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Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...

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Updated: May 12, 2026

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

Docking challenge: protein sampling and molecular docking performance.

Khaled M Elokely¹, Robert J Doerksen

¹Department of Medicinal Chemistry, School of Pharmacy, University of Mississippi, University, Mississippi 38677, USA.

Journal of Chemical Information and Modeling

|March 28, 2013

Summary

This summary is machine-generated.

Choosing the right molecular docking method is crucial for effective drug design. This study reveals that incorporating protein flexibility and water molecules significantly impacts docking accuracy, with optimal method selection yielding better predictions.

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Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

Area of Science:

Computational Chemistry
Drug Discovery
Structural Biology

Background:

Molecular docking is vital for predicting protein-ligand interactions in drug design.
Advancements in computational power enable more sophisticated docking algorithms, including those addressing protein flexibility and solvation.

Purpose of the Study:

To evaluate the impact of protein flexibility and active site water molecules on molecular docking effectiveness.
To determine the optimal docking strategies for accurate ligand pose prediction and ranking.

Main Methods:

Compared various docking algorithms with different approaches to protein flexibility (rigid, soft, flexible side chains, induced fit, multiple structures).
Assessed the influence of including active site water molecules on docking performance.
Evaluated docking accuracy for targets CHK1, ERK2, LpxC, and UPA.

Main Results:

Docking accuracy varied significantly across methods, ranging from 1% to 84%.
The choice of docking algorithm and the consideration of protein flexibility and water molecules are critical factors for success.
Different strategies yielded substantially different results for pose prediction and ligand ranking.

Conclusions:

No single docking method is universally optimal; strategic selection is paramount for virtual screening.
Further research into incorporating protein flexibility and solvation effects is essential for improving drug design computational tools.