Fig 1.
The Schematic diagram about the relationship between T2D and KC.
It highlights how hyperglycemia and IR in T2D contribute to oxidative stress, inflammation, and altered immune responses, which may promote KC development.
Table 1.
Data sources and descriptions.
Table 2.
A 2 × 2 contingency table for sKGs-set enrichment analysis.
Fig 2.
The Protein–protein interaction (PPI) network of shared DEGs (sDEGs) for T2D on KC to identify sKGs.
Orange colour nodes indicate the sKGs. This network highlights the complex interactions among sDEGs and identifies sKGs. Orange colour nodes indicate the sKGs. These sKGs may play critical roles in the molecular crosstalk linking T2D and KC pathogenesis.
Fig 3.
sKGs regulatory network (A) The JASPAR database-based on sKGs-TFs interaction network.
(B) The TarBase database-based on miRNA-sKGs interaction network. sKGs are shown as green color octagons in both A and B, while TFs and miRNAs are displayed as pink color hexagons in A and B, respectively.
Table 3.
GO-terms and KEGG pathways linked to T2D and KC that are noticeably enhanced.
Fig 4.
The Ramachandran plot illustrates the phi-psi angles for each residue of beta-tubulin.
The red areas show the most favorable phi-psi angle combinations. The white area shows an unfavorable phi-psi combination.
Fig 5.
The molecular docking score matrix displays strong binding affinities between target proteins and drug agents represented in red, while weak bindings are shown in green.
The X-axis represents the top 30 ranked drug agents (selected from 156), while the Y-axis shows the proposed receptors in order.
Fig 6.
To confirm the accuracy of the docking procedure, the co-crystallized ligand structure from the TFRC, and MCL1 (PDB ID: 60KD, and 3WIX) was re-docked.
As demonstrated, the docked ligand (red) closely resembles the crystallized ligand (purple) (RMSD = 1.398 Å, and 0.539 respectively).
Table 4.
Drug-likeness profiles of the top-ranked five drug molecules.
Table 5.
ADME and Toxicity (ADME/T) profile of the top-ranked five drug molecules.
Fig 7.
Some important docking results with the protein-ligand complexes.
Top-ranked four drug-target complexes highlighting their 3-dimension (3D) view and interacting residues. Complexes: (a) indicated MCL1-Imatinib, (b) NR2F1- Pazopanib hydrochloride, (c) SCRB1-Sorafenib, and (d) TFRC- Glibenclamide.
Fig 8.
Verification of the suggested shared key genes (sKGs) and potential therapeutic agents for T2D and KC through the literature review.
(A) Verification of the suggested T2D and KC-causing sKGs (B) Verification of the suggested drug-agents.