Towards inferring time dimensionality in protein-protein interaction networks by integrating structures: the p53 example

Abstract

Inspection of protein-protein interaction maps illustrates that a hub protein can interact with a very large number of proteins, reaching tens and even hundreds. Since a single protein cannot interact with such a large number of partners at the same time, this presents a challenge: can we figure out which interactions can occur simultaneously and which are mutually excluded? Addressing this question adds a fourth dimension into interaction maps: that of time. Including the time dimension in structural networks is an immense asset; time dimensionality transforms network node-and-edge maps into cellular processes, assisting in the comprehension of cellular pathways and their regulation. While the time dimensionality can be further enhanced by linking protein complexes to time series of mRNA expression data, current robust, network experimental data are lacking. Here we outline how, using structural data, efficient structural comparison algorithms and appropriate datasets and filters can assist in getting an insight into time dimensionality in interaction networks; in predicting which interactions can and cannot co-exist; and in obtaining concrete predictions consistent with experiment. As an example, we present p53-linked processes.

Fig. 1. The concept figure presenting an overview of this work.

Fig. 2. Schematic representation of the PRISM algorithm.

Fig. 3. (A) The fragments of the p53 protein and the available crystal structures; (B) p53 DNA-binding domain interactions. Edges are colored according to the different binding sites; these contain both experimental and PRISM-predicted interactions.

Fig. 4. Predicted partners of the p53 DNA-binding domain (left panel), with representation of some in the complexed state (right panel).

Fig. 5. Conserved contacts of Cdk2, Chk1 and Crk with p53 DBD predicted with MAPPIS.

Fig. 6. The Mdm2–pRb complex predicted by PRISM and the E2F1–pRb complex available in the PDB. Mdm2 associates with pRb through the same region where E2F1 interacts.

Fig. 7. Predicted partners interacting at the pocket region of Mdm2. (A) Mdm2–p53 complex taken from PDB. (B) Possible partners predicted by PRISM.

Fig. 8. Predicted partners of the Swib domain of Mdm2 (left panel) and representation of some of them in the complex state (right panel).