Fig 1.
Two dimensional molecular structure of the three anti-cancer drugs: midostaurin, enzastaurin and gefitinib.
Fig 2.
Structure visualization of cancer signaling target proteins S100A8 (1MR8), and EGFR tyrosine kinase domain (2GS2) retrieved from Protein Data Bank.
Surface representation of the two PDB structures used for docking analysis. Figure made using PyMol. (1) MR8 chain A (green) + chain B (cyan) (2) 2GS2 chain (yellow), drug binding cavity in magenta.
Fig 3.
Hierarchical clustering and functional analysis of significantly differentially expressed genes in kidney cancer using Affymetrix Human ST 1.0 array and Partek Genomics suite (ver 6.6).
Table 1.
Differentially expressed significant genes in Kidney cancer.
Table 2.
Expression of S100A8 and EGFR in kidney cancer among Saudi patients (CEGMR dataset) and GEO dataset (GSE781, GSE6344 and GSE7023).
Fig 4.
Leukocyte Extravasation Signaling: Transcriptomic signatures of kidney cancer showed a significant activation in leukocyte extravasation signaling pathway.
Red represents overexpression and green underexpression.
Table 3.
Canonical pathways predicted by Ingenuity Pathway Analysis for significant genes differentially expressed in kidney cancer.
Fig 5.
2D plot of inhibitors with S100A8 and EGFR tyrosine kinase domain proteins interaction profile by DockingServer.
Ligand bond, non-ligand bond, hydrogen bond and their lengths are marked for midostaurin, enzastaurin and gefitinib. Where A, B, C shows interaction of S100A8 (1MR8) with the drugs, and E, F shows interaction of EGFR (2GS2) with midostaurin and gefitinib respectively.
Fig 6.
Interactions of ligand with the protein.
Red represents protein as cartoon; grey represents interacting side chain as cylinder; and green represents drug as ball and stick model.
Table 4.
Binding and interaction values for docking of S100A8 dimer and EGFR kinase domain with inhibitors (midostaurin, enzastaurin and gefitinib).