Modeling CAPRI targets 110-120 by template-based and free docking using contact potential and combined scoring...

Area of Science:

• Computational biology
• Structural bioinformatics
• Protein-protein interactions

Background:

• The Critical Assessment of Predicted Interactions (CAPRI) and Critical Assessment of Structure Prediction (CASP) experiments are crucial for evaluating protein structure and complex prediction methods.
• Accurate prediction of protein-protein interactions and interfaces is essential for understanding biological processes and drug discovery.

Purpose of the Study:

• To analyze and improve template-based and free docking predictions in the CASP12/CAPRI37 round.
• To develop and benchmark a novel scoring function for template-based protein docking.

Main Methods:

• Development and benchmarking of a new scoring function for template-based docking using the Dockground resource.
• Application of the scoring function to CASP12/CAPRI37 targets, complemented by analyses of oligomeric states, biological functions, and interface relevance.
• Evaluation of free docking performance and the utility of a newly developed contact potential for binding site detection.

Main Results:

• The new scoring function successfully discriminated incorrect docking predictions.
• Accurate interface models were built from inaccurate subunit models when a good docking template was available.
• Free docking proved sensitive to individual model quality, but a new contact potential detected approximate binding sites.

Conclusions:

• The developed scoring function enhances template-based docking accuracy and aids in biological assessment.
• Complementary use of structure- and sequence-based alignments is beneficial for comparative docking, especially for targets lacking sequence-homology templates.
• Further development is required for the scoring function to distinguish biological from crystal packing interfaces and to improve docking of alpha-helix bundles.