Change in allosteric network affects binding affinities of PDZ domains: analysis through perturbation response scanning

Abstract

The allosteric mechanism plays a key role in cellular functions of several PDZ domain proteins (PDZs) and is directly linked to pharmaceutical applications; however, it is a challenge to elaborate the nature and extent of these allosteric interactions. One solution to this problem is to explore the dynamics of PDZs, which may provide insights about how intramolecular communication occurs within a single domain. Here, we develop an advancement of perturbation response scanning (PRS) that couples elastic network models with linear response theory (LRT) to predict key residues in allosteric transitions of the two most studied PDZs (PSD-95 PDZ3 domain and hPTP1E PDZ2 domain). With PRS, we first identify the residues that give the highest mean square fluctuation response upon perturbing the binding sites. Strikingly, we observe that the residues with the highest mean square fluctuation response agree with experimentally determined residues involved in allosteric transitions. Second, we construct the allosteric pathways by linking the residues giving the same directional response upon perturbation of the binding sites. The predicted intramolecular communication pathways reveal that PSD-95 and hPTP1E have different pathways through the dynamic coupling of different residue pairs. Moreover, our analysis provides a molecular understanding of experimentally observed hidden allostery of PSD-95. We show that removing the distal third alpha helix from the binding site alters the allosteric pathway and decreases the binding affinity. Overall, these results indicate that (i) dynamics plays a key role in allosteric regulations of PDZs, (ii) the local changes in the residue interactions can lead to significant changes in the dynamics of allosteric regulations, and (iii) this might be the mechanism that each PDZ uses to tailor their binding specificities regulation.

Figure 1. The allosteric response ratio profiles and ribbon diagrams of hPTP1E and PSD-95.

The allosteric response ratio plots as a function of residue index for (A) hPTP1E PDZ2 (PDB entry: 3LNX) and (C) PSD-95 PDZ3 (PDB entry: 1BFE) along with the ribbon diagrams colored with respect to allosteric response ratio profiles (B and D). The key residues obtained from recent experimental studies are illustrated with red dots in these plots. The residues that give the highest mean square fluctuation response upon perturbation of binding pocket residues from PRS are displayed in the corresponding ribbon diagrams. The residues whose perturbation leads to a high response (χ_i>1.00 for hPTP1E and PSD-95) are red, whereas residues with a low response are shown in blue within a color spectrum of red-orange-yellow-green-cyan and blue. The residues that match with experimentally determined ones are shown in stick representation. In hPTP1E PDZ2, distal surface 1 (DS1) contains residues in the N terminal of β6 and the anti-parallel β strand formed by β4 and β5 (Val61, Val64 and Val85) and distal surface 2 (DS2) located next to helix α1 consists of residues Val40 and Ile41. The figures were drawn using PYMOL .

Figure 2. Intramolecular signaling pathways of hPTP1E and PSD-95 proposed by the PRS method.

(A) The most highly weighted pathway of hPTP1E follows through connections Ser 17 → Val22 → Gly25 → Arg31 → Ile35 → Val61 → Leu64 → Thr70 → Ala74 → Leu78 → Thr81 → Leu88. The residues Val22, Ala39, Ile52, Val61 and Leu66 correspond to the residues in the dynamical network determined by experimental study. (B) The most highly weighted pathway of PSD-95 is obtained through connections Ile314 → Ile327 → Ile338 → Ala347 → Leu353 → Val362→ Leu367 → His372 → Ile380 → Val386 → Glu396. (C) Interestingly, these two pathways are clearly different; the predicted allosteric pathway of PSD-95 has a more homogeneous distribution through N-terminal to C-terminal, whereas the pathway of hPTP1E seems more localized especially in regions of β1-β2 loop, β2 and β3 strands and the region of β5 strand and the α2 helix. Identified residues in a window size of 3 for the pathway are highlighted in the sequence.

Figure 3. Intramolecular signaling pathway for PSD-95 with truncated third alpha helix predicted by the PRS method.

We obtain the allosteric pathway for the truncated PSD-95 through connections Ile314 → Ile 327 → Glu334 → His372 → Ile380 → Ile388. However, the predicted allosteric pathway of full PSD-95 is different. The interactions specifically located in the α₁ helix predicted for the PSD-95 were lost after removal of the α3 helix.

Figure 4. The Perturbation Scanning Response (PRS) method.

(A) The free-body diagram of the central Cα atom of each sphere exhibits all of the pairwise interaction forces generated by the coordinating Cα atoms. In the absence of external forces acting on the system, each Cα atom must be in equilibrium under the action of interaction forces. (B) Under an external force applied on residue j, ΔF _j, the residues change their original locations (shown in black dots in Figure 4A) in space. (C) Algorithm displaying the procedure used for predicting allosterically linked residues using PRS.