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

Assessing Two-dimensional Crystallization Trials of Small Membrane Proteins for Structural Biology Studies by Electron Crystallography09:23

Assessing Two-dimensional Crystallization Trials of Small Membrane Proteins for Structural Biology Studies by Electron Crystallography

11.6K
Evaluating two-dimensional (2D) crystallization trials for the formation of ordered membrane protein arrays is a highly critical and difficult task in electron crystallography. Here we describe our approach in screening for and identifying 2D crystals of predominantly small membrane proteins in the range of 15 –...
11.6K
Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules07:11

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules

7.3K
Here, we describe how to use the automated screening and data collection options available at some synchrotron beamlines. Scientists send cryocooled samples to the synchrotron, and the diffraction properties are screened, the data sets are collected and processed and, where possible, a structure solution is carried out—all without human...
7.3K
High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography06:19

High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography

5.6K
This protocol details high-throughput crystallization screening, ranging from the 1,536 microassay plate preparation to the end of a 6 week experimental time window. Details are included about the sample setup, the imaging obtained, and how users can perform analyses using an artificial intelligence-enabled graphical user interface to quickly and efficiently identify macromolecular crystallization...
5.6K
Crystallizing Membrane Proteins for Structure Determination using Lipidic Mesophases22:00

Crystallizing Membrane Proteins for Structure Determination using Lipidic Mesophases

30.6K
Herein is described the procedure implemented in the Caffrey Membrane Structural and Functional Biology Group to set up manually crystallization trials of membrane proteins in lipidic...
30.6K
Automated Protocols for Macromolecular Crystallization at the MRC Laboratory of Molecular Biology11:20

Automated Protocols for Macromolecular Crystallization at the MRC Laboratory of Molecular Biology

17.0K
Automated systems and protocols for the routine preparation of a large number of screens and nanoliter crystallization droplets for vapor diffusion experiments are described and...
17.0K
Protein-protein Interfaces02:04

Protein-protein Interfaces

14.5K
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...
14.5K

You might also read

Related Articles

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

Sort by
Same author

zsasa: a Zig-based engine for high-throughput solvent accessible surface area at proteome scale.

bioRxiv : the preprint server for biology·2026
Same author

Oligomer-based functions of mitochondrial porin.

Nature communications·2025
Same author

Application of Anomaly Detection to Identify Important Features of Protein Dynamics.

ACS omega·2025
Same author

Neuronal and non-neuronal functions of the synaptic cell adhesion molecule neurexin in Nematostella vectensis.

Nature communications·2024
Same author

PoSSuM v.3: A Major Expansion of the PoSSuM Database for Finding Similar Binding Sites of Proteins.

Journal of chemical information and modeling·2023
Same author

Predicting global distributions of eukaryotic plankton communities from satellite data.

ISME communications·2023

Related Experiment Video

Updated: Jan 20, 2026

Assessing Two-dimensional Crystallization Trials of Small Membrane Proteins for Structural Biology Studies by Electron Crystallography
09:23

Assessing Two-dimensional Crystallization Trials of Small Membrane Proteins for Structural Biology Studies by Electron Crystallography

Published on: October 29, 2010

11.6K

Accurate Classification of Biological and non-Biological Interfaces in Protein Crystal Structures using Subtle

Yoshinori Fukasawa1, Kentaro Tomii2,3,4

  • 1Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan. y-fukasawa@outlook.com.

Scientific Reports
|September 1, 2019
PubMed
Summary

Determining a protein's quaternary structure is vital for understanding its function. This study presents a novel classifier using protein sequence data and covariation signals to accurately identify biological protein assemblies from crystal structures.

More Related Videos

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
07:11

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules

Published on: March 22, 2019

7.3K
Author Spotlight: High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography
06:19

Author Spotlight: High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography

Published on: March 10, 2023

5.6K

Related Experiment Videos

Last Updated: Jan 20, 2026

Assessing Two-dimensional Crystallization Trials of Small Membrane Proteins for Structural Biology Studies by Electron Crystallography
09:23

Assessing Two-dimensional Crystallization Trials of Small Membrane Proteins for Structural Biology Studies by Electron Crystallography

Published on: October 29, 2010

11.6K
Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
07:11

Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules

Published on: March 22, 2019

7.3K
Author Spotlight: High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography
06:19

Author Spotlight: High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography

Published on: March 10, 2023

5.6K

Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational biology

Background:

  • Proteins function as oligomers or multimers, making their quaternary structure essential for biological activity.
  • X-ray crystallography provides structural data, but distinguishing biological from crystallographic interfaces is challenging.
  • Accurate identification of biological units is crucial for understanding protein function in vivo.

Purpose of the Study:

  • To develop a simple, highly accurate classifier for inferring biological units from protein crystal structures.
  • To overcome the difficulty of distinguishing biological protein-protein interfaces from crystallographic ones.
  • To leverage large-scale protein sequence information and modern contact prediction methods.

Main Methods:

  • Utilized a classifier based on extensive protein sequence data.
  • Employed a modern contact prediction method exploiting protein covariation signals (CSs).
  • Analyzed the relationship between classification accuracy and biological unit conservation.

Main Results:

  • The developed classifier accurately infers biological units in protein crystal structures.
  • The method shows promise even for detecting weak signals of biological interfaces.
  • Demonstrated the impact of sequence selection in multiple sequence alignments on CSs and results.

Conclusions:

  • The proposed method offers a reliable approach for identifying biological protein assemblies.
  • Covariation signals from protein sequences are valuable for predicting biological interfaces.
  • The classifier's utility is expected to increase with growing sequence data availability.