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Related Experiment Video

Updated: Jan 23, 2026

Molecular Evolution of the Tre Recombinase

Molecular Evolution of the Tre Recombinase

Published on: May 29, 2008

Decrypting protein surfaces by combining evolution, geometry, and molecular docking.

Chloé Dequeker¹, Elodie Laine¹, Alessandra Carbone^1,2

¹Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Paris, France.

|June 15, 2019

Summary

This summary is machine-generated.

This study introduces interacting regions to understand complex protein interactions and predict protein partners. The dynJET2 algorithm integrates multiple data sources for accurate predictions of protein binding sites.

Keywords:

binding site complete cross-docking evolutionary conservation interface prediction protein-protein interaction

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Area of Science:

Computational biology
Structural biology
Bioinformatics

Background:

Protein interactions are numerous and complex, involving surface usage and flexibility.
Understanding protein binding sites is crucial for deciphering biological functions.

Purpose of the Study:

To develop novel methods for predicting protein interacting regions and partners.
To account for protein surface multiplicity and molecular flexibility in interaction prediction.

Main Methods:

Introduced the concept of 'interacting regions' to capture multi-partner usage and interface variability.
Integrated evolutionary, physicochemical, and geometrical properties with complete cross-docking (CC-D) simulations.
Developed the dynJET2 algorithm for predicting interacting patches and partner numbers.

Main Results:

Predicted interacting patches accurately matched known interacting regions.
Demonstrated the complementary nature of different information sources (evolutionary, physical, geometrical).
Successfully predicted the number of partners for proteins in a new dataset.

Conclusions:

The dynJET2 algorithm effectively predicts protein interacting regions and partner numbers.
The proposed methods provide new insights into the complexity of protein-protein interactions.
The study offers valuable tools and data for the research community.