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Related Concept Videos

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...
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Plasma membranes have integral transmembrane proteins involved in facilitated transport. These proteins are collectively referred to as transport proteins, and they function as either channels for the material or as carriers themselves. Channel proteins have hydrophilic domains exposed to the intracellular and extracellular fluids and a hydrophilic channel through their core that provides a hydrated opening for solutes to pass through the membrane layers. Passage through the channel allows...
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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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Determining Membrane Protein Topology Using Fluorescence Protease Protection (FPP)
08:14

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Published on: April 20, 2015

Enhanced membrane protein topology prediction using a hierarchical classification method and a new scoring function.

Allan Lo1, Hua-Sheng Chiu, Ting-Yi Sung

  • 1Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan.

Journal of Proteome Research
|December 18, 2007
PubMed
Summary

Predicting transmembrane protein structure is crucial. This study introduces a new computational method using support vector machines (SVMs) to accurately determine transmembrane helix location and protein topology, aiding proteome annotation.

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Structural Biology

Background:

  • Predicting transmembrane (TM) helix and topology is vital for understanding membrane protein structure and function.
  • Experimental determination of high-resolution membrane protein models is challenging, necessitating computational approaches.

Purpose of the Study:

  • To develop and evaluate a novel hierarchical classification method for predicting TM helix location and protein topology.
  • To improve the accuracy of computational methods for membrane protein structure prediction.

Main Methods:

  • Utilized support vector machines (SVMs) with integrated features capturing sequence-to-structure relationships.
  • Developed a new scoring function based on membrane protein folding principles.
  • Employed cross-validation on low- and high-resolution datasets for evaluation.

Main Results:

  • Achieved up to 90% accuracy in topology (sidedness) prediction.
  • Correctly predicted TM helix locations and topology for 69% of a low-resolution benchmark set.
  • Demonstrated high discrimination between soluble and membrane proteins with very low false positive (0.5%) and false negative (0-1.2%) rates.

Conclusions:

  • The developed SVM-based method accurately predicts TM helix location and protein topology.
  • The complexity of topogenesis differs between single-spanning and multispanning TM proteins, with interloop interactions being key for the latter.
  • This method facilitates membrane proteome annotation for structural and functional insights.