Tiliroside protects against diabetic nephropathy in streptozotocin-induced diabetes rats by attenuating oxidative stress and inflammation

Table 1 Predicted active sites for fibronectin, transforming growth factor-β1, interleukin-6, and tumor necrosis factor-α with the rank

No.	Biomarker name	Targets (PDB ID)	Rank	Score	Probability	Predicted active sites
1	Fibronectin	1MFN	1	2.74	0.084	HIS36, HIS37, ALA38, SER41, ARG46, ASN61, LEU62, ASN63, TYR68
2	TGF-β1	Q3UNK5	1	9.11	0.534	ARG277, THR282, ASN283, ASN292, CYS293, CYS294, TRP330, ASP333, GLN359, SER386, CYS387, CYS389, PRO99
3	IL-6	2 L3Y	1	10.37	0.597	ILE129, PHE132, ASN133, GLU135, VAL136, ILE142, LEU184, THR187, ARG188, THR27, VAL30, GLY31, LEU89, LEU90, LYS91, ILE92, SER93, LEU96
4	TNF-α	2TNF	1	8.36	0.491	PRO100, PRO102, TRP114, GLU116, LYS98, SER99

P2Rank is a machine learning tool that predicts ligand-binding sites in proteins using structural features, ranking them based on their likelihood of being active sites. TGF-β1: Transforming growth factor-β1; IL-6: Interleukin-6; TNF-α: Tumor necrosis factor-α.