Speaker
Prof.
Martin Weigt
(Université Pierre et Marie Curie)
Description
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 to link this variability (easy to observe) to
structure (hard to obtain), i.e. to infer directly co-evolving
residue pairs which turn our 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.
Primary author
Prof.
Martin Weigt
(Université Pierre et Marie Curie)
