Structural Biology/Biochemistry Seminar
Tuesday September 10, 2013
Kasha Laboratory, Room 112
11:15 AM
“Impact of cancer mutations on protein binding and activityā€¯

Dr. Anna Panchenko
Computational Biology Branch
National Center for Biotechnology Information
Host: Dr. Peter Fajer

Cellular regulatory mechanisms provide a sensitive, specific and robust response to external stimuli. Many signaling pathways involve a dense network of protein-protein interactions and hence the analysis of protein interactions, networks, and pathways is essential for understanding biological mechanisms on a molecular level.

We are interested in problems of biomolecular recognition, mechanisms of evolution of protein interactions and the role of these interactions in cellular regulatory mechanisms. We apply methods of computational biophysics and bioinformatics to explore protein binding principles and to predict binding interfaces, interaction partners and the effects of disease mutations.

ABSTRACT OF TALK: Impact of cancer mutations on protein binding and activity

The substitutions of only one residue in a protein sequence, so-called missense mutations, can be related to many pathological conditions and may influence susceptibility to disease and drug treatment. However, the mechanisms and effects of mutations on proteins and biomolecular interactions remain unclear. I will describe a new framework that uses experimental evidence on structural complexes, the atomic details of binding interfaces and evolutionary conservation to map the set of human protein-biomolecular interactions. To decipher the impact of missense cancer mutations on protein interactions, we map mutated genes/proteins on human protein interactome and estimate the changes in binding energy for glioblastoma mutations. This analysis allows us to stratify cancer-related interactions, identify potential driver genes, and propose additional cancer biomarkers. To understand the molecular mechanisms of aberrant activation of receptor tyrosine kinases in cancer, we further analyze the effects of single and double cancer mutations on the stability of kinase active and inactive states. We draw important conclusions about the relationship between the frequency of mutations and their activating effect.