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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.
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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...

Cell-surface Signaling

Cell-surface Signaling

Hormones—or any molecule that binds to a receptor, known as a ligand—that are lipid-insoluble (water-soluble) are not able to diffuse across the cell membrane. In order to be able to affect a cell without entering it, these hormones bind to receptors on the cell membrane. When a first messenger, a hormone, binds to a receptor, a signal cascade is set off, causing second messengers, proteins inside the cell, to become activated, resulting in downstream effects.

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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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

Targeting protein-ligand neosurfaces with a generalizable deep learning tool.

Anthony Marchand¹, Stephen Buckley¹, Arne Schneuing¹

¹Laboratory of Protein Design and Immunoengineering, Institute of Bioengineering, Ecole polytechnique fédérale de Lausanne, Lausanne, Switzerland.

|January 15, 2025

Summary

This summary is machine-generated.

Researchers developed a computational strategy to design proteins targeting neosurfaces, which are surfaces formed by protein-ligand complexes. This approach uses deep learning to create novel chemically induced protein interactions for drug-controlled therapies.

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Area of Science:

Biochemistry
Computational Biology
Drug Discovery

Background:

Protein-protein interactions are fundamental to biological processes.
Regulation of these interactions by small molecules is an emerging area.
Computational design of chemically induced protein interactions remains challenging.

Purpose of the Study:

To present a computational strategy for designing proteins that target neosurfaces (surfaces arising from protein-ligand complexes).
To demonstrate the generalizability of deep learning models to novel molecular contexts.

Main Methods:

Utilized a geometric deep learning approach with learned molecular surface representations.
Developed and experimentally validated protein binders against three drug-bound protein complexes (Bcl2-venetoclax, DB3-progesterone, PDF1-actinonin).

Main Results:

Designed protein binders exhibited high affinities and specificities for their target neosurfaces.
Demonstrated that surface fingerprints trained on proteins could be successfully applied to neosurfaces.
Validated the generalizability of the deep learning approach across different drug-target complexes.

Conclusions:

The developed computational strategy enables the design of proteins targeting neosurfaces.
This approach offers a powerful demonstration of deep learning model generalizability.
Designed chemically induced protein interactions hold potential for engineered cells and drug-controlled therapies.