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Figure 1. Principal component analysis
Figure 1. Principal component analysis
Pincipal component analysis (PCA) shows clear separation between the CB-839-treated group (red) and the control group (green) based on metabolomic profiles. Each point represents an individual sample, and shaded ellipses indicate 95% confidence intervals for each group. The first principal component (PC1) accounts for 97.4% of the variance, while the second component (PC2) explains 1.5%, indicating that most of the variation is captured along PC1.
This clear separation suggests that CB-839 treatment induces a substantial shift in the metabolic landscape, resulting in distinct metabolic profiles between the two conditions
Figure 2. Hierarchical clustering heatmap
Figure 2. Hierarchical clustering heatmap
Hierarchical clustering analysis demonstrates that CB-839-treated samples (purple) and control samples (green) form distinct clusters, reflecting systematic differences in their metabolic profiles. The color scale represents relative metabolite abundance, with red indicating higher and green indicating lower intensity. The grouping pattern indicates high intra-group similarity and clear inter-group separation, suggesting that CB-839 treatment induces consistent and measurable alterations in metabolite abundance across samples.
Figure 3. Changes in key metabolites following CB-839 treatment
Figure 3. Changes in key metabolites following CB-839 treatment
Bars represent the log2 fold changes of selected metabolites in CB-839-treated group relative to control.
Positive values indicate increased abundance, while negative values indicate decreased levels following treatment.
Figure 4. Metabolites set enrichment analysis
Figure 4. Metabolites set enrichment analysis
Metabolite set enrichment analysis (MSEA) results for selected pathways following CB-839 treatment.
Shown are the enrichment scores (ES), normalized enrichment scores (NES), and key contributing metabolites (Lead_metabolites) for each pathway.
One-carbon metabolism and glutathione synthesis showed positive enrichment trends, with lead metabolites such as homocysteine, S-adenosylhomocysteine, and gamma-glutamylcysteine contributing most strongly.
In contrast, the TCA cycle showed a negative enrichment score, indicating a relative reduction in downstream metabolites.
Figure 5. Schematic diagram of the metabolite set enrichment analysis
Figure 5. Schematic diagram of the metabolite set enrichment analysis
Figure 6. X-ray crystal structure of GLS1-inhibitor complex
Figure 6. X-ray crystal structure of GLS1-inhibitor complex
GLS1 exists as either a dimer or a tetramer. The dimer is known to be inactive while the tetramer shows the catalytic activity. Recent X-ray protein crystals revealed the allosteric binding pocket of those inhibitors. Especially, GLS1-BPTES (5UQE) and GLS1-CB-839 (5JYO) shows the binding modes of those inhibitors. In the co-crystal structures, those inhibitors were located between the weak interfaces of the GLS1 tetramer (CB-839, Magenta). This allosteric inhibition site is far (18 angstrom) from its known active site, and the interaction with inhibitor fix the flexible loop thereby inhibiting the catalytic activity.
Figure 7. GLS1-inhibitor complex structure predicted by Chai-1
Figure 7. GLS1-inhibitor complex structure predicted by Chai-1
To predict the GLS1-CB-839/BPTES complex structures with Chai-1, extensive trials were conducted from monomer, dimer, and tetramer of the GLS1 in addition of inhibitors. Without any restraints or template, Chai-1 was able to successfully model the ligand to the hydrophobic pockets that was observed from various co-crystals. However, it failed to correctly recapitulate the mode of binding that was observed from X-ray crystallography. The addition of template/restraints in Chai-1 were unable to reproduce the observed X-ray structure.
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