Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Entropy02:39

Entropy

36.4K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
36.4K
Entropy01:18

Entropy

3.6K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
3.6K
Standard Entropy Change for a Reaction03:00

Standard Entropy Change for a Reaction

25.0K
Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
25.0K
Entropy and Solvation02:05

Entropy and Solvation

8.5K
The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
8.5K
Entropy within the Cell01:22

Entropy within the Cell

13.0K
A living cell's primary tasks of obtaining, transforming, and using energy to do work may seem simple. However, the second law of thermodynamics explains why these tasks are harder than they appear. None of the energy transfers in the universe are completely efficient. In every energy transfer, some amount of energy is lost in a form that is unusable. In most cases, this form is heat energy. Thermodynamically, heat energy is defined as the energy transferred from one system to another that...
13.0K
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

5.0K
The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
5.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

LSP-MD: A Fast Computational Method to Study Allostery Driven by Thermal Vibrations.

Journal of chemical theory and computation·2025
Same author

Local and distal changes in dynamics are caused by an L205R Cushing's syndrome mutant in PRKACA.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Role of the αC-β4 loop in protein kinase structure and dynamics.

eLife·2024
Same author

Gauging Dynamics-driven Allostery Using a New Computational Tool: A CAP Case Study.

Journal of molecular biology·2023
Same author

Protein Kinase Structure and Dynamics: Role of the αC-β4 Loop.

bioRxiv : the preprint server for biology·2023
Same author

Single-residue mutation in protein kinase C toggles between cancer and neurodegeneration.

The Biochemical journal·2023

Related Experiment Video

Updated: Feb 11, 2026

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.4K

Self-organization, entropy and allostery.

Alexandr P Kornev1

  • 1Department of Pharmacology, University of California at San Diego, La Jolla, CA 92093, U.S.A. akornev@ucsd.edu.

Biochemical Society Transactions
|April 22, 2018
PubMed
Summary

Allostery, a key biological process, is better understood by integrating its dynamics with protein fractal properties, hierarchical folding, and entropy-driven recognition. Collective study of these self-organizing phenomena advances biological insights.

Keywords:
allosteric regulationfractalsprotein conformationprotein dynamics

More Related Videos

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides
09:41

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides

Published on: May 29, 2018

10.0K
Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
08:08

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

15.3K

Related Experiment Videos

Last Updated: Feb 11, 2026

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.4K
Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides
09:41

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides

Published on: May 29, 2018

10.0K
Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
08:08

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

15.3K

Area of Science:

  • Biochemistry
  • Structural Biology
  • Biophysics

Background:

  • Allostery is a crucial biological regulatory mechanism.
  • The precise molecular mechanisms of allosteric signal transmission are debated.
  • Existing research often studies related phenomena like protein fractal properties, hierarchical folding, and entropy-driven recognition in isolation.

Purpose of the Study:

  • To propose a unified framework for understanding allostery.
  • To integrate the study of allosteric signal transmission with protein internal dynamics, fractal-like properties, hierarchical folding, and entropy-driven molecular recognition.
  • To highlight the common root of these phenomena in the self-organization of polypeptide chains.

Main Methods:

  • Conceptual synthesis of existing multi-disciplinary data.
  • Theoretical integration of allosteric regulation with protein structural and dynamic properties.
  • Argument for a collective, cross-referenced approach to studying these phenomena.

Main Results:

  • Allosteric regulation is proposed as part of a larger picture encompassing protein interior fractal-like properties, hierarchical folding, and entropy-driven molecular recognition.
  • These diverse phenomena share a common origin in the self-organization of polypeptide chains.
  • Studying these phenomena collectively facilitates cross-referencing of data and accelerates progress.

Conclusions:

  • A unified, multi-disciplinary approach is necessary to fully elucidate allosteric mechanisms.
  • Understanding the self-organization of polypeptide chains is key to integrating these biological concepts.
  • This integrated perspective promises significant advancements in understanding protein regulation and function.