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Related Concept Videos

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:
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 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...
Conserved Binding Sites01:49

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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Crystal Field Theory - Octahedral Complexes02:58

Crystal Field Theory - Octahedral Complexes

Crystal Field Theory
To explain the observed behavior of transition metal complexes (such as colors), a model involving electrostatic interactions between the electrons from the ligands and the electrons in the unhybridized d orbitals of the central metal atom has been developed. This electrostatic model is crystal field theory (CFT). It helps to understand, interpret, and predict the colors, magnetic behavior, and some structures of coordination compounds of transition metals.
CFT focuses on...

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Related Experiment Video

Updated: Jun 21, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Predicting ligand binding energies.

J D Hirst1

  • 1Department of Molecular Biology, TPC-6, Scripps Research Institute, La Jolla, CA 92037, USA. jhirst@scripps.edu

Current Opinion in Drug Discovery & Development
|August 4, 2009
PubMed
Summary
This summary is machine-generated.

This review explores novel computational methods for predicting ligand binding energies in computer-aided drug design. It covers techniques from simplified ligand analyses to detailed receptor-ligand statistical mechanics models.

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Area of Science:

  • Computational chemistry
  • Molecular modeling
  • Drug discovery

Background:

  • Molecular recognition is central to chemistry and biology.
  • Computer-aided drug design (CADD) is a rapidly growing field.
  • Predicting ligand binding is crucial for drug development.

Purpose of the Study:

  • To review novel methods for predicting ligand binding energies.
  • To focus on techniques rather than specific applications.
  • To present a range of computational approaches.

Main Methods:

  • Statistical analyses of reduced ligand descriptors.
  • Statistical mechanical methods with atomic detail.
  • Methods considering both ligand and receptor information.

Main Results:

  • Emergence of diverse novel techniques for binding energy prediction.
  • Advancements span from simplified to highly detailed computational models.
  • Methods cater to varying levels of available structural information.

Conclusions:

  • The field of CADD is advancing with new predictive methods.
  • A spectrum of computational approaches is available for binding energy prediction.
  • Future drug design will benefit from these evolving techniques.