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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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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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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Protein structure prediction using the evolutionary algorithm USPEX.

Pavel Rachitskii1, Ivan Kruglov1,2, Alexei V Finkelstein3,4,5

  • 1Moscow Institute of Physics and Technology, Dolgoprudny, Russia.

Proteins
|February 13, 2023
PubMed
Summary
This summary is machine-generated.

We enhanced the USPEX evolutionary algorithm for accurate protein tertiary structure prediction from amino acid sequences. Our method shows competitive performance against deep learning approaches, finding stable protein conformations with high accuracy.

Keywords:
USPEXevolutionary algorithmprotein foldingprotein structure predictionvariation operator

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Area of Science:

  • Biophysics
  • Computational Biology
  • Structural Biology

Background:

  • Protein structure prediction remains a significant challenge in biophysics.
  • Classical methods often lag behind deep learning in predicting stable protein conformations.
  • Accurate prediction requires robust global optimization and reliable energy evaluation.

Purpose of the Study:

  • To extend the USPEX evolutionary algorithm for de novo protein structure prediction.
  • To compare the performance of various force fields in protein structure prediction.
  • To develop novel variation operators for enhanced protein structure modeling within USPEX.

Main Methods:

  • Global optimization using the extended USPEX evolutionary algorithm.
  • Protein structure relaxation and energy calculations with Tinker and Rosetta (REF2015).
  • Development of novel variation operators for generating new protein structure models.

Main Results:

  • The enhanced USPEX algorithm accurately predicted tertiary structures for seven test proteins.
  • USPEX found protein structures with energies comparable or lower than Rosetta Abinitio.
  • Force fields showed limitations in accurate blind prediction without experimental validation.

Conclusions:

  • The extended USPEX algorithm is a powerful tool for accurate protein tertiary structure prediction.
  • USPEX demonstrates effectiveness in identifying deep energy minima.
  • Current force fields require further refinement for precise blind protein structure prediction.