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Related Concept Videos

Membrane Domains01:18

Membrane Domains

The membrane domains concentrate specific lipids and proteins at one place within the membrane, which helps in cell signaling, adhesion, and other critical cellular processes. These domains can differ in size, composition, function, and lifespan.
Protein Domains
The membrane comprises a group of distinct proteins responsible for carrying out a cell's specific function. For example, the plasma membrane of the human sperm, or a single germ cell, contains a unique set of proteins in the anterior...
Multi-pass Transmembrane Proteins and β-barrels01:09

Multi-pass Transmembrane Proteins and β-barrels

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 G-protein-linked receptors (GPCRs) and...
Mechanisms of Membrane Domain Formation00:59

Mechanisms of Membrane Domain Formation

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 cytoskeletal...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Single-pass Transmembrane Proteins01:25

Single-pass Transmembrane Proteins

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...
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...

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Related Experiment Video

Updated: Jun 18, 2026

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

Structural feature extraction protocol for classifying reversible membrane binding protein domains.

Morten Källberg1, Hui Lu

  • 1Department of Bioengineering-Bioinformatics Program, University of Illinois at Chicago, 851 S. Morgan St. Chicago, IL 60607-7052, USA.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
Summary
This summary is machine-generated.

We developed a new automated method using machine learning to analyze protein structures. This approach effectively identifies key features for classifying protein functions, outperforming older sequence-based methods.

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Protein Membrane Overlay Assay: A Protocol to Test Interaction Between Soluble and Insoluble Proteins in vitro
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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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Last Updated: Jun 18, 2026

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

Protein Membrane Overlay Assay: A Protocol to Test Interaction Between Soluble and Insoluble Proteins in vitro
08:38

Protein Membrane Overlay Assay: A Protocol to Test Interaction Between Soluble and Insoluble Proteins in vitro

Published on: August 14, 2011

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational biology

Background:

  • Automated function annotation of protein structures is crucial for understanding biological processes.
  • Machine learning classification protocols often outperform traditional sequence-based methods.
  • Extracting relevant structural features remains a challenge for accurate annotation.

Purpose of the Study:

  • To present an automated method for extracting structural features from proteins.
  • To utilize surface patch construction for improved feature extraction.
  • To demonstrate the method's utility in classifying protein domains.

Main Methods:

  • Developed an automated procedure for growing surface patches on protein structures.
  • Employed machine learning classification protocols for feature analysis.
  • Applied the method to identify known protein domain families.

Main Results:

  • The patch-growing procedure successfully extracts relevant features from protein structures.
  • The automated method demonstrates high efficacy in classifying protein functions.
  • Successfully identified reversible membrane binding domains from C1, C2, and PH families.

Conclusions:

  • The developed automated method offers a superior alternative to sequence-based approaches for protein function annotation.
  • Surface patch extraction is a valuable strategy for machine learning-based structural analysis.
  • This method facilitates accurate identification of functionally important protein domains.