Background
Methods
Dataset
Similarity calculation of herb pairs and protein pairs
Herb pairs with similar efficacies indicate similar targets
Construction of herb-herb network and protein-protein network
Random walk on heterogeneous herb-target network to identify candidate targets
Experimental setting and evaluation
Shortest path analysis
Results
Overview of heNetRW
Network | Number of nodes | Number of edges | Average degree | Network density |
---|---|---|---|---|
Herb-herb network | 741 | 60,753 | 163.98 | 0.22 |
Protein-protein network | 4794 | 656,681 | 273.95 | 0.06 |
Heterogeneous herb-target network | 6716 | 740,887 | 220.63 | 0.03 |
Herb pairs with similar efficacies indicate similar targets
Target identification of herbs
Prediction simulation | Algorithm | Number of herbs | F1-score | Hit@1 (%) |
---|---|---|---|---|
NoTarget | PRINCE | 260 | 0.16±0.17 | 29.23 |
heNetRW | 261 | 0.28±0.20 | 50.57 | |
HalfTarget | PRINCE | 896 | 0.05±0.10 | 6.70 |
heNetRW | 896 | 0.59±0.33 | 75.78 |
Parameters tuning of heNetRW
Case study
Simulation | Herb | Number of Train targets | Number of test targets | Number of correct targets | Precision/recall /F1-score |
---|---|---|---|---|---|
NoTarget | Rhizoma coptidis | 0 | 64 | 35 | 0.5469 |
Turmeric | 0 | 152 | 81 | 0.5329 | |
HalfTarget | Rhizoma coptidis | 32 | 32 | 24 | 0.75 |
Turmeric | 76 | 76 | 43 | 0.5658 |
Rhizoma coptidis | Turmeric | ||||
---|---|---|---|---|---|
Rank | Candidate Target | Score | Rank | Candidate Target | Score |
1 |
CASP3
| 0.4526 | 1 |
CASP3
| 0.2750 |
2 |
RELA
| 0.4109 | 2 |
RELA
| 0.2554 |
3 |
PTGS2
| 0.3834 | 3 |
PTGS2
| 0.2222 |
4 |
TNF
| 0.2988 | 4 |
TNF
| 0.1816 |
5 |
NOS2
| 0.2771 | 5 |
BCL2
| 0.1716 |
6 |
BCL2
| 0.2708 | 6 |
NOS2
| 0.1624 |
7 | CYP3A4 | 0.2325 | 7 |
BAX
| 0.1403 |
8 | SOD1 | 0.2132 | 8 |
TP53
| 0.1349 |
9 |
BAX
| 0.2096 | 9 |
JUN
| 0.1318 |
10 |
CASP9
| 0.1928 | 10 |
CYP3A4
| 0.1230 |
11 |
IL6
| 0.1846 | 11 |
SOD1
| 0.1182 |
12 |
JUN
| 0.1777 | 12 |
FOS
| 0.1165 |
13 |
CDKN1A
| 0.1701 | 13 |
CASP9
| 0.1158 |
14 |
TP53
| 0.1701 | 14 |
VEGFA
| 0.1141 |
15 |
IL1B
| 0.1658 | 15 |
IL6
| 0.1111 |
16 |
VEGFA
| 0.1612 | 16 |
CDKN1A
| 0.1106 |
17 |
FOS
| 0.1561 | 17 |
NFKBIA
| 0.0992 |
18 | ICAM1 | 0.1558 | 18 |
IL1B
| 0.0926 |
19 | HMOX1 | 0.1502 | 19 |
MMP9
| 0.0873 |
20 |
MAPK1
| 0.1358 | 20 |
ICAM1
| 0.0872 |
Rhizoma coptidis | Turmeric | ||||
---|---|---|---|---|---|
Rank | Candidate Target | Score | Rank | Candidate Target | Score |
1 |
PTGS2
| 0.0311 | 1 |
CASP3
| 0.0657 |
2 |
NOS2
| 0.0285 | 2 |
TNF
| 0.0619 |
3 |
BAX
| 0.0259 | 3 |
BCL2
| 0.0518 |
4 |
CASP9
| 0.0252 | 4 |
JUN
| 0.0438 |
5 |
CDKN1A
| 0.0238 | 5 |
VEGFA
| 0.0424 |
6 |
NFKBIA
| 0.0220 | 6 |
BAX
| 0.0400 |
7 |
FOS
| 0.0212 | 7 |
IL6
| 0.0390 |
8 |
CDK2
| 0.0203 | 8 |
MMP9
| 0.0355 |
9 |
VEGFA
| 0.0202 | 9 |
CASP9
| 0.0334 |
10 |
IL4
| 0.0178 | 10 |
AKT1
| 0.0326 |
11 |
BCL2L1
| 0.0160 | 11 |
CCND1
| 0.0302 |
12 | AKT1 | 0.0146 | 12 | CDK2 | 0.0296 |
13 |
HERC5
| 0.0143 | 13 |
MAPK1
| 0.0282 |
14 |
CDC2
| 0.0135 | 14 | CDK4 | 0.0269 |
15 |
EIF6
| 0.0132 | 15 |
XDH
| 0.0245 |
16 | MMP9 | 0.0130 | 16 |
SOD1
| 0.0241 |
17 | IL2 | 0.0126 | 17 |
PRKCB
| 0.0233 |
18 |
MPO
| 0.0121 | 18 |
CYP3A4
| 0.0213 |
19 |
EGFR
| 0.0120 | 19 |
VCAM1
| 0.0211 |
20 |
HIF1A
| 0.0118 | 20 |
MYC
| 0.0202 |