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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...

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...

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...

The Equilibrium Binding Constant and Binding Strength

The Equilibrium Binding Constant and Binding Strength

The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:

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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked. In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...

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Related Experiment Video

Updated: Jun 2, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

PPDock: Pocket Prediction-Based Protein-Ligand Blind Docking.

Jie Du^1,2, Mingzhi Yuan^1,2, Ao Shen^1,2

¹Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai 200032, P. R. China.

Journal of Chemical Information and Modeling

|January 15, 2025

Summary

This summary is machine-generated.

We developed PPDock, a new deep learning method for protein-ligand docking. It improves accuracy and efficiency by first predicting the binding pocket before docking, outperforming existing blind docking techniques.

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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

Area of Science:

Computational chemistry
Drug discovery
Bioinformatics

Background:

Protein-ligand docking is vital for drug discovery but traditional methods struggle with accuracy and speed, especially in blind docking.
Deep learning has improved efficiency but often uses the whole protein, hindering pocket identification and generalization.

Purpose of the Study:

To propose a novel two-stage docking paradigm for improved protein-ligand docking.
To introduce PPDock, a new blind docking method incorporating pocket prediction.

Main Methods:

A two-stage approach: first predicting the protein binding pocket, then performing pocket-based docking.
Development of PPDock, a deep learning-based blind docking method utilizing the pocket prediction stage.

Main Results:

PPDock demonstrated superior performance across multiple evaluation metrics on benchmark datasets.
The method achieved high docking accuracy, enhanced generalization ability, and improved computational efficiency compared to existing techniques.

Conclusions:

The proposed two-stage docking paradigm, implemented in PPDock, effectively addresses limitations of current blind docking methods.
PPDock offers a promising advancement for accurate and efficient protein-ligand docking in drug discovery.