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Related Concept Videos

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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Conservation of Protein Domains Over Different Proteins02:26

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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.
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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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Protein Networks02:26

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Conserved Binding Sites01:49

Conserved Binding Sites

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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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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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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Algorithms for protein design.

Pablo Gainza1, Hunter M Nisonoff1, Bruce R Donald2

  • 1Department of Computer Science, Duke University, Durham, NC, United States.

Current Opinion in Structural Biology
|April 18, 2016
PubMed
Summary
This summary is machine-generated.

Computational protein design uses algorithms and biophysical models to create new proteins. Recent algorithmic advances allow for more accurate models, improving protein design success for therapeutics and assemblies.

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Area of Science:

  • Molecular Biology
  • Computational Biology
  • Protein Engineering

Background:

  • Computational structure-based protein design is a key tool in molecular biology.
  • Programs predict protein sequences for specific structures and functions.
  • Program success depends on biophysical models and algorithms.

Purpose of the Study:

  • Review recent algorithmic developments in computational protein design.
  • Highlight how new algorithms facilitate more accurate biophysical models.
  • Identify future algorithmic challenges for designing therapeutic proteins and assemblies.

Main Methods:

  • Review of recent literature on algorithms for computational protein design.
  • Emphasis on the interplay between algorithmic advancements and biophysical model accuracy.
  • Analysis of algorithmic challenges relevant to therapeutic protein and assembly design.

Main Results:

  • Novel algorithms are enabling the use of more sophisticated and accurate biophysical models.
  • Improvements in algorithms are crucial for enhancing the success rate of protein design programs.
  • Algorithmic progress directly impacts the ability to design proteins with desired functions.

Conclusions:

  • Simultaneous improvement of biophysical models and algorithms is essential for advancing protein design.
  • Specific algorithmic challenges remain for designing therapeutic proteins and complex protein assemblies.
  • Future research should focus on addressing these algorithmic challenges to unlock new protein design capabilities.