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Related Concept Videos

Protein Organization01:24

Protein Organization

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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
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The homogenate obtained after cell lysis contains various membrane-bound organelles that can be further separated into pure fractions by subcellular fractionation. These isolates are used to study specific cellular components, analyze localized protein activity, and are even employed in diagnostics. Fractionation is typically achieved using centrifugation methods, the most common being density-gradient and differential centrifugation.
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Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
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Overview of Protein Sorting and Transport01:45

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Eukaryotic cells have different membrane-bound organelles with distinct protein requirements. The process by which proteins are targeted to a specific organelle is called protein sorting.
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Enriching Subcellular Proteins in Leptospira Using a Triton X-114-Based Fractionation Approach
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Improving Protein Subcellular Location Classification by Incorporating Three-Dimensional Structure Information.

Ge Wang1,2,3, Yu-Jia Zhai4, Zhen-Zhen Xue1,2,3,5

  • 1School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.

Biomolecules
|November 27, 2021
PubMed
Summary

This study explores using protein 3D structures, not just sequences, to predict subcellular locations. Incorporating structural features improves prediction accuracy, offering new insights into protein spatial distribution and function.

Keywords:
deep learninggraph neural networkprotein data bankprotein structuresubcellular location prediction

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Area of Science:

  • Proteomics
  • Structural Biology
  • Bioinformatics

Background:

  • Protein subcellular localization is crucial for function.
  • Machine learning for protein localization often relies solely on amino acid sequences.
  • Protein 3D structures offer richer functional information but are underutilized.

Purpose of the Study:

  • To investigate the utility of protein 3D structural features for predicting subcellular localization.
  • To enhance existing sequence-based protein localization prediction methods.

Main Methods:

  • Extracted handcrafted features (physical, chemical, topological) from protein 3D structures.
  • Utilized deep neural networks to learn structural features.
  • Employed these features in machine learning models for subcellular location classification.

Main Results:

  • Certain structural features significantly impact protein location classification accuracy.
  • The inclusion of structural features improves upon sequence-based prediction performance.
  • Demonstrated the value of 3D structural data in proteomics.

Conclusions:

  • Protein 3D structure is a valuable data source for improving subcellular localization prediction.
  • This approach offers a novel perspective for analyzing protein spatial distribution.
  • Findings may aid in understanding the link between protein structure and function.