Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at...

Area of Science:

• Structural biology
• Computational biology
• Systems biology

Background:

• Predicting protein-protein interactions (PPIs) structurally is crucial for understanding protein function, drug discovery, and genome-wide systems biology.
• Existing methods often struggle with large-scale, proteome-wide predictions at the structural level.

Purpose of the Study:

• To present PRISM (protein interactions by structural matching), a novel protocol for large-scale prediction of protein-protein interactions and assembly of protein complex structures.
• To enable functional annotation and pathway construction at the proteome scale.

Main Methods:

• PRISM employs a two-component approach: rigid-body structural comparisons against known protein-protein interfaces and flexible refinement using a docking energy function.
• It leverages structural similarity and evolutionary conservation of binding residue 'hot spots' to predict interacting residues.

Main Results:

• PRISM effectively predicts protein-protein interactions and assembles protein complex structures on a large scale.
• The method is based on the principle that distinct protein structures can interact through similar architectural motifs.

Conclusions:

• PRISM offers a powerful tool for structural systems biology, facilitating the prediction of protein function and the construction of cellular pathways.
• The protocol is implemented in Python, runs in a UNIX environment, and accepts PDB-formatted structures.