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Related Concept Videos

Ligand Binding Sites02:40

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 Sites02:40

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 and Linkage00:49

Ligand Binding and Linkage

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 the...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

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 the...
The Equilibrium Binding Constant and Binding Strength02:18

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:
Ligand-gated Ion Channels01:19

Ligand-gated Ion Channels

Ligand-gated ion channels are transmembrane proteins with a channel for ions to pass through and a binding site for a ligand. The channel opens only when a ligand attaches to the binding site.
Three Subfamilies of Ligand-gated Ion Channels
Ligand-gated ion channels fall into three subfamilies. The 'Cys-loop' includes the nicotinic acetylcholine receptors, γ-aminobutyric acid (GABA), glycine, and 5-hydroxytryptamine receptors. The second one is the 'Pore-loop' channels that include the...

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Related Experiment Video

Updated: May 26, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
10:29

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

Toward a Random Background for Ligand Optimization.

Xinyu Xu, Olivier Mailhot, Galen J Correy

    Biorxiv : the Preprint Server for Biology
    |May 25, 2026
    PubMed
    Summary
    This summary is machine-generated.

    Drug discovery ligand optimization is challenging. Unexpectedly, 11.2% of analogs with minor changes showed improved potency, but often had worse pharmacokinetics, revealing a complex optimization landscape.

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

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    Related Experiment Videos

    Last Updated: May 26, 2026

    Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
    10:29

    Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

    Published on: May 9, 2025

    Modeling Ligands into Maps Derived from Electron Cryomicroscopy
    09:30

    Modeling Ligands into Maps Derived from Electron Cryomicroscopy

    Published on: July 19, 2024

    Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
    08:49

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

    Published on: June 20, 2025

    Area of Science:

    • Medicinal Chemistry
    • Drug Discovery
    • Pharmacology

    Background:

    • Ligand optimization is crucial for drug discovery, involving synthesizing numerous analogs.
    • The efficiency of optimization is unclear due to a lack of a random background for comparison.
    • Existing data on analog improvement is clouded by reporting bias and reproducibility issues.

    Purpose of the Study:

    • To establish a background expectation for ligand potency optimization.
    • To systematically assess the impact of small, random modifications on ligand properties.
    • To quantify the challenges in improving drug candidates beyond in vitro potency.

    Main Methods:

    • Systematically modified 18 lead molecules across six targets using single atom changes.
    • Synthesized 257 unique analog compounds.
    • Evaluated potency, in vitro pharmacokinetics (metabolic stability, plasma free fraction), and in vivo efficacy.

    Main Results:

    • 11.2% of analogs with small perturbations showed a ≥10-fold increase in potency.
    • More potent analogs often exhibited poorer in vitro pharmacokinetic properties.
    • Some analogs compensated for reduced exposure with increased potency, leading to improved in vivo compounds.

    Conclusions:

    • Ligand optimization presents a frustrated landscape, with potency gains often offset by pharmacokinetic liabilities.
    • This study provides a baseline expectation for ligand optimization efficiency.
    • Moving beyond in vitro potency requires addressing complex trade-offs between efficacy and drug-like properties.