Protein Complex Structure Prediction With AlphaFold-Enhanced HDOCK in CAPRI Rounds 47-55

Area of Science:

• Structural Biology
• Computational Biology
• Bioinformatics

Background:

• Protein-protein interactions are fundamental to biological processes.
• Accurate prediction of protein complex structures is crucial for understanding cellular mechanisms and developing therapeutics.
• The Critical Assessment of PRediction of Interactions (CAPRI) experiment benchmarks computational prediction methods.

Purpose of the Study:

• To evaluate and refine computational strategies for predicting protein-protein complex structures.
• To assess the impact of integrating AlphaFold and advanced sampling techniques on prediction accuracy within the CAPRI framework.

Main Methods:

• Participation in CAPRI Rounds 47-55.
• Initial use of a hybrid docking strategy combining template-based and ab initio methods.
• Integration of AlphaFold into the prediction pipeline starting from CAPRI Round 53.
• Refinement of AlphaFold usage with enhanced sampling strategies from CAPRI Round 54 onwards.

Main Results:

• Continuous refinement of protein complex structure prediction strategies over multiple CAPRI rounds.
• Significant improvement in prediction accuracy observed after integrating AlphaFold and enhancing sampling methods in later CAPRI rounds.

Conclusions:

• The integration of AlphaFold, coupled with enhanced sampling, represents a significant advancement in computational protein complex structure prediction.
• These refined computational approaches are vital for advancing structural biology and drug discovery efforts.