Optimal selection of suitable templates in protein interface prediction.

Area of Science:

• * Computational biology and bioinformatics.
• * Structural biology and protein interactions.
• * Molecular modeling and drug discovery.

Background:

• * Accurate protein-protein interface classification aids functional studies and drug design.
• * Template-based prediction is effective but challenged by low sequence identity and diverse binding sites in superfamilies like the immunoglobulin superfamily (IgSF).
• * Identifying suitable templates for IgSF proteins is difficult due to shared structural homology but low sequence identity.

Purpose of the Study:

• * To develop a robust computational approach for predicting protein-protein interfaces within the immunoglobulin superfamily (IgSF).
• * To enhance the accuracy of interface prediction by leveraging evolutionary profiles and hierarchical clustering.
• * To provide residue-level predictions and confidence scores for IgSF protein complexes.

Main Methods:

• * Generation of template-specific evolutionary profiles using a mutual information-based approach.
• * Hierarchical clustering of query proteins with known IgSF templates based on residue conservation scores.
• * Refinement of initial interface predictions through extensive docking simulations.
• * Development of a confidence assessment system for prediction results.

Main Results:

• * The developed method achieved an average F-score of 0.64 and a median F-score of 0.78 on 51 IgSF proteins.
• * Removing low and medium confidence predictions significantly improved performance, with average and median F-scores reaching 0.8 and 0.81, respectively.
• * Residue-level interface predictions, protein complex models, and confidence measurements were generated for IgSF singletons.

Conclusions:

• * The novel method effectively predicts challenging protein-protein interfaces in the IgSF, outperforming previous approaches.
• * The confidence scoring system allows for filtering and enhances the reliability of predictions.
• * This work provides valuable tools for functional characterization and rational drug design targeting IgSF proteins.