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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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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
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Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function
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Protein structure optimization using improved simulated annealing algorithm on a three-dimensional AB off-lattice

Lizhong Zhang1, He Ma2, Wei Qian3

  • 1College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China; College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang 110142, China.

Computational Biology and Chemistry
|February 29, 2020
PubMed
Summary
This summary is machine-generated.

An improved simulated annealing algorithm enhances protein structure optimization. This method efficiently finds lower energy conformations for artificial and real protein sequences, outperforming previous approaches.

Keywords:
C(α)space-filling modelOff-lattice modelProtein folding conformationSimulated annealing

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Area of Science:

  • Computational biology
  • Biophysics
  • Bioinformatics

Background:

  • Protein structure prediction is crucial for understanding biological function.
  • Accurate protein structure optimization is computationally challenging.
  • Existing algorithms may struggle with complex energy landscapes.

Purpose of the Study:

  • To develop an improved simulated annealing (ISA) algorithm for protein structure optimization.
  • To enhance the efficiency and accuracy of protein folding simulations.
  • To provide a robust method for exploring protein conformational space.

Main Methods:

  • Developed an improved simulated annealing (ISA) algorithm using a 3D AB off-lattice model.
  • Implemented a general formula for initial solution generation and a multivariable disturbance term for neighborhood solutions.
  • Incorporated storage operations to prevent missing optimal solutions.
  • Utilized Cα space-filling models to represent protein folding conformations.

Main Results:

  • The ISA algorithm demonstrated superior performance in finding lower energies for artificial protein sequences compared to five previous methods.
  • For real protein sequences from the Protein Data Bank (PDB), the algorithm achieved energy conformations with Cα-Root Mean Square Deviation (RMSD) below 3.0 Å.
  • Cα space-filling models effectively simulated dynamic changes in protein folding at the atomic level.

Conclusions:

  • The proposed ISA algorithm is effective for protein structure optimization, offering improved accuracy and efficiency.
  • The method provides reliable energy conformations for real protein structures, comparable to experimental data.
  • Cα space-filling models offer a valuable tool for visualizing and analyzing protein folding dynamics.