Drug Target Protein-Protein Interaction Networks: A Systematic Perspective

Abstract

The identification and validation of drug targets are crucial in biomedical research and many studies have been conducted on analyzing drug target features for getting a better understanding on principles of their mechanisms. But most of them are based on either strong biological hypotheses or the chemical and physical properties of those targets separately. In this paper, we investigated three main ways to understand the functional biomolecules based on the topological features of drug targets. There are no significant differences between targets and common proteins in the protein-protein interactions network, indicating the drug targets are neither hub proteins which are dominant nor the bridge proteins. According to some special topological structures of the drug targets, there are significant differences between known targets and other proteins. Furthermore, the drug targets mainly belong to three typical communities based on their modularity. These topological features are helpful to understand how the drug targets work in the PPI network. Particularly, it is an alternative way to predict potential targets or extract nontargets to test a new drug target efficiently and economically. By this way, a drug target's homologue set containing 102 potential target proteins is predicted in the paper.

Figure 1

Degree distributions of two types of proteins. The inset is the overall view of both distributions. Drug targets and common proteins are following the well-known power law just with different parameters. The highest degree of the drug targets is 103 compared to 667 in PT. It indicates that the drug targets are not the hubs.

Figure 2

Distribution of normalized betweenness of drug targets proteins and pending test proteins. The betweenness of drug target proteins is lower than others. The distributions of the two types of proteins are similar. The inset shows there are few changes between the betweenness distributions of the original PPI and the new PPI with the known drug targets removed.

Figure 3

Distribution of eigenvector centrality. Drug targets and other proteins have the same distribution of the eigenvector centrality. The inset shows that the amount of changes on the eigenvector centrality after removing the drug targets is negligible. But the average eigenvector centrality of drug targets is not lower than others although the results of the analysis on degree and betweenness implied the drug targets are not the hubs.

Figure 4

Distribution of average distance. The known drug target's distribution of average distance is similar with common proteins. The inset shows there are few changes on the average distance after the protein targets were removed from the PPI network.

Figure 5

The distribution of eccentricity. It shows that the difference in eccentricity between drug targets and others is not remarkable although most targets' eccentricity is 9 and the normal proteins' eccentricity is 9 and 10. However, the eccentricity is changed apparently after removing the drug targets from PPI networks.

Figure 6

The distribution D(i) and PT(i) of the communities. There are 15 main protein communities consisting of 11,099 proteins detected in PPI. The majority of the drug targets are in the three communities 5, 10, and 13.

Figure 7

rd(i) of the communities. When rd(i) > 1, it indicates that the community i tends to be a target-like community. Similarly, if rd(i) < 1, the community i is closer to nondrug target proteins.

Figure 8

The full view of communities 5 and 10.

Figure 9

17-core subnetwork of the drug targets PPI network. As shown in four ego networks of the known drug targets (PSMD1, TOP2A) and normal proteins (EWSR1, ATXN1), the neighbors of a drug target are less but those neighbors have higher degree than normal proteins. It implies a very important drug protein's reaction mechanism, that is, the drug target protein's interaction with most high connective proteins, though few of them are the hubs as important bridges of the PPI network.

Figure 10

rc_D(k) and rc_PT(k) of the drug targets PPI networks. The drug target proteins are mainly in the 6-, 9-, 12-, 16-, and 18-core subnetworks, while the pending test proteins that represent normal proteins are evenly distributed across all core subnetworks.