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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:
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...
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.
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 analyses the...
Protein-protein Interfaces02:04

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 polypeptide...

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BINANA: a novel algorithm for ligand-binding characterization.

Jacob D Durrant1, J Andrew McCammon

  • 1Department of Chemistry & Biochemistry, University of California San Diego, La Jolla, CA 92093-0365, United States. jdurrant@ucsd.edu

Journal of Molecular Graphics & Modelling
|February 12, 2011
PubMed
Summary
This summary is machine-generated.

A new computer algorithm, BINANA (BINding ANAlyzer), automates the characterization of ligand-receptor interactions. This tool aids in assessing ligand binding and identifying promising drug candidates by analyzing binding features.

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Biochemistry

Background:

  • Characterizing ligand-receptor interactions is crucial for understanding ligand binding.
  • Manual analysis of these interactions is time-consuming and complex.
  • Automating this process can significantly enhance research efficiency.

Purpose of the Study:

  • To introduce BINANA (BINding ANAlyzer), a novel Python-implemented algorithm.
  • To facilitate the automated characterization of ligand-receptor complexes.
  • To assist computational chemists and structural biologists in analyzing binding interactions.

Main Methods:

  • Development of a Python-based computer algorithm named BINANA.
  • Application of BINANA to analyze ligand-receptor complexes.
  • Utilizing BINANA for database searching and virtual screening analysis.

Main Results:

  • BINANA successfully automates the characterization of various ligand-receptor interactions.
  • A positive correlation was confirmed between hydrophobic contacts and ligand potency.
  • BINANA can identify complexes with specific binding features and potential lead candidates.

Conclusions:

  • BINANA offers an efficient solution for automated characterization of ligand-receptor binding.
  • The algorithm aids in identifying key binding characteristics and drug discovery.
  • BINANA is a valuable tool for computational chemists and structural biologists.