Table 8.
Drug target distribution in different pathway databases
| Database | #drug target in database | #Non-drug target in database | % of proteins in database that are drug targets | % of all drug targets with pathway info | % of all non-drug targets with pathway info |
|---|---|---|---|---|---|
| UniProt (all prots) |
1953 |
113741 |
1.69 |
83.97 |
8.33 |
| PID |
394 |
1261 |
23.81 |
20.17 |
1.11 |
| Reactome |
1262 |
4215 |
23.04 |
64.62 |
3.71 |
| KEGG | 1414 | 7473 | 15.91 | 72.40 | 6.57 |
84% of all drug-targets under study have pathway information. KEGG includes the highest number of drug targets (72%), followed by Reactome (65%). The number of non-drug targets in each database is small compared to all non-drug targets in UniProt, suggesting that pathways might be enriched for drug targets. Only 1.69% of UniProt proteins are drug targets while they constitute 15.9%-23.8% of pathway databases. This observation is confirmed by comparing the percentages of drug targets and non-drug targets in UniProt to those per database: KEGG, for example, contains 72.4% of all drug targets but only 6.6% of all non-drug targets found in UniProt.