Analysis of Protein-Protein Interactions for Intermolecular Bond Prediction

Abstract

Protein-protein interactions often involve a complex system of intermolecular interactions between residues and atoms at the binding site. A comprehensive exploration of these interactions can help reveal key residues involved in protein-protein recognition that are not obvious using other protein analysis techniques. This paper presents and extends DiffBond, a novel method for identifying and classifying intermolecular bonds while applying standard definitions of bonds in chemical literature to explain protein interactions. DiffBond predicted intermolecular bonds from four protein complexes: Barnase-Barstar, Rap1a-raf, SMAD2-SMAD4, and a subset of complexes formed from three-finger toxins and nAChRs. Based on validation through manual literature search and through comparison of two protein complexes from the SKEMPI dataset, DiffBond was able to identify intermolecular ionic bonds and hydrogen bonds with high precision and recall, and identify salt bridges with high precision. DiffBond predictions on bond existence were also strongly correlated with observations of Gibbs free energy change and electrostatic complementarity in mutational experiments. DiffBond can be a powerful tool for predicting and characterizing influential residues in protein-protein interactions, and its predictions can support research in mutational experiments and drug design.

Keywords: DiffBond; bond classifier; intermolecular bond prediction; ionic bond identificatio.

Figure 1

Sidechain visualization of Arg59 on Barnase (green) and Glu76 on Barstar (teal). Arg59 and Glu76 are within 4 Å and are oppositely charged amino acids, so they are predicted to form a salt bridge by DiffBond.

Figure 2

Intersection using CSG involves: (a) Two proteins with oppositely charged electrostatic fields. (b) When the proteins are in complex, the oppositely charged fields overlap forming an intersection region shown in orange. (c) The intersection region represents the degree to which the field of one protein complements the field of the other.

Figure 3

Effect of Nullification on Barnase-Barstar. (a) Wildtype Barnase electrostatic surface at isopotential of +1 kT/e. (b) Barnase nullified at residue 59, electrostatic surface at isopotential of +1 kT/e. (c) Overlap of wildtype (transparent yellow) and nullified Barnase (green) surfaces. (a–c) The red square encompasses the main difference in isopotential surface due to nullification. (d) Wildtype Barnase (blue) in complex with Barstar (transparent yellow).

Figure 4

Comparison of $∆∆G$ when a bond is broken and when a bond remains intact for (a) Ionic bonds, (b) Salt Bridges, and (c) Hydrogen bonds. Each bond compared using normalized average $∆∆G$ values for Barnase-Barstar (1BRS) and Rap1a-raf (1C1Y). (*) indicates that no bonds were predicted by DiffBond in those groups. Rap1a-raf hydrogen bond had only one bond broken prediction, so no intervals were calculated.

Figure 5

Comparison of interface intersection volume changes when a bond is broken and when a bond remains intact for (a) Ionic bonds and (b) Salt Bridges. Each bond compared using volumes calculated from VASP-E for Barnase-Barstar (1BRS) and Rap1a-raf (1C1Y).