Modeling of transient protein-protein interactions relevant for cancer

Dnr:

SNIC 2017/1-161

Type:

SNAC Medium

Principal Investigator:

Björn Wallner

Affiliation:

Linköpings universitet

Start Date:

2017-05-01

End Date:

2018-05-01

Primary Classification:

10203: Bioinformatik (beräkningsbiologi) (tillämpningar under 10610)

Secondary Classification:

10610: Bioinformatik och systembiologi (metodutveckling under 10203)

Tertiary Classification:

10601: Strukturbiologi

Webpage:

Allocation

Abstract

Proteins are key players in virtually all biological events and accomplish their function as part of larger protein complexes. Unfortunately, compared to structure determination of individual proteins, structural characterization protein-protein interactions is much more difficult and is a major challenge in structural biology. For transient interactions it is even more difficult since the interactions only last for a short period of time they are hard to even detect, and thus even harder to study in molecular detail. Yet these transient interactions are key for regulating complex signaling networks that ultimately determine normal cell fate or drive abnormal cell growth leading to cancer. In this proposal, we suggest an integrative approach where we combine new technologies in proteomics with structural bioinformatics and computational modeling to study and understand highly dynamic transient interactions. We will develop computational tools to study protein-protein interactions involving disorder and tools that can be used to turn binary interaction maps into 3D models for further investigation and characterization. In particular, we will apply the developed tools to study interactions involving the oncoprotein Myc and transcription factor EBF1, both highly relevant in various cancers and for which we have first hand access to experimental data to understand how they interact with its partners at the molecular level to regulate and determine the development of disease.