Coarse-grained and atomic resolution biomolecular docking with the ATTRACT approach

Area of Science:

• Computational biology
• Structural bioinformatics
• Protein structure prediction

Background:

• Protein-protein interactions are crucial for biological processes.
• Accurate prediction of protein complex structures is a significant challenge in structural biology.

Purpose of the Study:

• To evaluate the performance of the ATTRACT protein-protein docking program in recent CAPRI rounds.
• To assess the effectiveness of a combined rigid body minimization and elastic network mode optimization approach.

Main Methods:

• Utilized the ATTRACT program for protein-protein docking predictions across CAPRI rounds 38-45.
• Employed a hybrid method combining rigid body minimization with simultaneous optimization using elastic network modes.
• Evaluated the approach on a large benchmark dataset.

Main Results:

• Achieved acceptable or better quality predictions for 11 out of 16 targets (~70%) in CAPRI.
• Successfully predicted peptide-protein and carbohydrate-protein interactions.
• Demonstrated modest improvements in docking performance compared to rigid docking alone.

Conclusions:

• The ATTRACT program shows robust performance in predicting protein-protein complex structures.
• The combined optimization strategy offers a potential improvement over traditional rigid docking.
• Further refinements in scoring and flexible refinement steps could enhance docking accuracy.