Protein-protein docking with dynamic residue protonation states

Area of Science:

• Computational Biology
• Structural Biology
• Biochemistry

Background:

• Protein-protein interactions are crucial for cellular functions.
• Environmental factors, particularly pH, significantly influence these interactions by altering residue protonation states.
• Accurate modeling of these interactions requires accounting for pH-dependent effects.

Purpose of the Study:

• To develop a pH-sensitive protein-protein docking approach (pHDock).
• To dynamically sample side-chain protonation states of ionizable residues during docking.
• To improve the accuracy of protein complex structure prediction and binding affinity estimation.

Main Methods:

• Developed pHDock, a docking method incorporating on-the-fly sampling of protonation states for Asp, Glu, His, Tyr, and Lys.
• Evaluated pHDock performance against standard RosettaDock and control cases (fixed pH or protonation states).
• Incorporated backbone flexibility using conformational ensembles to further enhance results.

Main Results:

• pHDock successfully generated local docking funnels for approximately 50% of tested protein complexes, outperforming RosettaDock in 19 cases.
• Top-ranked pHDock structures exhibited lower interface RMSDs and better recovery of native contacts and hydrogen bonds compared to RosettaDock.
• The approach accurately predicted significant pH-dependent binding affinity changes for the Fc-FcRn complex.

Conclusions:

• pHDock offers a significant advancement in modeling pH-sensitive protein-protein interactions.
• The method improves the accuracy of protein docking and has potential applications in predicting binding affinity.
• This work contributes to the broader goal of simulating cellular interactions considering environmental factors and opens avenues for pH-sensitive protein design.