Computational analysis and prediction of the binding motif and protein interacting partners of the Abl SH3 domain

Abstract

Protein-protein interactions, particularly weak and transient ones, are often mediated by peptide recognition domains, such as Src Homology 2 and 3 (SH2 and SH3) domains, which bind to specific sequence and structural motifs. It is important but challenging to determine the binding specificity of these domains accurately and to predict their physiological interacting partners. In this study, the interactions between 35 peptide ligands (15 binders and 20 non-binders) and the Abl SH3 domain were analyzed using molecular dynamics simulation and the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. The calculated binding free energies correlated well with the rank order of the binding peptides and clearly distinguished binders from non-binders. Free energy component analysis revealed that the van der Waals interactions dictate the binding strength of peptides, whereas the binding specificity is determined by the electrostatic interaction and the polar contribution of desolvation. The binding motif of the Abl SH3 domain was then determined by a virtual mutagenesis method, which mutates the residue at each position of the template peptide relative to all other 19 amino acids and calculates the binding free energy difference between the template and the mutated peptides using the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. A single position mutation free energy profile was thus established and used as a scoring matrix to search peptides recognized by the Abl SH3 domain in the human genome. Our approach successfully picked ten out of 13 experimentally determined binding partners of the Abl SH3 domain among the top 600 candidates from the 218,540 decapeptides with the PXXP motif in the SWISS-PROT database. We expect that this physical-principle based method can be applied to other protein domains as well.

Figure 1. The Correlations between Experimental and Predicted Relative Binding Free Energies of the 15 Binders of the Abl SH3 Domain

Figure 2. The Distributions of the Predicted Binding Free Energies for Binders and Non-Binders of the Abl SH3 Domain

Figure 3. The Preference of Residue Based on the Binding Free Energy Difference between the Mutated Peptide and the Template Peptide

The preference of residue at positions (A) P₋₅, (B) P₋₃, (C) P₀, and (D) P₃ based on the binding free energy difference between the mutated peptide and the template peptide APSYSPPPPP. In (D), the conformational entropy was included in the binding free energies.

Figure 4. The Electrostatic Potentials of the Peptide-Binding Interfaces for Four SH3 Domains

(A) 1bbz, (B) 1cka, (C) 1gbq, and (D) 1bb9. The scale of gradation was from −5 kT/e to +5 kT/e corresponding to red color to blue color. The electrostatic potentials of proteins were calculated using the Delphi module in Insight II. The salt concentration was set to 0.0 M because electrostatic potentials had small changes in the range of the experimental salt concentrations. The internal and external dielectric constants were set to 1 and 80, respectively. Electrostatic potentials were computed using a grid space of 0.5 Å with the focusing technique. The structures of the four SH3 domains were aligned using the Homology module in Insight II. The Tyr residue at P₋₃ in peptide APSYSPPPPP was shown in stick.

Figure 5. The Distribution of the Predicted Binding Free Energies Based on SPMFEP for Binders and Non-Binders