of CASP3 and Alnusiin; (B) RMSD of the Cα atoms of STAT3 and Alnusiin with time. The variation in RMSD of receptor protein is shown on the y-axis (on left) through time. The variation in RMSD of the ligand is shown on the y-axis (on right) through time.
FIGURE 8
FIGURE 8
The plots of residue wise root mean square fluctuation (RMSF). (A) RMSF plot of CASP3 with Alnusiin and (B) RMSF plot of STAT3 with Alnusiin.
FIGURE 9
FIGURE 9
Detailed ligand intereactions with protein residues of (A) PDB -IGFW and (B) pDB - 6TLC.
FIGURE 10
FIGURE 10
Protein-Ligand interaction profile of (A) CASP3-Alnussin and (B) STAT3-Alnusiin, interaction profile of crucial interacting amino acids, timeline representation of the interactions of amino acids.
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