Functional Protein Dynamics Directly from Sequences

The sequence correlations within a protein multiple sequence alignment are routinely being used to predict contacts within its structure, but here we point out that these data can also be used to predict a protein's dynamics directly. The elastic network protein dynamics models rely directly upon the contacts, and the normal modes of motion are obtained from the decomposition of the inverse of the contact map. To make the direct connection between sequence and dynamics, it is necessary to apply coarse-graining to the structure at the level of one point per amino acid, which has often been done, and protein coarse-grained dynamics from elastic network models has been highly successful, particularly in representing the large-scale motions of proteins that usually relate closely to their functions. The interesting implication of this is that it is not necessary to know the structure itself to obtain its dynamics and instead to use the sequence information directly to obtain the dynamics.

Automated summary

The sequence correlations in protein multiple sequence alignments can be used to predict protein dynamics. Elastic network protein dynamics models rely on contacts within the alignment and obtain normal modes of motion from the inverse of the contact map. Coarse-graining at the level of one point per amino acid allows for the direct connection between sequence and dynamics, making it possible to obtain protein dynamics using only the sequence information.