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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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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.
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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 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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A Protocol for Computer-Based Protein Structure and Function Prediction
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Prediction of structural alphabet protein blocks using data mining.

Mirjana M Maljković1, Nenad S Mitić1, Alexandre G de Brevern2

  • 1Faculty of Mathematics, University of Belgrade, Studentski Trg 16, 11000, Belgrade, Serbia.

Biochimie
|February 10, 2022
PubMed
Summary
This summary is machine-generated.

Predicting protein structural alphabets (SAs) like Protein Blocks (PBs) from amino acid sequences is crucial for understanding protein structure and function. New models achieve 80% accuracy, significantly improving upon previous methods.

Keywords:
Amino acid sequenceDisorder predictorsMachine learningProtein blocksRepeatsSpider3

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Machine learning in protein science

Background:

  • 3D protein structures dictate biological functions.
  • Local protein conformations can be approximated by structural alphabets (SAs).
  • Protein Blocks (PBs) are a known SA, comprising 16 prototypes of five amino acids.

Purpose of the Study:

  • To develop accurate models for predicting Protein Blocks (PBs) from amino acid sequences.
  • To enhance the prediction accuracy of local protein conformations.

Main Methods:

  • Utilized data mining and machine learning algorithms for PB prediction.
  • Incorporated sequence information, Spider3 predictions, intrinsically disordered region predictors, and repeat-finding tools for model training.
  • Evaluated different classification algorithms, including CART and C5.0.

Main Results:

  • Achieved a maximum prediction accuracy of 80%, a substantial improvement over the previous 61% accuracy.
  • Identified varying attribute significance across different algorithms.
  • Found that incorporating intrinsically disordered region and repeat information improved PB prediction precision with the CART algorithm.

Conclusions:

  • Developed improved models for predicting Protein Blocks (PBs) from amino acid sequences.
  • Demonstrated the utility of integrating diverse sequence and structural property predictors.
  • Highlighted potential applications in protein structural modeling and computational protein design.