PRODIGY: A Contact-based Predictor of Binding Affinity in Protein-protein Complexes

Area of Science:

• Structural biology
• Computational biology
• Biophysics

Background:

• Protein-protein interactions are fundamental to cellular processes.
• Accurate prediction of binding affinity is crucial for biological research and drug discovery.
• Existing methods for predicting binding affinity are limited in accessibility and ease of use.

Purpose of the Study:

• To introduce and describe the PRODIGY web server for predicting protein-protein complex binding affinity.
• To provide a user-friendly tool based on structural properties for affinity prediction.

Main Methods:

• Development of a binding affinity predictor based on the number of interfacial contacts in protein-protein complexes.
• Implementation of the predictor into a web server (PRODIGY).
• Validation of the predictor against experimental binding affinity data.

Main Results:

• The number of interfacial contacts serves as a robust descriptor of binding affinity.
• The PRODIGY predictor achieves high performance (Pearson's r = 0.73, RMSE = 1.89 kcal mol⁻¹).
• The PRODIGY web server offers a user-friendly interface for structural-based affinity prediction.

Conclusions:

• Structural properties, specifically interfacial contacts, can accurately predict protein-protein binding affinity.
• The PRODIGY web server provides an accessible and efficient tool for researchers.
• This tool facilitates biological system investigation and accelerates drug design efforts.