Human cancer protein-protein interaction network: a structural perspective

Abstract

Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network). The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%). We illustrate the interface related affinity properties of two cancer-related hub proteins: Erbb3, a multi interface, and Raf1, a single interface hub. The results reveal that affinity of interactions of the multi-interface hub tends to be higher than that of the single-interface hub. These findings might be important in obtaining new targets in cancer as well as finding the details of specific binding regions of putative cancer drug candidates.

Figure 1. Representation of PIN,SPIN and iSPIN.

In A) proteins in PIN are represented; the ones colored black have PDB IDs and the ones colored blue do not have PDB IDs. In B) The proteins with PDB ID and interactions among them constitutes SPIN. In C) The proteins with PDB ID and protein interface information and their interactions constitutes iSPIN. The zoomed representations give idea about what type of information each network contains; PIN is an abstract representation of interactions, SPIN is a subset of PIN with information of PDB IDs, and iSPIN contains the most detailed information including protein interfaces into network. All the networks are visualized using Cytoscape .

Figure 2. Topological properties of SPIN.

(A) Degree distribution of proteins, R² = 0.914 for power law fit (B) Average clustering coefficient (C) Topological coefficients (D) Shortest path length distribution.

Figure 3. Molecular function and biological process distribution of cancer & non-cancer genes.

(A) Molecular distribution of genes in SPIN (B) Molecular distribution of genes in PIN (C) Biological process distribution in SPIN (D) Biological process distribution in PIN.

Figure 4. Sub-networks in SPIN.

SPIN is clustered into sub-networks, proteins are classified into four categories; cancer-hub, noncancer-hub, cancer-nonhub, noncancer-nonhub are displayed in purple, green, blue and white color, respectively. Over-represented molecular functions (if any) are shown for each sub-network.

Figure 5. Essentiality of different categories of proteins.

A) Essentiality in PIN. B) Essentiality in SPIN. C) Essentiality in random network.

Figure 6. Essentiality of proteins classified as cancer-hub, cancer-nonhub and non-cancer-hub in SPIN, PIN and random network.

Figure 7. Representation of iSPIN.

The nodes colored in green and red are multi-interface hubs and single-interface hubs, respectively. In the zoomed representation, the interactions of a multi-interface hub; ERBB3 is displayed.

Figure 8. Representation of ERBB3-NRG1 interaction schematically.

The interactions are visualised using VMD A) ERBB3 (1m6b_A) and NRG1 (1hae_A) are shown as newcartoon diagram in blue and red color, respectively. The transparent surface represents the interface region. The labeled residues (represented by their Cα atoms) of 1hae_A are reported to be critical for binding in a previous work ; i.e. when they are mutated to alanine, the binding affinity for ERBB3 was significantly reduced. B) HER3 (blue) – pertuzumab heavy chain (yellow) is shown. Pertuzumab shares the same interface with NRG1 (see “An inhibitor affecting Erb signaling pathway: pertuzumab” section).

Figure 9. Ribbon diagram and interface representation of ERBB3 interactions with PLCG1, EPOR and ACK1.

ERBB3 (1m6b_A), PCLG1 (1hsq_A), EPOR (1eer_B) and ACK1 (1u46_A) are colored in blue, red, pink and orange respectively. Interface residues are shown as spheres. (A) ERBB3-PLCG1 interaction. (B) ERBB3-EPOR interaction. (C) ERBB3-ACK1 interaction.

Figure 10. Ribbon diagram and interface representation of RAF1 interactions with YWHAZ, MAP2K2 and CDC25A.

RAF1 (1c1y_B), YWHAZ (1qja_A), MAP2K2 (1s9i_A) and CDC25A (1c25_A) are colored in blue, red, cyan and purple respectively. (A) RAF1-YWHAZ interaction. (B) RAF1-MAP2K2 interaction. (C) RAF1-CDC25A interaction. Interaction interfaces of RAF1 through YWHAZ, MAP2K2 and CDC25A are highly overlapping; the interactions are mutually exclusive.

Figure 11. Flowchart representation of the method of mapping interactions to 3D structures and generating iSPIN.

The method is applied for all the interactions in the human interactome (PIN).