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Related Concept Videos

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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 form...
Conserved Binding Sites01:49

Conserved Binding Sites

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.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Conserved Binding Sites01:49

Conserved Binding Sites

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.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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 form...
Protein and Protein Structure02:15

Protein and Protein Structure

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.
A protein's shape is critical to its function. For example, an enzyme can...
Protein Networks02:26

Protein Networks

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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

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Published on: July 25, 2013

New conformational search method using genetic algorithm and knot theory for proteins.

Y Sakae1, T Hiroyasu, M Miki

  • 1Department of Physics, Nagoya University, Nagoya, Aichi 464-8602, Japan. sakae@tb.phys.nagoya-u.ac.jp

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|December 2, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a novel computational method combining simulated annealing, genetic algorithms, and knot theory to find stable protein structures. The improved approach successfully avoids unnatural "knot" conformations in protein folding simulations.

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Area of Science:

  • Computational biology
  • Biophysics
  • Protein structure prediction

Background:

  • Protein conformational search is crucial for understanding protein function and designing new proteins.
  • Existing methods like simulated annealing with genetic crossover can find minimum energy structures but may produce unnatural "knot" conformations.
  • Knot theory provides a mathematical framework to identify and avoid complex topological structures.

Purpose of the Study:

  • To develop an improved protein conformational search method that prevents the formation of knot conformations.
  • To apply the enhanced method to a real protein system and validate its effectiveness.

Main Methods:

  • Developed a parallel simulated annealing algorithm incorporating genetic crossover.
  • Integrated knot theory principles into the conformational search algorithm to exclude knot structures.
  • Applied the refined method to predict the global minimum energy structure of Protein G (56 amino acids).

Main Results:

  • The enhanced method successfully avoided the generation of knot conformations during the simulation.
  • The algorithm efficiently searched the conformational space while adhering to topological constraints.
  • The study demonstrated the feasibility of using knot theory to refine protein structure prediction.

Conclusions:

  • Combining simulated annealing, genetic algorithms, and knot theory offers a powerful approach for accurate protein conformational searching.
  • This method enhances the reliability of protein structure prediction by eliminating biologically improbable knot formations.
  • The developed technique has significant implications for computational protein design and drug discovery.