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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.
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The Equilibrium Binding Constant and Binding Strength

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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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Ligand Binding and Linkage

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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...

Ligand Binding Sites

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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...

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Related Experiment Video

Updated: Aug 1, 2025

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

Who Binds Better? Let Alphafold2 Decide!

Julia K Varga¹, Ora Schueler-Furman¹

¹Microbiology and Molecular Genetics, Institute for Biomedical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, 9112001, Israel.

Angewandte Chemie (International Ed. in English)

|April 28, 2023

Summary

This summary is machine-generated.

Deep learning models like AlphaFold2 can now predict protein structures. A new method uses these models to identify which peptide binds a receptor with higher affinity, advancing protein-protein interaction studies.

Keywords:

Alphafold2 Binding Affinity Prediction Competitive Binding Deep Learning Peptide-Protein Interactions

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Area of Science:

Structural biology
Computational biology
Biophysics

Background:

Deep learning, particularly AlphaFold2, has enabled high-quality protein structure prediction.
Predicting protein-protein binding affinity remains a significant challenge in structural biology.

Purpose of the Study:

To develop a method for predicting peptide-receptor binding affinity using deep learning.
To leverage AlphaFold2's predictive power for understanding molecular interactions.

Main Methods:

Utilized AlphaFold2 to model receptor-peptide interactions.
Designed experiments where AlphaFold2 predicts binding when a receptor is presented with two competing peptides simultaneously.

Main Results:

AlphaFold2 successfully modeled the higher-affinity peptide within the receptor's binding site.
The model effectively excluded the lower-affinity peptide when both were present.

Conclusions:

This approach offers a novel computational strategy for assessing peptide-receptor binding affinities.
Deep learning tools can be effectively repurposed to address complex biological binding problems.