Network Pharmacology-Based Prediction of Mechanism of Shenzhuo Formula for Application to DKD

Table 3

Thirty key targets obtained by network topology analysis.

Serial number	Node	Degree	Closeness centrality	Betweenness centrality
1	PIK3CA	40	0.49508197	0.09370214
2	STAT3	40	0.5	0.0863086
3	AKT1	35	0.49025974	0.15311921
4	KNG1	33	0.44023324	0.06128185
5	VEGFA	33	0.49185668	0.06953442
6	JUN	32	0.48089172	0.07229449
7	MAPK3	30	0.4617737	0.02240476
8	MAPK1	30	0.4689441	0.06714477
9	EGF	27	0.4617737	0.0336672
10	EDN1	27	0.46604938	0.05180077
11	EGFR	26	0.44023324	0.01794429
12	JAK1	26	0.44940476	0.02254905
13	IL6	26	0.45209581	0.02532622
14	CXCL8	25	0.43768116	0.03191743
15	RELA	24	0.45757576	0.04035241
16	FN1	23	0.4351585	0.01464828
17	JAK2	23	0.44940476	0.01620852
18	CTNNB1	23	0.45481928	0.06488997
19	TNF	22	0.44281525	0.0272631
20	TGFB1	21	0.44281525	0.03270724
21	MMP9	20	0.40921409	0.03200512
22	CXCR4	19	0.41032609	0.01402652
23	TIMP1	19	0.41712707	0.00798146
24	MAPK14	19	0.44411765	0.01628416
25	BDKRB1	18	0.3994709	0.00725308
26	PIK3CB	18	0.40921409	0.00732155
27	MAPK8	18	0.42296919	0.03099697
28	ITGB3	18	0.42296919	0.01050834
29	CCR5	16	0.39841689	0.00592392
30	PLG	16	0.40266667	0.02168017