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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...

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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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Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
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Related Experiment Video

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A Rapid and Quantitative Fluorimetric Method for Protein-Targeting Small Molecule Drug Screening

A Rapid and Quantitative Fluorimetric Method for Protein-Targeting Small Molecule Drug Screening

Published on: October 16, 2015

Quantitative metrics for drug-target ligandability.

Sinisa Vukovic¹, David J Huggins²

¹Department of Physics, Cavendish Laboratory, University of Cambridge, 19 JJ Thomson Avenue, Cambridge CB3 0HE, UK.

Drug Discovery Today

|March 10, 2018

Summary

Ligandability, a key factor for drug development, can be quantified using a novel metric balancing effort and reward. This approach aids in predicting the tractability of new drug targets.

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Published on: September 26, 2025

Area of Science:

Drug discovery and development
Computational chemistry
Pharmacology

Background:

Ligandability is essential for determining a drug target's druggability.
Predicting ligandability is simpler than predicting pharmacodynamics and pharmacokinetics.
A quantitative metric for ligandability is needed.

Purpose of the Study:

To introduce and evaluate a metric for quantifying ligandability from experimental data.
To assess ligandability of known drug targets using the proposed metric.
To guide systematic improvement of computational ligandability predictions.

Main Methods:

Reviewing existing literature on ligandability and druggability.
Developing a metric based on effort-reward balance.
Applying the metric to well-studied drug targets.

Main Results:

The proposed metric quantifies ligandability based on experimental data.
Evaluation across diverse drug targets provides insights into their ligandability.
The metric offers a framework for assessing the balance between effort and reward in drug development.

Conclusions:

The developed metric provides a quantitative measure of ligandability.
This metric can systematically enhance computational predictions for novel drug targets.
Predicting tractability of new targets is feasible using this approach.