Kusunokinin, a lignan compound, inhibits cancer cell proliferation and induces apoptosis; however, the role of kusunokinin is not fully understood. Here, we aimed to identify a target protein of (-)-kusunokinin and determine the protein levels of its downstream molecules. We found that (-)-kusunokinin bound 5 possible target proteins, including CSF1R, MMP-12, HSP90-α, CyclinB1 and MEK1 with ΔGbind less than -10.40 kcal/mol. MD simulation indicated (-)-kusunokinin and pexidartinib (P31, a specific CSF1R binding compound) shared some extents of functional similarity in which (-)-kusunokinin bound CSF1R at the juxtamembrane (JM) region with aromatic amino acids similar to pexidartinib using π-π interaction, as well as hydrogen bond. Both P31 and (-)-kusunokinin moved into the same CSF1R region and W7 was a mutual key residue. However, the P31 binding site differed from the (-)-kusunokinin binding site. For in vitro study, the synthetic (±)-kusunokinin exhibited stronger cytotoxicity than picropodophyllotoxin, silibinin and etoposide on MCF-7 cells and represented less toxicity than picropodophyllotoxin and doxorubicin on L-929 and MCF-12A cells. Knocking down CSF1R using a specific siRNA combination with (±)-kusunokinin demonstrated levels of cell proliferation proteins slightly higher than siRNA-CSF1R treatment. However, siRNA-CSF1R combination with P31 represented the number of cell viability and cell proliferation proteins, like in the control groups (Lipofectamine and siRNA-Luciferase). Moreover, (±)-kusunokinin suppressed CSF1R and its downstream proteins, including AKT, CyclinD1 and CDK1. Meanwhile, both P31 and siRNA-CSF1R dramatically suppressed CSF1R, MEK1, AKT, ERK, CyclinB1, CyclinD1 and CDK1. Our overall results indicate that the mechanism of (±)-kusunokinin differed fairly from P31. We have concluded that (±)-kusunokinin inhibited breast cancer cell proliferation partially through the binding and suppression of CSF1R, which consequently affected AKT and its downstream molecules.

Melanin, the pigment responsible for human skin color, increases susceptibility to UV radiation, leading to excessive melanin production and hyperpigmentation disorders. This study investigated the ethanolic extract of Garcinia atroviridis fruits for its phenolic and flavonoid contents, antioxidant activity, and impact on melanogenesis pathways using qRT-PCR and Western blot analysis. Utilizing network pharmacology, molecular docking, and dynamics simulations, researchers explored G. atroviridis fruit extract’s active compounds, targets, and pharmacological effects on hyperpigmentation. G. atroviridis fruit extract exhibited antioxidant properties, scavenging DPPH^• and ABTS^•+ radicals radicals and chelating copper. It inhibited cellular tyrosinase activity and melanin content in stimulated B16F10 cells, downregulating TYR, TRP-1, phosphorylated CREB, CREB, and MITF proteins along with transcription levels of MITF, TYR, and TRP-2. LC-MS analysis identified thirty-three metabolites, with seventeen compounds selected for further investigation. Network pharmacology revealed 41 hyperpigmentation-associated genes and identified significant GO terms and KEGG pathways, including cancer-related pathways. Kaempferol-3-O-α-L-rhamnoside exhibited high binding affinity against MAPK3/ERK1, potentially regulating melanogenesis by inhibiting tyrosinase activity. Stable ligand–protein interactions in molecular dynamics simulations supported these findings. Overall, this study suggests that the ethanolic extract of G. atroviridis fruits possesses significant antioxidant, tyrosinase inhibitory, and anti-melanogenic properties mediated through key molecular targets and pathways.

G Protein-Coupled Receptors (GPCRs) are integral membrane proteins that have gained considerable attention as drug targets, particularly in cancer treatment. In this study, we explored the capacity of bioactive compounds derived from Gnetum gnemon (GG) for the development of of pharmaceuticals targeting GPCRs within the context of cancer therapy. Integrated approach combined network pharmacology and molecular docking to identify and validate the underlying pharmacological mechanisms. We retrieved targets for GG-derived compounds and GPCRs-related cancer from databases. Subsequently, we established a protein-protein interaction (PPI) network by mapping the shared targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were employed to predict the mechanism of action of these targets. Molecular docking was conducted to validate our findings. We identified a total of 265 targets associated with GG-derived bioactive compounds for the treatment of GPCRs-related cancer. Functional enrichment analysis revealed the promising therapeutic effects of these targets on GPCRs-related cancer pathways. The PPI network analysis identified hub targets, including MAPK3, SRC, EGFR, STAT3, ESR1, MTOR, CCND1, and PPARG, which demonstrate as treatment targets for GPCRs-related cancer using GG-derived compounds. Additionally, molecular docking experiments demonstrated the strong binding affinity of gnetin A, gnetin C, (-)-viniferin, and resveratrol dimer, thus inhibiting MAPK3, SRC, EGFR, and MTOR. Survival analysis established the clinical prognostic relevance of identified hub genes in cancer. This study presents a novel approach for comprehending the therapeutic mechanisms of GG-derived active compounds and thereby paving the way for their prospective clinical applications in the field of cancer treatment.

Chronic kidney disease (CKD) involves inflammation, oxidative stress, and fibrosis, leading to renal dysfunction. Dapagliflozin, an SGLT2 inhibitor, shows renoprotective effects beyond glucose control, but its precise molecular mechanisms remain unclear. This study utilizes network pharmacology and molecular docking to elucidate its multi-target effects in CKD. Dapagliflozin’s SMILES structure was analyzed for ADMET properties. Potential targets were identified via SwissTargetPrediction, GeneCards, and SEA, and common CKD-related targets were determined. A protein–protein interaction (PPI) network was constructed, and key pathways were identified using GO and KEGG enrichment analyses. Molecular docking was conducted to validate dapagliflozin’s binding affinities with hub proteins. A total of 208 common targets were identified, including EGFR, GSK3β, and IL-6. GO and KEGG analyses highlighted key pathways, such as PI3K-Akt, MAPK, and AGE-RAGE, involved in inflammation, oxidative stress, and metabolic regulation. Molecular docking confirmed strong binding affinities with EGFR (−8.42 kcal/mol), GSK3β (−7.70 kcal/mol), and IL-6 (−6.83 kcal/mol). Dapagliflozin exhibits multi-target therapeutic potential in CKD by modulating inflammation, oxidative stress, and metabolic pathways. This integrative approach enhances the understanding of its mechanisms, supporting future experimental validation and clinical application in CKD management.