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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:

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...

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Related Experiment Video

Updated: May 28, 2025

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Published on: July 19, 2024

Physics-Inspired Accuracy Estimator for Model-Docked Ligand Complexes.

Byung-Hyun Bae^1,2, Jungyoon Choi^1,3, Chaok Seok²

¹Biomedical Research Division, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea.

Journal of Chemical Theory and Computation

|February 10, 2025

Summary

This summary is machine-generated.

DENOISer, a deep neural network, improves drug discovery by accurately scoring protein-ligand poses in model docking. It overcomes limitations of traditional scoring functions, enhancing accuracy in identifying correct solutions.

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Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry

Analyzing Protein Architectures and Protein-Ligand Complexes by Integrative Structural Mass Spectrometry

Published on: October 15, 2018

Area of Science:

Computational chemistry
Structural biology
Artificial intelligence in drug discovery

Background:

AI-driven protein structure prediction advances model docking for drug discovery.
Traditional docking score functions struggle with minor structural inaccuracies, failing to identify correct ligand poses.

Purpose of the Study:

To develop a deep neural network, DENOISer, to address scoring challenges in model docking.
To improve the accuracy of identifying correct protein-ligand complex structures.

Main Methods:

Proposed DENOISer, a deep neural network with native-likeness and binding energy prediction subnetworks.
Incorporated physical knowledge as inductive bias for enhanced pose discrimination and noise tolerance.
Combined DENOISer with Rosetta GALigandDock sampling.

Main Results:

DENOISer outperformed existing docking tools on model-docking and cross-docking benchmarks.
Physics-based components and consensus ranking were identified as key factors for success.
Demonstrated tolerance to small interfacial structural noises.

Conclusions:

DENOISer effectively addresses scoring challenges in model docking, improving accuracy.
The approach shows promise for assisting drug discovery by providing reliable structural models.
Future drug discovery efforts can benefit from DENOISer's enhanced pose ranking capabilities.