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Cooperative Allosteric Transitions

Cooperative Allosteric Transitions

Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...

Cooperative Allosteric Transitions

Cooperative Allosteric Transitions

Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...

Cooperative Allosteric Transitions

Cooperative Allosteric Transitions

Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...

Cooperative Binding of Transcription Regulators

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome. Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...

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:

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:

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Related Experiment Video

Updated: Jun 28, 2026

Optical Tweezers to Study RNA-Protein Interactions in Translation Regulation

Optical Tweezers to Study RNA-Protein Interactions in Translation Regulation

Published on: February 12, 2022

Hidden markov model for competitive binding and chain elongation.

R M Roberts¹, T J Cleland, P C Gray

¹Los Alamos National Laboratory, Los Alamos, New Mexico 87545.

The Journal of Physical Chemistry. B

|October 28, 2008

Summary

A new hidden Markov method models chemical reactions with premature chain termination, extending previous models. This approach accurately simulates complex molecular chain elongation processes, offering a powerful computational tool.

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Last Updated: Jun 28, 2026

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Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

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Published on: March 1, 2022

Area of Science:

Computational Chemistry
Biophysical Chemistry
Systems Biology

Background:

Many chemical systems involve iterated reactions for molecular chain elongation, crucial in biological processes like DNA transcription and RNA translation.
Premature chain termination by competitive reactions complicates accurate modeling of these systems.

Purpose of the Study:

To develop a hidden Markov method for modeling chemical reaction chains with competitive termination processes.
To extend the hidden Markov model framework for enhanced simulation accuracy.

Main Methods:

Developed a novel hidden Markov method, extending Gibson and Bruck's model.
Demonstrated equivalence between the new method and full reaction set simulations (Gillespie).
Applied the method to test problems and a practical biological system.

Main Results:

The hidden Markov method accurately models chain-elongation with premature termination.
Equivalence confirmed between the developed method and traditional simulation techniques.
Successful application shown for modeling terminal modification of ligand-aggregated receptors.

Conclusions:

The developed hidden Markov method provides an effective approach for simulating complex chemical reaction systems with termination.
This method offers a computationally efficient alternative to full reaction set simulations.
The model has practical applications in understanding biological processes like receptor modification.