HawkDock: a web server to predict and analyze the protein-protein complex based on computational docking and MM/GBSA

Area of Science:

• Structural biology
• Computational chemistry
• Bioinformatics

Background:

• Protein-protein interactions (PPIs) are crucial for cellular functions.
• Accurate prediction of PPI 3D structures remains a significant challenge.

Purpose of the Study:

• To develop HawkDock, a free web server for predicting and analyzing PPI structures.
• To integrate docking, scoring, and free energy decomposition for enhanced analysis.

Main Methods:

• Utilized the ATTRACT docking algorithm and the HawkRank scoring function.
• Integrated MM/GBSA free energy decomposition for key residue identification.
• Employed 3Dmol.js for molecular visualization.

Main Results:

• HawkDock demonstrated superior performance in structural modeling compared to ZDOCK 3.0.2.
• Successfully identified key residues in approximately 81.4% of predicted models and 95.4% of crystal structures.
• The server provides a multi-functional platform for PPI structure prediction and analysis.

Conclusions:

• HawkDock is a powerful and accessible tool for predicting PPI binding structures.
• It effectively identifies critical residues involved in protein-protein interactions.
• The web server is freely available at http://cadd.zju.edu.cn/hawkdock/.