The change of protein intradomain mobility on ligand binding: is it a commonly observed phenomenon?

Abstract

Analysis of changes in the dynamics of protein domains on ligand binding is important in several aspects: for the understanding of the hierarchical nature of protein folding and dynamics at equilibrium; for analysis of signal transduction mechanisms triggered by ligand binding, including allostery; for drug design; and for construction of biosensors reporting on the presence of target ligand in studied media. In this work we use the recently developed HCCP computational technique for the analysis of stabilities of dynamic domains in proteins, their intrinsic motions and of their changes on ligand binding. The work is based on comparative studies of 157 ligand binding proteins, for which several crystal structures (in ligand-free and ligand-bound forms) are available. We demonstrate that the domains of the proteins presented in the Protein DataBank are far more robust than it was thought before: in the majority of the studied proteins (152 out of 157), the ligand binding does not lead to significant change of domain stability. The exceptions from this rule are only four bacterial periplasmic transport proteins and calmodulin. Thus, as a rule, the pattern of correlated motions in dynamic domains, which determines their stability, is insensitive to ligand binding. This rule may be the general feature for a vast majority of proteins.

FIGURE 1

The basic scheme of the HCCP algorithm.

FIGURE 2

The maximal difference in p_dom between the alternative structures of the same protein Δp_dom obtained for 157 studied proteins. (a) The diagram in which the studied proteins are sorted by Δp_dom in ascending order. (b) The distribution of these proteins according to their Δp_dom values.

FIGURE 3

Dependence of the p_dom on GNM cutoff radius r_c for two representative proteins: LAOBP (a) and malate dehydrogenase (b). In panel a, the gaps between the open and closed forms are shown by arrows and the corresponding Δp_dom values are indicated. PDB identifiers of different conformations are indicated. Last character indicates the chain (“0” means that only one chain is present).

FIGURE 4

The comparison of RMSD (RMSD_max) of C_α atoms between alternative structures of the same protein with the largest Δp_dom. The data are for 157 studied proteins. Those proteins for which ligand-binding is the reason for large Δp_dom values are indicated by open circles. The reason for large Δp_dom for other proteins is the existence of long unstructured loops, swapped domains, missed segments, etc. Linear fit is shown by the dashed line.

FIGURE 5

The comparison of RMSD (RMSD_max) of C_α atoms between alternative structures of the same protein with the largest Δp_dom and the largest pairwise C_α RMSD between individual domains of alternative structures (RMSD_dom) of these proteins. The data are for 157 studied proteins. Those proteins for which ligand-binding is the reason for large Δp_dom values are indicated by open circles. Linear fit is shown by the dashed line. The proteins discussed in the text are marked by arrows.

FIGURE 6

The proteins with significant Δp_dom caused by the ligand binding. Two structures, which correspond to the largest value of Δp_dom, are shown for each protein. The dynamic domains, computed by HCCP, are marked by black and white coloring. The ligands are shown in the space-fill representation. The structure of the GlnBP protein is visually very similar to LAOBP and thus not shown. The PDB codes for each conformation are given in the parentheses. The last letter of the code indicates the chain used. The underscore sign (_) means that the PDB entry contains a single chain.