Protein Dynamics
Image Source: http://www.csb.pitt.edu/Faculty/bahar/images/prody.png
Proteins are always in motion. It may be “global” or “local” movements. The global motions, that are encoded in the architecture, arise due to changes during binding to a substrate, whereas local movements, that complement global motions, are seen as in the rearrangement of loops and adjustment of the side chains of the residues.
In the recent paper by Liu and Bahar, they have analyzed the systematically the “key residues that mediate structural dynamics”. They took 34 enzymes that are structurally and functionally varied and determine relative mobility for each residue, and the mutation propensity at that position. They used Gaussian Network Model (GNM), to study the global modes and relative mobility, and Shannon’s Mutual Information (MI), to identify co-evolved residues, to demonstrate
the importance of structural adaptability in sustaining functional dynamics of the enzyme notwithstanding sequence variations that confer specificity
So, what does all this mean? In one sentence, this paper says those residues in a protein that show least mobility (relative to others in the same protein) are most likely to be conserved. This also means that the correlation of the residue being less mobile and the residue’s degree of substitution may be the reason why we see a relatively small set of protein folds .
Take home points from this paper:
- conserved residues have minimal fluctuations in global modes
- increase in sequence variability is accompanied with increase in conformational mobility
- co-evolved residues are either involved in substrate binding or assist the residues involved in substrate binding
- finally, a mobility scale for the 20 amino acids that can used for understanding dynamics in other proteins.
Liu, Y., & Bahar, I. (2012). Sequence Evolution Correlates with Structural Dynamics Molecular Biology and Evolution, 29 (9), 2253-2263 DOI: 10.1093/molbev/mss097
Further reading:
- http://gor.bb.iastate.edu/anm/gnm_help.htm
- Haliloglu T, Seyrek E and Erman B. (2008) Prediction of Binding Sites in Receptor-Ligand Complexes with Gaussian Network Model Phys. Rev. Lett. 100, 228102
- Tozzini V. (2010) Minimalist models for proteins: a comparative analysis. Q Rev Biophys. Aug;43(3):333-71
Getting to know Structural Bioinformatics 
