Distinguishing structural and functional restraints in evolution in order to identify interaction sites

Area of Science:

• Computational biology
• Structural genomics
• Bioinformatics

Background:

• Structural genomics projects are generating vast amounts of protein 3D structure data.
• Predicting protein interaction sites is crucial for inferring protein function.
• Existing evolutionary conservation methods often fail to distinguish structural from functional constraints.

Purpose of the Study:

• To develop novel computational methods for predicting protein interaction sites.
• To differentiate evolutionary restraints arising from protein structure versus function.
• To leverage both sequence and structural information for improved functional site prediction.

Main Methods:

• Method 1: Compares observed amino acid conservation against predicted conservation based on local environment.
• Method 2: Uses information theory to identify positions with poor predictions from environment-specific substitution tables.
• Method 3: Identifies conserved residues by superposing 3D structures of homologous proteins.

Main Results:

• Developed three distinct methods to identify evolutionary restraints on protein sequence and structure.
• Integrated scores from these methods onto 3D protein structures to identify clusters of evolutionarily constrained residues.
• Successfully mapped interaction sites involved in various protein functions.

Conclusions:

• The proposed methods effectively identify functional interaction sites by analyzing evolutionary restraints.
• The approach successfully differentiates structural constraints from functional interaction constraints.
• This work provides a powerful tool for functional annotation in structural genomics.