Inferring Interaction Partners and Evolutionary Constraints from Protein Sequences

BIOENGINEERING SEMINAR
 
Abstract:
Proteins and multi-protein complexes play crucial roles in our cells. The amino-acid sequence of a protein encodes its function, including its structure and its possible interactions. In evolution, random mutations affect the sequence, while natural selection acts at the level of function. Hence, shedding light on the sequence-function mapping of proteins is central to a systems-level understanding of cells, and has far-reaching applications in synthetic biology and drug targeting. The current explosion of available sequence data has inspired data-driven approaches to discover the principles of protein operation. At the root of these approaches is the observation that amino-acid residues which possess related functional roles often evolve in a correlated way.

First, I will present two novel methods to predict protein-protein interactions from sequence data. One method is based on the maximum-entropy inference approach that has already allowed to infer protein structures from sequences, and the other one is based on information theory. These methods accurately identify which proteins are functional interaction partners among the paralogous proteins of two families, starting from sequence data alone. They also provide signatures of the existence of interactions between protein families.

Then, I will propose a simple interpretation of the origin of the "sectors" of collectively correlated amino acids that have been discovered in several protein families through statistical analyses of sequence alignments. I will show that selection acting on any functional property of a protein, represented by an additive trait, can give rise to such a sector. 

Bio:
CNRS Researcher in the Laboratoire Jean Perrin at Sorbonne Université in Paris, France.
Until January 2016: Postdoctoral Research Fellow in the Biophysics Theory Group of the Lewis-Sigler Institute for Integrative Genomics at Princeton University, in Princeton, NJ, USA.
2012: PhD at the Complex Matter and Complex Systems laboratory of Université Paris-Diderot, Paris 7 and CNRS, in Paris, France.


Zoom link for attending remotely:  https://zoom.us/meeting/567807442