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

The Proteasome02:18

The Proteasome

9.5K
Eukaryotic cells can degrade proteins through several pathways. One of the most important amongst these is the ubiquitin-proteasome pathway. It helps the cell eliminate the misfolded, damaged, or unwarranted cytoplasmic proteins in a highly specific manner.
In this pathway, the target proteins are first tagged with small proteins called ubiquitin. A series of enzymes carry out the ubiquitination of the target proteins - E1 (ubiquitin-activating enzyme), E2 (ubiquitin-conjugating enzyme), and E3...
9.5K
The Proteasome Structure01:17

The Proteasome Structure

1.2K
The ubiquitin-proteasome pathway is a well-known mechanism utilized by eukaryotic cells to remove cytoplasmic proteins that are misfolded, damaged, or no longer needed. In this pathway, the protein that needs to be eliminated undergoes a process called ubiquitination, where a chain of ubiquitin molecules is attached to the 48th lysine residue of the target protein. This ubiquitin modification helps the proteasome distinguish between a target protein and a healthy protein.
The proteasome is an...
1.2K

You might also read

Related Articles

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

Sort by
Same author

Cryo-Electron Microscopy Structural Ensemble Optimization Using Individual Particles.

Journal of chemical theory and computation·2026
Same author

Counting particles in cryo-electron microscopy may result in incorrect population estimates.

Communications biology·2026
Same author

Machine learning for biomolecular modeling.

The Journal of chemical physics·2026
Same author

A theoretical framework for random acceleration molecular dynamics simulations.

The Journal of chemical physics·2026
Same author

CryoJAX: a cryo-electron microscopy image-simulation library in JAX.

Acta crystallographica. Section D, Structural biology·2026
Same author

Cryo-electron microscopy ensemble optimization using individual particles and physical constraints.

bioRxiv : the preprint server for biology·2026

Related Experiment Video

Updated: Nov 23, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

2.3K

An automated protocol for modelling peptide substrates to proteases.

Rodrigo Ochoa1,2, Mikhail Magnitov3,4, Roman A Laskowski3

  • 1Biophysics of Tropical Diseases, Max Planck Tandem Group, University of Antioquia, 050010, Medellín, Colombia. rodrigo.ochoa@udea.edu.co.

BMC Bioinformatics
|December 30, 2020
PubMed
Summary

This study presents a computational protocol to model protease-peptide complexes, aiding in understanding substrate recognition. The findings offer insights for predicting novel protease substrates by analyzing structural features.

Keywords:
BioinformaticsPeptidesPromiscuityProteasesStructure

More Related Videos

Use of Recombinant Fusion Proteins in a Fluorescent Protease Assay Platform and Their In-gel Renaturation
19:23

Use of Recombinant Fusion Proteins in a Fluorescent Protease Assay Platform and Their In-gel Renaturation

Published on: January 16, 2019

9.5K
Analysis of Group IV Viral SSHHPS Using In Vitro and In Silico Methods
10:40

Analysis of Group IV Viral SSHHPS Using In Vitro and In Silico Methods

Published on: December 21, 2019

26.2K

Related Experiment Videos

Last Updated: Nov 23, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

2.3K
Use of Recombinant Fusion Proteins in a Fluorescent Protease Assay Platform and Their In-gel Renaturation
19:23

Use of Recombinant Fusion Proteins in a Fluorescent Protease Assay Platform and Their In-gel Renaturation

Published on: January 16, 2019

9.5K
Analysis of Group IV Viral SSHHPS Using In Vitro and In Silico Methods
10:40

Analysis of Group IV Viral SSHHPS Using In Vitro and In Silico Methods

Published on: December 21, 2019

26.2K

Area of Science:

  • Biochemistry
  • Structural Biology
  • Computational Biology

Background:

  • Proteases play crucial roles in biological processes, exhibiting substrate specificity that can sometimes extend to promiscuity.
  • Existing databases of protease specificity matrices offer insights, but structural determinants of substrate recognition remain incompletely understood.

Purpose of the Study:

  • To develop a computational protocol for modeling protease-peptide complexes using available crystal structures.
  • To investigate structural determinants of protease substrate recognition and binding dynamics.

Main Methods:

  • Compiled a dataset of protease crystal structures with bound peptide-like ligands.
  • Developed a protocol for modeling substrate binding and analyzing associated observables.
  • Employed Rosetta's Backrub method for conformational sampling of modeled protease-peptide complexes.

Main Results:

  • Compared calculated structural observables (e.g., relative accessible surface area, interaction energy) with experimental cleavage data and informational entropies.
  • Identified specific structural observables that correlate with protease substrate recognition.
  • Demonstrated the potential for these observables to aid in predicting novel protease substrates.

Conclusions:

  • The developed approach provides a valuable repository of annotated protease structures and an open-source computational protocol.
  • The protocol enables reproducible modeling and dynamic analysis of protease-peptide interactions.
  • This work contributes to a deeper understanding of protease function and substrate recognition mechanisms.