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

4.7K
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,...
4.7K
Protein Networks02:26

Protein Networks

2.9K
2.9K
Conserved Binding Sites01:49

Conserved Binding Sites

5.3K
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...
5.3K
Protein-protein Interfaces02:04

Protein-protein Interfaces

15.0K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
15.0K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

4.6K
4.6K
Protein Organization01:24

Protein Organization

10.0K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
10.0K

You might also read

Related Articles

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

Sort by
Same author

Extending the classical sequence-structure-function paradigm through protein dynamics and context-dependent behavior.

FEBS letters·2026
Same author

Joint clinical and molecular subtyping of COPD with variational autoencoders.

Nature communications·2026
Same author

King's stages of amyotrophic lateral sclerosis: an 18F-FDG-PET study of brain connectivity.

Brain : a journal of neurology·2026
Same author

Discriminative Performance and Clinical utility of COPD Exacerbation Categories for Predicting Future Exacerbations.

American journal of respiratory and critical care medicine·2026
Same author

Brief comments on "Perturbation response scanning of drug-target networks: Drug repurposing for multiple sclerosis".

Journal of pharmaceutical analysis·2026
Same author

Clinical History, Spirometry, and CT Features Can Predict Dyspnea in Smokers with and without Spirometry-Defined COPD.

Lung·2026
Same journal

Anti-mycobacterial activity of phytocompounds from <i>Ricinus communis</i> L. - an integrated <i>in-vitro</i> and <i>in-silico</i> approach.

Journal of biomolecular structure & dynamics·2026
Same journal

Binding studies of the X-ray characterized [SnMe<sub>2</sub>Cl<sub>2</sub>(Me<sub>2</sub>phen)] complex with human serum albumin: experimental and molecular docking approaches.

Journal of biomolecular structure & dynamics·2026
Same journal

Computational design and experimental validation of peptide inhibitors to disrupt urease enzyme maturation in pathogenic bacteria <i>Proteus mirabilis</i>.

Journal of biomolecular structure & dynamics·2026
Same journal

Wavelet-domain multiway spectral separation of free drug, DNA, and drug-DNA complex profiles for quantitative binding analysis based on fractional occupancy (<i>θ</i>).

Journal of biomolecular structure & dynamics·2026
Same journal

Gene expression and microsecond scale conformational dynamics suggest potential regulatory mechanisms for the expanded subtilase family of <i>T. rubrum</i>.

Journal of biomolecular structure & dynamics·2026
Same journal

Deciphering the Role of Sugar Osmolytes in Free and Nano forms to Mitigate Protein Aggregation: Insights from Biophysical and Microscopic Studies.

Journal of biomolecular structure & dynamics·2026
See all related articles

Related Experiment Video

Updated: Mar 31, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.8K

A generative model for protein contact networks.

Lorenzo Livi1, Enrico Maiorino2, Alessandro Giuliani3

  • 1a Department of Computer Science , Ryerson University , 350 Victoria Street, Toronto , ON , M5B 2K3 Canada .

Journal of Biomolecular Structure & Dynamics
|October 17, 2015
PubMed
Summary
This summary is machine-generated.

We developed a new generative model for protein contact networks (PCNs) that better mimics real protein structures. While improving diffusion properties, it required a reconfiguration step to accurately capture shortest path structures.

Keywords:
generative modelgraph Laplacianmesoscopic analysisprotein contact network

More Related Videos

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps
09:30

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Published on: July 19, 2024

2.3K
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

16.2K

Related Experiment Videos

Last Updated: Mar 31, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.8K
Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps
09:30

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Published on: July 19, 2024

2.3K
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

16.2K

Area of Science:

  • Computational Biology
  • Network Science
  • Structural Bioinformatics

Background:

  • Protein contact networks (PCNs) are crucial for understanding protein structure and function.
  • Existing generative models struggle to accurately replicate the complex topology of real PCNs.
  • Mesoscopic and topological properties are key indicators of network health and function.

Purpose of the Study:

  • To introduce a novel generative model for PCNs.
  • To evaluate the model's ability to reproduce key network properties, including diffusion and shortest path characteristics.
  • To investigate the role of modularity in PCN architecture.

Main Methods:

  • Development of a generative model for PCNs.
  • Analysis of mesoscopic properties using graph Laplacian spectra.
  • Evaluation of topological descriptors like shortest path statistics and modularity.
  • Implementation of a targeted edge reconfiguration process for model refinement.

Main Results:

  • The proposed generative model significantly improves the approximation of real PCNs, particularly in diffusion properties derived from normalized Laplacian spectra.
  • The model, even after refinement, shows limitations in accurately reproducing shortest path structures.
  • Modularity is demonstrated to be an emergent property rather than a sole driver of PCN architecture.

Conclusions:

  • The enhanced generative model offers improved representation of PCN diffusion properties.
  • A secondary edge reconfiguration step is necessary for accurate shortest path representation.
  • Modularity arises from protein structural organization and is optimized alongside path efficiency in PCNs.