Direct coupling analysis: From sequence variability to protein (complex) structure prediction

08/01/2013 - Room C209 at 14:00 - External Seminar
Martin Weigt
(Université Pierre et Marie Curie)
Many families of homologous proteins show a remarkable degree of structural and functional conservation, despite their large variability in amino acid sequences. We have developed a statistical-mechanics inspired inference approach -- called direct coupling analysis -- to link this variability (easy to observe) to structure (hard to obtain). Using sequence information alone, we infer directly co-evolving residue pairs, which turn out to form native contacts in the folded protein with high accuracy. The gained information is used to guide tertiary and quaternary structure prediction. As a specific example, I will discuss the auto-phosphorylation complex of histidine kinases, which are involved in the majority of signal transduction systems in the bacteria. Only a multidisciplinary approach integrating statistical genomics, biophysical protein simulation, and mutagenesis experiments, allows us to predict and verify the - so far unknown - active kinase structure.
Hosted by: Marco Punta