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

Fluid Mosaic Model01:19

Fluid Mosaic Model

18.5K
Scientists identified the plasma membrane in the 1890s and its principal chemical components (lipids and proteins) by 1915. The model for plasma membrane structure, proposed in 1935 by Hugh Davson and James Danielli, was the first model to be widely accepted in the scientific community. The model was based on the plasma membrane's "railroad track" appearance in early electron micrographs. Davson and Danielli theorized that the plasma membrane's structure resembled a sandwich...
18.5K
The Fluid Mosaic Model01:34

The Fluid Mosaic Model

181.6K
The fluid mosaic model was first proposed as a visual representation of research observations. The model comprises the composition and dynamics of membranes and serves as a foundation for future membrane-related studies. The model depicts the structure of the plasma membrane with a variety of components, which include phospholipids, proteins, and carbohydrates. These integral molecules are loosely bound, defining the cell’s border and providing fluidity for optimal function.
181.6K
Introduction to Membrane Proteins01:16

Introduction to Membrane Proteins

82.2K
The cell membrane, or plasma membrane, is an ever-changing landscape. It is described as a fluid mosaic where various macromolecules are embedded in the phospholipid bilayer. Among the macromolecules are proteins. The protein content varies across cell types. For example, mitochondrial inner membranes contain ~76% protein content, while myelin contains ~18% protein content. Individual cells contain many types of membrane proteins—red blood cells contain over 50—and different cell...
82.2K
Multi-pass Transmembrane Proteins and β-barrels01:09

Multi-pass Transmembrane Proteins and β-barrels

6.7K
In multi-pass transmembrane proteins, the polypeptide chain crosses the membrane more than once. The transmembrane polypeptide chain either forms an α-helix or β-strand structure. α-Helix containing multi-pass transmembrane proteins are ubiquitous, whereas β-strand containing ones are mainly found in gram-negative bacteria, mitochondria, and chloroplasts.
α-Helix containing multi-pass transmembrane proteins
Multi-pass transmembrane proteins such as...
6.7K
Mechanisms of Membrane Domain Formation00:59

Mechanisms of Membrane Domain Formation

4.2K
Different physical properties of lipids and proteins allow them to localize and form distinct islands or domains in the membrane. Some membrane domains are formed due to protein-protein interactions, whereas others are formed due to the presence of specific lipids such as sphingolipids and sterols—for example, large proteins, such as bacteriorhodopsin, aggregate and create distinct domains.
Another mechanism for membrane domain formation involves membrane proteins interacting with...
4.2K
Mechanisms of Membrane-bending01:15

Mechanisms of Membrane-bending

3.6K
The living membranes are flexible due to their fluid mosaic nature; however, their bending into different shapes is an active process regulated by specific lipids and proteins. The membrane bending can be transient as seen in vesicles or stable for a long time as in microvilli. Cells regulate the size, location, and duration of the membrane curvature.
Membrane bending can happen due to intrinsic changes in lipid composition or extrinsic association with different proteins. The proteins involved...
3.6K

You might also read

Related Articles

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

Sort by
Same author

A Novel Triose Phosphate Isomerase Inhibitor With Dual Trypanosomicidal Activity was Identified Using Artificial Intelligence-Based Virtual Screening.

ChemMedChem·2026
Same author

The role of gastropods in African swine fever virus ecology.

Virology journal·2024
Same author

The fusion of physics and biology in early mammalian embryogenesis.

Current topics in developmental biology·2024
Same author

Artificial intelligence-powered discovery of small molecules inhibiting CTLA-4 in cancer.

BJC reports·2024
Same author

AI-powered discovery of a novel p53-Y220C reactivator.

Frontiers in oncology·2023
Same author

Discovery of a cryptic pocket in the AI-predicted structure of PPM1D phosphatase explains the binding site and potency of its allosteric inhibitors.

Frontiers in molecular biosciences·2023

Related Experiment Video

Updated: Feb 25, 2026

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

3.3K

The mesoscopic membrane with proteins (MesM-P) model.

Aram Davtyan1, Mijo Simunovic1, Gregory A Voth1

  • 1Department of Chemistry, The James Franck Institute, Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois 60637, USA.

The Journal of Chemical Physics
|August 3, 2017
PubMed
Summary

We introduce the Mesoscopic Membrane with Proteins (MesM-P) model for simulating lipid membranes and protein interactions. This model reveals four protein aggregation mechanisms on membranes, dependent on stiffness and protein curvature.

More Related Videos

Method to Visualize and Analyze Membrane Interacting Proteins by Transmission Electron Microscopy
10:49

Method to Visualize and Analyze Membrane Interacting Proteins by Transmission Electron Microscopy

Published on: March 5, 2017

14.0K
Native Cell Membrane Nanoparticles System for Membrane Protein-Protein Interaction Analysis
07:31

Native Cell Membrane Nanoparticles System for Membrane Protein-Protein Interaction Analysis

Published on: July 16, 2020

6.6K

Related Experiment Videos

Last Updated: Feb 25, 2026

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

3.3K
Method to Visualize and Analyze Membrane Interacting Proteins by Transmission Electron Microscopy
10:49

Method to Visualize and Analyze Membrane Interacting Proteins by Transmission Electron Microscopy

Published on: March 5, 2017

14.0K
Native Cell Membrane Nanoparticles System for Membrane Protein-Protein Interaction Analysis
07:31

Native Cell Membrane Nanoparticles System for Membrane Protein-Protein Interaction Analysis

Published on: July 16, 2020

6.6K

Area of Science:

  • Biophysics
  • Computational Biology
  • Materials Science

Background:

  • Lipid membranes are crucial for cellular functions.
  • Simulating protein-membrane interactions requires multiscale approaches.
  • Existing models struggle with protein-induced membrane dynamics at mesoscopic scales.

Purpose of the Study:

  • Introduce the Mesoscopic Membrane with Proteins (MesM-P) model.
  • Investigate protein aggregation and membrane shape changes at mesoscales.
  • Bridge the gap between different simulation resolutions.

Main Methods:

  • Developed a discrete mesoscopic quasi-particle approach (MesM-P).
  • Extended a previous elastic membrane model.
  • Simulated large lipid vesicles with varying bound protein densities.

Main Results:

  • Identified four distinct protein aggregation mechanisms.
  • Demonstrated dependence of aggregation on membrane stiffness and protein spontaneous curvature.
  • Validated MesM-P against higher-resolution coarse-grained molecular dynamics simulations.

Conclusions:

  • MesM-P effectively models protein-facilitated lipid membrane dynamics.
  • The model captures complex protein aggregation behaviors.
  • MesM-P enables simulations at length and time scales beyond traditional methods.