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Ligand Binding Sites

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

Ligand Binding Sites

Ligand Binding Sites

Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...

Conserved Binding Sites

Conserved Binding Sites

Protein-protein Interfaces

Protein-protein Interfaces

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...

Protein-Protein Interfaces

Protein-Protein Interfaces

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Related Experiment Video

Updated: Apr 14, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

GalaxyCDock: Webserver for Covalent Protein-Ligand Binding Mode Prediction.

Sumin Lee¹, Nuri Jung¹, Hyeonuk Woo²

¹Department of Chemistry, Seoul National University, Seoul 08826, the Republic of Korea.

Journal of Molecular Biology

|April 12, 2026

Summary

We developed GalaxyCDock, a new web server for covalent protein-ligand docking. This tool accurately predicts binding modes for difficult-to-target proteins, improving drug discovery.

Keywords:

binding mode prediction covalent docking covalent protein–ligand complex

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Last Updated: Apr 14, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

Computational chemistry
Drug discovery
Structural biology

Background:

Covalent ligands offer unique therapeutic potential by targeting proteins resistant to conventional drugs.
Accurate prediction of covalent ligand binding is essential for drug specificity and safety.
Existing computational tools for covalent docking lack accessibility and precision.

Purpose of the Study:

To introduce GalaxyCDock, a novel web server designed for covalent protein-ligand docking.
To enhance the accuracy and accessibility of computational tools for covalent ligand binding prediction.
To provide a practical alternative for modeling covalent interactions in drug design.

Main Methods:

GalaxyCDock integrates efficient pose sampling from GalaxyDock2 with a deep learning scoring function, GalaxyDock-DL.
The server predicts binding modes for covalent ligands targeting specific proteins.
Performance was evaluated on standard and newly curated datasets.

Main Results:

GalaxyCDock demonstrated superior performance compared to established tools like AutoDock4 and DOCK6.
High accuracy was achieved in both re-docking (up to 80%) and cross-docking (up to 61%) tasks.
GalaxyCDock offers a viable alternative to advanced models when receptor structures are known.

Conclusions:

GalaxyCDock significantly advances covalent protein-ligand docking capabilities.
The developed tool addresses the limitations of current computational methods.
GalaxyCDock is publicly accessible, facilitating its use in drug discovery research.