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

Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Protein Networks02:26

Protein Networks

2.9K
2.9K
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.7K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.7K
Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)01:15

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)

1.1K
Insensitive Nuclei Enhanced by Polarization Transfer (INEPT) is an advanced Nuclear Magnetic Resonance (NMR) technique specifically designed to detect and enhance the signals of low-abundance nuclei, such as carbon-13 and nitrogen-15, in small molecules. The fundamental principle behind INEPT is the transfer of polarization from a more abundant and highly polarizable nucleus, typically hydrogen-1, to the low-abundance nucleus of interest. This process effectively boosts the NMR signal of the...
1.1K
Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

2.7K
Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
2.7K
Network Covalent Solids02:18

Network Covalent Solids

16.2K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.2K

You might also read

Related Articles

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

Sort by
Same author

SLAE: Strictly Local All-atom Environment for Protein Representation.

bioRxiv : the preprint server for biology·2025
Same author

Compact RNA sensors for increasingly complex functions of multiple inputs.

Nature chemistry·2025
Same author

Does Sequence Clustering Confound AlphaFold2?

Journal of molecular biology·2025
Same author

High-throughput DNA melt measurements enable improved models of DNA folding thermodynamics.

Nature communications·2025
Same author

The conformational landscape of fold-switcher KaiB is tuned to the circadian rhythm timescale.

Proceedings of the National Academy of Sciences of the United States of America·2024
Same author

Protein language models learn evolutionary statistics of interacting sequence motifs.

Proceedings of the National Academy of Sciences of the United States of America·2024
Same journal

Complementing Onsager's Conductivity Theory by Grotthuss Mechanism Mitigation via Ion-Induced Depletion of Hydrogen-Bond-Donating Water.

Journal of chemical theory and computation·2026
Same journal

Microscopic Stress in Biomembranes: A Perspective on Key Concepts, Methods, and Applications.

Journal of chemical theory and computation·2026
Same journal

Analytic Nuclear Gradients Including Oriented External Electric Fields in a Molecule-Fixed Frame.

Journal of chemical theory and computation·2026
Same journal

Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model.

Journal of chemical theory and computation·2026
Same journal

Generalizable Protein Folding Pathway Exploration with DA2-GRASP: Extending Beyond Miniproteins.

Journal of chemical theory and computation·2026
Same journal

Improving PCM in Protic Media: Markov State Models for TD-DFT Calculations.

Journal of chemical theory and computation·2026
See all related articles

Related Experiment Video

Updated: Feb 13, 2026

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
07:57

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

Published on: August 21, 2019

9.2K

Transferable Neural Networks for Enhanced Sampling of Protein Dynamics.

Mohammad M Sultan, Hannah K Wayment-Steele, Vijay S Pande

    Journal of Chemical Theory and Computation
    |March 13, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new method using nonlinear latent embeddings from variational autoencoders for enhanced sampling in molecular simulations. The approach enables rapid sampling across multiple related systems, accelerating biophysical research.

    More Related Videos

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    1.1K
    Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy
    10:03

    Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy

    Published on: June 27, 2014

    18.4K

    Related Experiment Videos

    Last Updated: Feb 13, 2026

    Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
    07:57

    Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

    Published on: August 21, 2019

    9.2K
    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    1.1K
    Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy
    10:03

    Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy

    Published on: June 27, 2014

    18.4K

    Area of Science:

    • Computational Chemistry
    • Molecular Dynamics
    • Machine Learning

    Background:

    • Variational autoencoder (VAE) frameworks effectively reduce complex nonlinear dynamics in molecular simulations to a nonlinear latent embedding.
    • This latent embedding has potential applications as a collective variable for enhanced sampling techniques.

    Purpose of the Study:

    • To demonstrate the utility of nonlinear latent embeddings as collective variables for enhanced sampling.
    • To present a modification enabling rapid sampling across multiple related molecular systems.
    • To improve the efficiency of training VAE models for larger systems.

    Main Methods:

    • Utilizing nonlinear latent embeddings from VAEs as collective variables.
    • Applying a modified variational dynamics encoder incorporating time-structure based independent component analysis (tICA).
    • Demonstrating transferability of a trained model to related systems.

    Main Results:

    • The method successfully described force field changes in capped alanine dipeptide.
    • A VAE model trained on the WW domain protein was efficiently transferred for enhanced sampling of a related mutant (GTT mutation).
    • The tICA-enhanced VAE training improved efficiency for larger systems.

    Conclusions:

    • Nonlinear latent embeddings serve as effective transferable collective variables for enhanced sampling.
    • The modified VAE approach enables rapid and efficient sampling of related molecular systems.
    • This method holds promise for probing variations in large biophysical systems.