Fig 1.
Sequential experimental steps undertaken in the current study.
Fig 2.
Generated pharmacophore models using auto pharmacophore generation module of BIOVIA studio.
Fig 3.
Frontier molecular orbitals (FMOs) of linalool and LN@AgNPs in the form of HOMO, LUMO and the Energy gap (Eg) using the Gaussian 06 package.
Table 1.
Calculated energies and properties of linalool and LN@AgNPs.
Fig 4.
The Molecular electrostatic potential surface of selected compound linalool and its nanoconjugate (LN@AgNPs).
Table 2.
Physiochemical and drug likeness properties of selected compounds.
Fig 5.
BOILED-Egg results of two selected compounds in comparison, generated by SwissADME server.
Fig 6.
Bioavailability radar of selected compounds linalool (a) and LN@AgNPs (b) using the SwissADME server.
Table 3.
The absorption, distribution, excretion, metabolism, and toxicity of linalool and LN@AgNPs.
Fig 7.
The toxicity radar map shows the likelihood of positive toxicity results in relation to the average of the class (a).
The network chart shows the relationship between the chosen substance and anticipated activities (b).
Fig 8.
PIP network of 50 gene directly and indirectly involved in immune checkpoints using STRING.
Fig 9.
Box plots showing the expression of the 12 genes identified by the Gene Expression Profiling Interactive Analysis in glioblastoma multiforme: (a) AKT1, (b) CASP3, (c) CD8A, (d) CDK2NA, (e) CDK6, (f) CLAT4, (g) EGFR, (h) PDCD1 (i) PD-L1, (j) PROM1, (k) PTEN and (l) TP53. Num, number; T, tumor; N, normal.
Table 4.
Docking score of selected compounds against glioblastoma gene targets.
Table 5.
Residual amino acid interactions (H-bond, metal acceptor and hydrophobic).
Fig 10.
3D representation of docked complexes; binding mode of linalool and LN@AgNPs to the PD-L1.
Fig 11.
3D representation of docked complexes; binding mode of linalool and LN@AgNPs to the PTEN.
Fig 12.
RMSD plots for linalool in complex with PD-L1 (a) and PTEN (b); from each docked complex’s individual 100 ns MD simulation trajectory, the ligand RMSD values were calculated as the protein-fit ligand.
Protein RMSD values were retrieved for the alpha carbon atoms.
Fig 13.
Root Mean Square Fluctuation (RMSF) and Radius of Gyration (Rg) analyses of protein-ligand complexes over a 100 ns molecular dynamics (MD) simulation.
(a, b) RMSF plots showing the flexibility of each residue in the protein structures. (c, d) Rg plots showing compactness and structural stability over time. Panels (a) and (c) represent the PD-L1–linalool complex, whereas panels (b) and (d) correspond to the PTEN–linalool complex.
Fig 14.
Cross-correlation matrix showing coordinate fluctuations for Cα atoms around the mean positions during MD simulation: positive correlations are represented by red, whereas negative correlations are represented by blue.
PD-L1/linalool (a) and PTEN/linalool (b).
Fig 15.
Principal Component Analysis (PCA) of linalool-bound complexes.
(a, c) PCA projections showing motions along the first two principal components (PC1 and PC2) for the PD-L1 and PTEN complexes, respectively. (b, d) Representative conformations captured along PC1 and PC2, illustrating dominant motions extracted from the PCA.
Fig 16.
Free Energy Landscape (FEL) of linalool-bound complexes.
(a, b) 3D surface plots of Gibbs free energy landscapes for PD-L1 and PTEN complexes, respectively. Purple regions represent low-energy conformations, green indicates meta-stable states, and yellow highlights high-energy conformations.
Fig 17.
Comparison for the binding free energy terms applied, PD-L1/linalool (a) and PTEN/linalool (b).
Fig 18.
SF-767 glioblastoma cell line viability after treatment lianlool (green) and LN@AgNPs (yellow) was assessed using the MTT assay and results are presented as mean ± 95% confidence interval (CI) with error bars.
Statistical significance was determined using two-way ANOVA followed by Tukey’s post hoc analysis, with significance levels indicated as ns (not significant), p < 0.05, p < 0.01, p < 0.001, and p < 0.0001.
Fig 19.
Use of IC50 values to parameterize concentration–effect curves.
A plot of the concentration–response curve for Linalool (a). A plot of the concentration–response curve for LN@AgNPs (b).
Fig 20.
Relative gene expression levels of PD-L1 (green) and PTEN (red) in cells treated with linalool and LN@AgNPs, analyzed using RT-PCR.
Data are presented as mean ± 95% confidence interval. Statistical significance was assessed using a two-way ANOVA, followed by a Tukey’s post hoc test to compare each treatment group with the control.