Identification of Motions in Membrane Proteins by Elastic Network Models and Their Experimental Validation

摘要: Identifying the functional motions of membrane proteins is difficult because they range from large-scale collective dynamics to local small atomic fluctuations at different timescales that are measure experimentally due hydrophobic nature these proteins. Elastic Network Models, and in particular their most widely used implementation, Anisotropic Model (ANM), have proven be useful computational methods many recent applications predict protein dynamics. These models based on premise biomolecules possess intrinsic mechanical characteristics uniquely defined by architectures. In ANM, interactions between residues close proximity represented harmonic potentials with a uniform spring constant. The slow mode shapes generated ANM provide valuable information global relevant function. its extension form ANM-guided molecular (MD), this coarse-grained approach augmented detail. results extensions can guide experiments thus speedup process quantifying Testing predictions accomplished through (a) direct observation studies structure biophysical probes, (b) perturbation by, e.g., cross-linking or site-directed mutagenesis, (c) studying effects such perturbations function, typically ligand binding activity assays. To illustrate applicability combined ANM-experimental testing framework proteins, we describe-alongside general protocols-here application rhodopsin, prototypical member pharmacologically G-protein coupled receptor family.