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

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

14.8K
Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
14.8K
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

4.9K
Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
4.9K
Conservation of Protein Domains02:26

Conservation of Protein Domains

4.2K
4.2K
Conserved Binding Sites01:49

Conserved Binding Sites

5.2K
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...
5.2K
Conserved Binding Sites01:49

Conserved Binding Sites

2.0K
2.0K
Protein and Protein Structure02:15

Protein and Protein Structure

89.9K
Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
89.9K

You might also read

Related Articles

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

Sort by
Same author

De novo headache after microsurgical resection or stereotactic radiosurgery of brain arteriovenous malformation.

Headache·2026
Same author

Long-term outcomes after treatment for symptomatic hemorrhage of brain arteriovenous malformations.

Annals of medicine·2026
Same author

De Novo Protein Structure Prediction by Model Quality Assessment Dynamic Feedback Mechanism Using Deep Learning.

IEEE transactions on computational biology and bioinformatics·2025
Same author

Improving protein-protein interaction site prediction using graph neural network and structure profiles.

Analytical biochemistry·2025
Same author

QSM predicts haemorrhage risk in brainstem cavernous malformations: a multicentre prospective study.

Journal of neurology, neurosurgery, and psychiatry·2025
Same author

Long-term outcomes and prognostic factors after surgery alone for brain arteriovenous malformation.

Brain circulation·2025
Same journal

A Transparent, Microfluidic Lab On A Chip For Multi-Modal Cell Culture Monitoring For Neurotoxicity Research.

IEEE transactions on nanobioscience·2026
Same journal

Investigating Effect of Dimensional Variance on Separation of Glomerular Ultrafiltrate in a Microfluidic Environment.

IEEE transactions on nanobioscience·2026
Same journal

Green synthesis of multifunctional ZnFe<sub>2</sub>O<sub>4</sub>-MWCNT-Cellulose acetate nanocomposite for peroxidase enzyme immobilization.

IEEE transactions on nanobioscience·2026
Same journal

IoT-Enabled SnOâ‚‚-Based Humidity Sensor for Real-Time Monitoring in Neonatal Incubators.

IEEE transactions on nanobioscience·2026
Same journal

Electrokinetic and Antibiofilm Effects of Silver Nanoparticles Combined with Imipenem Against multidrug-resistant of Klebsiella pneumoniae.

IEEE transactions on nanobioscience·2026
Same journal

Bio-inspired Optofluidic Molecular Communication with Photothermally Actuated Microrobot Swarms.

IEEE transactions on nanobioscience·2026
See all related articles

Related Experiment Video

Updated: Feb 23, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

16.1K

Conformational Space Sampling Method Using Multi-Subpopulation Differential Evolution for De novo Protein Structure

Xiao-Hu Hao, Gui-Jun Zhang, Xiao-Gen Zhou

    IEEE Transactions on Nanobioscience
    |September 9, 2017
    PubMed
    Summary
    This summary is machine-generated.

    A new multi-subpopulation differential evolution (MDE) method enhances protein structure prediction by improving conformational space sampling. This approach effectively identifies near-native protein conformations, advancing computational biology.

    More Related Videos

    Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
    05:08

    Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

    Published on: July 8, 2025

    1.2K
    Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
    10:58

    Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

    Published on: July 25, 2013

    17.7K

    Related Experiment Videos

    Last Updated: Feb 23, 2026

    Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
    09:51

    Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

    Published on: July 16, 2017

    16.1K
    Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
    05:08

    Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

    Published on: July 8, 2025

    1.2K
    Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
    10:58

    Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

    Published on: July 25, 2013

    17.7K

    Area of Science:

    • Computational Biology
    • Biophysics
    • Structural Biology

    Background:

    • Protein structure prediction is a complex optimization challenge involving vast conformational spaces and intricate energy landscapes.
    • Existing methods struggle with efficiently sampling these spaces to find accurate protein structures.

    Purpose of the Study:

    • To introduce and validate a novel conformational space sampling method, multi-subpopulation differential evolution (MDE), for protein structure prediction.
    • To enhance the efficiency and accuracy of identifying low-energy protein conformations.

    Main Methods:

    • Developed MDE, a method employing multi-subpopulation differential evolution with an ultrafast shape recognition-based modal identification protocol.
    • Integrated an abstract convex underestimate technique for local descent sampling to improve exploration of low-energy regions.
    • Utilized differential evolution to maintain modal survival throughout the evolutionary process.

    Main Results:

    • MDE demonstrated strong conformational space sampling capabilities across 20 tested proteins.
    • The method effectively generated clusters of conformations, with representative samples suitable for refinement.
    • Near-native protein conformations were successfully obtained, validated against established methods and CASP 11 targets.

    Conclusions:

    • MDE offers a robust and effective approach for protein structure prediction by enhancing conformational sampling.
    • The method's ability to identify near-native structures positions it as a valuable tool in computational structural biology.
    • Further applications of MDE could significantly advance the field of protein structure determination.