Speaker
Prof.
Chris Sander
(MSKCC)
Description
Attributes of living systems are constrained in evolution.
An alternative to the analysis of conserved attributes
('characters') is analysis of functional interactions
('couplings') that cause conservation. A quantitative theory
of evolutionary couplings may be widely applicable to
biological and technical evolution at different scales of
phenomena. In a particularly interesting application,
evolutionary couplings in proteins in the form of amino acid
pairwise covariation across a protein family, can be used to
computationally fold proteins, to predict oligomerization,
functional sites and paths, and functionally distinct
conformational states. For example, protein residue-residue
couplings, used as input to distance geometry and molecular
dynamics tools, are sufficient to generate good all-atom
models of proteins from different fold classes, ranging in
size from 50 to more than 300 residues. The evolutionary
couplings in proteins, extracted from the rich evolutionary
sequence record, provide insight into essential interactions
constraining protein evolution and, with the rapid rise in
large-scale sequencing, are likely to facilitate a
comprehensive survey of the universe of protein structures
by a combination computational and experimental technology.
Since March 2013, a web service at www.EVfold.org provides a
tool for the analysis of covaration in proteins with respect
to functional interactions and structural distance
constraints. Project leaders: Debora Marks, Harvard Medical
School and Chris Sander, Memorial Sloan-Kettering Cancer
Center. See http://bit.ly/tob48p (PDF) and www.evfold.org.
Primary author
Prof.
Chris Sander
(MSKCC)