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Related Concept Videos

Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

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Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
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Insertion of Multi-pass Transmembrane Proteins in the RER01:29

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The rough ER membrane synthesizes, assembles, and embeds transmembrane proteins in diverse topologies. These proteins function as transporters or channels and can remain in the ER membrane or are sent to the Golgi complex, lysosome, and cell membrane.
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Multi-pass Transmembrane Proteins and β-barrels01:09

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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
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Insertion of Single-pass Transmembrane Proteins in the RER01:26

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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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Single-pass Transmembrane Proteins01:25

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Integral membrane proteins are tightly associated with the cell membrane and play a crucial role in cell communication, signaling, adhesion, and transport of the molecules. Some integral membrane proteins are present only in the membrane monolayer. For example, the enzyme fatty acid amide hydrolase is present in the cytoplasmic side of the membrane monolayer. In contrast, another type of integral membrane protein, also known as a transmembrane protein, spans across the membrane. Transmembrane...
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Protein Diffusion in the Membrane01:24

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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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Related Experiment Video

Updated: Jul 25, 2025

Determining Membrane Protein Topology Using Fluorescence Protease Protection FPP
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Recognition of outer membrane proteins using multiple feature fusion.

Wenxia Su1, Xiaojun Qian2, Keli Yang3

  • 1College of Science, Inner Mongolia Agriculture University, Hohhot, China.

Frontiers in Genetics
|June 23, 2023
PubMed
Summary

This study introduces a computational model for predicting outer membrane proteins (OMPs), crucial for membrane stability and potential disease diagnostics. The developed model achieves high accuracy, aiding experimental research.

Keywords:
jackknife testouter membrane proteinprediction modelpseudo amino acid compositionsupport vector machine

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Proteomics

Background:

  • Outer membrane proteins (OMPs) are vital for bacterial outer membrane structure and function.
  • OMPs possess antigenicity and immunogenicity, offering potential in clinical diagnostics and disease prevention.
  • Experimental identification of OMPs is costly and time-consuming, highlighting the need for computational approaches.

Purpose of the Study:

  • To develop and validate a computational model for accurate prediction of outer membrane proteins.
  • To provide a cost-effective and efficient alternative to experimental methods for OMP identification.

Main Methods:

  • Utilized a non-redundant dataset comprising 208 OMPs (positive set) and 876 non-OMPs (negative set).
  • Employed pseudo amino acid composition for feature vector extraction.
  • Applied a support vector machine (SVM) algorithm for prediction.

Main Results:

  • Achieved an overall accuracy of 93.19% in Jackknife cross-validation.
  • Obtained an area under the receiver operating characteristic curve (AUC) of 0.966.
  • Demonstrated the model's high predictive capability.

Conclusions:

  • The developed computational model accurately predicts outer membrane proteins.
  • This model can significantly guide and accelerate experimental research in OMP studies.
  • Offers a valuable tool for advancing research in bacterial outer membrane protein identification and application.