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Related Concept Videos

Atomic Nuclei: Nuclear Spin State Population Distribution01:14

Atomic Nuclei: Nuclear Spin State Population Distribution

Near absolute zero temperatures, in the presence of a magnetic field, the majority of nuclei prefer the lower energy spin-up state to the higher energy spin-down state. As temperatures increase, the energy from thermal collisions distributes the spins more equally between the two states. The Boltzmann distribution equation gives the ratio of the number of spins predicted in the spin −½ (N−) and spin +½ (N+) states.
Atomic Nuclei: Nuclear Spin State Overview01:03

Atomic Nuclei: Nuclear Spin State Overview

NMR-active nuclei have energy levels called 'spin states' that are associated with the orientations of their nuclear magnetic moments. In the absence of a magnetic field, the nuclear magnetic moments are randomly oriented, and the spin states are degenerate. When an external magnetic field is applied, the spin states have only 2 + 1 orientations available to them. A proton with = ½ has two available orientations. Similarly, for a quadrupolar nucleus with a nuclear spin value of one, the...
Free Energy Changes for Nonstandard States03:25

Free Energy Changes for Nonstandard States

The free energy change for a process taking place with reactants and products present under nonstandard conditions (pressures other than 1 bar; concentrations other than 1 M) is related to the standard free energy change according to this equation:
Atomic Nuclei: Nuclear Relaxation Processes01:23

Atomic Nuclei: Nuclear Relaxation Processes

In the absence of an external magnetic field, nuclear spin states are degenerate and randomly oriented. When a magnetic field is applied, the spins begin to precess and orient themselves along (lower energy) or against (higher energy) the direction of the field. At equilibrium, a slight excess population of spins exists in the lower energy state. Because the direction of the magnetic field is fixed as the z-axis,  the precessing magnetic moments are randomly oriented around the z-axis. This...
Entropy02:39

Entropy

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...
Potential-Energy Criterion for Equilibrium01:16

Potential-Energy Criterion for Equilibrium

Potential energy or potential function plays an essential role in determining the stability of a mechanical system. If a system is subjected to both gravitational and elastic forces, the potential function of the system can be expressed as the algebraic sum of gravitational and elastic potential energy. If the system is in equilibrium and is displaced by a small amount, then the work done on the system equals the negative of the change in the system's potential energy from the initial to the...

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Related Experiment Video

Updated: May 16, 2026

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

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

Published on: March 1, 2022

Using the unfolded state as the reference state improves the performance of statistical potentials.

Yufeng Liu1, Haipeng Gong

  • 1Ministry of Education Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing, China.

Biophysical Journal
|December 4, 2012
PubMed
Summary

We developed a new statistical potential, SPOUSE, using unfolded protein states. SPOUSE improves protein structure modeling by better representing polypeptide chains compared to existing methods.

Related Experiment Videos

Last Updated: May 16, 2026

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

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

Published on: March 1, 2022

Area of Science:

  • Computational Biology
  • Biophysics
  • Structural Bioinformatics

Background:

  • Distance-dependent statistical potentials are crucial for protein structure and energetics modeling.
  • Current reference states often fail to capture specific chemical constraints of polypeptide chains.
  • This limits the accuracy and selectivity of existing statistical potentials.

Purpose of the Study:

  • To introduce a novel statistical potential, SPOUSE (Statistical Potential based on Unfolded State Ensemble).
  • To improve the accuracy of protein structure modeling by developing a more representative reference state.
  • To evaluate SPOUSE's performance against widely used distance-dependent potentials.

Main Methods:

  • Developed SPOUSE by deriving the reference state from unfolded protein ensembles using the statistical coil model.
  • Compared SPOUSE against three leading distance-dependent potentials.
  • Assessed performance in native conformation identification, selection of near-native models, and energy-model error correlation.

Main Results:

  • SPOUSE demonstrated superior performance in native conformation identification compared to existing potentials.
  • SPOUSE showed improved accuracy in selecting close-to-native protein models.
  • SPOUSE achieved better correlation coefficients between energy and model error.

Conclusions:

  • SPOUSE offers a more accurate and selective approach for protein structure and energetics modeling.
  • The use of unfolded state ensembles provides a better representation of polypeptide chain behavior.
  • SPOUSE shows potential for further enhancements through integration with orientation-dependent potentials.