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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.
The primary structure of a protein is its amino acid sequence....
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Protein and Protein Structure02:15

Protein and Protein Structure

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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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Protein-protein Interfaces02:04

Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Protein Families02:47

Protein Families

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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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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...
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Protein and Protein Structures02:15

Protein and Protein Structures

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Feature and Algorithm Selection Method for Improving the Prediction of Protein Structural Class.

Qianwu Ni1, Lei Chen1

  • 1College of Information Engineering, Shanghai Maritime University, Shanghai 201306. China.

Combinatorial Chemistry & High Throughput Screening
|March 16, 2017
PubMed
Summary

Accurate protein structural class prediction is crucial for understanding protein functions. This study introduces a novel method combining feature and algorithm selection to enhance prediction accuracy, outperforming existing models.

Keywords:
Protein structural class predictionalgorithm selectionensemble classifierfeature selectionminimum redundancy maximum relevanceoptimal ensemble prediction model

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Structural biology

Background:

  • Protein structural class prediction is vital for understanding protein functions, regulations, and interactions.
  • Existing computational methods face challenges in selecting optimal classification algorithms and essential features.

Purpose of the Study:

  • To develop an improved method for protein structural class prediction by integrating feature and algorithm selection.
  • To enhance the accuracy of predicting protein structural classes.

Main Methods:

  • Utilized amino acid composition and physiochemical features to represent proteins.
  • Employed the minimum redundancy maximum relevance (mRMR) method for feature selection.
  • Applied 38 machine learning algorithms and selected the best performing ensemble model.

Main Results:

  • The developed ensemble model significantly outperformed models using single algorithms.
  • The combined feature and algorithm selection approach yielded superior prediction accuracy.
  • The method demonstrated superiority over models relying solely on feature or algorithm selection.

Conclusions:

  • Feature selection and algorithm selection procedures are effective in improving ensemble prediction models.
  • The proposed method offers a robust approach for accurate protein structural class prediction.
  • This work contributes to advancing computational methods in structural bioinformatics.