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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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Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
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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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Related Experiment Video

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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How good are simplified models for protein structure prediction?

Swakkhar Shatabda1, M A Hakim Newton2, Mahmood A Rashid1

  • 1Institute for Integrated and Intelligent Systems (IIIS), Griffith University, 170 Kessels Road, Nathan, QLD 4111, Australia ; Queensland Research Laboratory, National ICT of Australia (NICTA), GPO Box 2434, Brisbane, QLD 4001, Australia.

Advances in Bioinformatics
|May 31, 2014
PubMed
Summary

Protein structure prediction models face challenges with simplified energy functions. This study shows lattice models can closely fit native structures, but many popular energy models are weak for guiding accurate protein structure prediction.

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Area of Science:

  • Computational Biology
  • Biophysics
  • Structural Bioinformatics

Background:

  • Protein structure prediction (PSP) is a long-standing challenge due to atomic complexity and unknown energy functions.
  • Simplified lattice models are often used, but their accuracy in representing native structures and guiding search is questioned.
  • Assessing the validity of lattice-based energy models is crucial for advancing PSP.

Purpose of the Study:

  • To evaluate if native protein structures can be accurately represented on discrete lattices.
  • To assess the effectiveness of contact-based energy models in guiding protein structure prediction on lattices.
  • To identify weaknesses in commonly used energy models for PSP.

Main Methods:

  • Developed a constraint-based local search algorithm for the protein chain lattice fitting (PCLF) problem on cubic and face-centered cubic lattices.
  • Employed various techniques to sample protein conformation space.
  • Correlated energy functions with root mean square deviation (RMSD) of lattice-based structures against native structures.

Main Results:

  • Achieved very close lattice fits for native protein structures using the PCLF algorithm.
  • Identified significant weaknesses in several popular contact-based energy models used in PSP.
  • Demonstrated that current lattice-based energy models may not reliably guide the search towards native structures.

Conclusions:

  • Lattice models can provide accurate representations of native protein structures.
  • Many widely used contact-based energy functions exhibit limitations in guiding accurate protein structure prediction.
  • Further development of energy models is necessary for effective lattice-based PSP.