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Related Concept Videos

Mechanisms of Membrane-bending01:15

Mechanisms of Membrane-bending

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...
Membrane Fluidity01:23

Membrane Fluidity

Cell membranes are composed of phospholipids, proteins, and carbohydrates loosely attached to one another through chemical interactions. Molecules are generally able to move about in the plane of the membrane, giving the membrane its flexible nature called fluidity. Two other features of the membrane contribute to membrane fluidity: the chemical structure of the phospholipids and the presence of cholesterol in the membrane.Fatty acids tails of phospholipids can be either saturated or...
Membrane Fluidity01:26

Membrane Fluidity

Membrane fluidity is explained by the fluid mosaic model of the cell membrane, which describes the plasma membrane structure as a mosaic of components—including phospholipids, cholesterol, proteins, and carbohydrates—that gives the membrane a fluid character.
Mosaic nature of the membrane
The mosaic characteristic of the membrane helps the plasma membrane remain fluid. The integral proteins and lipids exist as separate but loosely-attached molecules in the membrane. The membrane is a relatively...
Insertion of Single-pass Transmembrane Proteins in the RER01:26

Insertion of Single-pass Transmembrane Proteins in the RER

Integral membrane proteins are proteins adhered to the lipid bilayer of a cell organelle or membrane. They can be of two types: transmembrane integral proteins that span the lipid bilayer and monotopic proteins that are attached to either side of the membrane but do not pass through it.
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Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
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Overview

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Pulling Membrane Nanotubes from Giant Unilamellar Vesicles
06:26

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Published on: December 7, 2017

TMKink: a method to predict transmembrane helix kinks.

Alejandro D Meruelo1, Ilan Samish, James U Bowie

  • 1Medical Scientist Training Program, UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, UCLA, Los Angeles, California 90095-1570, USA.

Protein Science : a Publication of the Protein Society
|May 13, 2011
PubMed
Summary

Scientists identified local sequence preferences, like proline abundance, in kinked transmembrane helices. This led to a neural network predictor, TMKink, accurately identifying helix distortions in membrane proteins.

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Area of Science:

  • Structural biology
  • Bioinformatics
  • Membrane protein research

Background:

  • Transmembrane helices in membrane proteins often exhibit distortions or bends.
  • Understanding the generation and prediction of these helix bends is crucial for deciphering protein structure and function.

Purpose of the Study:

  • To identify local sequence features associated with kinked transmembrane helices.
  • To develop a computational tool for predicting the occurrence of helix bends in membrane proteins.

Main Methods:

  • Analysis of local sequence preferences within kinked transmembrane helices.
  • Development and training of a neural network predictor (TMKink) utilizing sequence information.

Main Results:

  • Identified a higher abundance of proline in kinked helices as a key local sequence preference.
  • The TMKink predictor achieved a sensitivity of 0.70 and a specificity of 0.89 in identifying helix bends.
  • The predictor successfully identifies over two-thirds of all bends with high reliability.

Conclusions:

  • Local sequence information, particularly proline content, can be effectively used to predict helix distortions.
  • The developed TMKink predictor demonstrates high accuracy and reliability in identifying kinked transmembrane helices.
  • Future improvements in helix distortion predictors are anticipated with the availability of more structural data.