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Simulation of the Protein Folding Process

  • Roterman Irena
  • L. Konieczny
  • M. Banach
  • D. Marchewka
  • B. Kalinowska
  • Z. Baster
  • M. Tomanek
  • M. Piwowar
Part of the Springer Series in Bio-/Neuroinformatics book series (SSBN, volume 1)

Abstract

This chapter introduces a novel protein folding simulation model which involves several stages. In particular, it distinguishes the so-called early stage (ES) and late state (LS) intermediates, though it can also account for a greater number of intermediates or — alternatively — using ES as the sole intermediate. The early stage intermediate is generated by geometric modeling of polypeptide bond chains, expressed as pairs of their relative binding angles (V-angle) and radii of curvature (R - which is dependent on V). Results of this process point to a limited conformational subspace, providing a convenient set of starting structures for subsequent free internal energy optimization algorithms. The late stage folding model acknowledges the influence of water on the folding process, with hydrophobic residues directed toward the center of the emerging protein body and hydrophilic residues exposed on its surface. Overall, the structure of the protein’s hydrophobic core can be modeled with a 3D Gauss function (hence the “fuzzy oil drop” designation). The presented algorithm reflects the influence of the aqueous environment on the protein’s structure as addition to the optimization of its internal free energy components.

Applying information theory concepts to the process of structural modeling justifies the need for a limited conformational subspace, comprising selected fragments of the Ramachandran map. Comparing the quantity of information present in the initial amino acid sequence with the quantity of information required to accurately describe the resulting 3D structure (pairs of Φ and Ψ angles) reveals a deficit and therefore calls for an additional source of information. We postulate that this information is contributed by the aqueous environment which triggers the generation of a hydrophobic core. In addition, deviations from the idealized “fuzzy oil drop” structure are found to correspond to active sites capable of binding ligands or forming protein complexes. Multicriteria optimization concept is applied to strike a balance between internal and external (environmental) optimization.

Keywords

Hydrophobic Core Folding Process Folding Simulation Hydrophobicity Profile Elliptical Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Roterman Irena
    • 1
  • L. Konieczny
    • 2
  • M. Banach
    • 3
  • D. Marchewka
    • 3
  • B. Kalinowska
    • 3
  • Z. Baster
    • 4
  • M. Tomanek
    • 5
  • M. Piwowar
    • 1
  1. 1.Department of Bioinformatics and Telemedicine – Medical CollegeJagiellonian UniversityKrakowPoland
  2. 2.Chair of Medical Biochemistry - Medical CollegeJagiellonian UniversityKrakówPoland
  3. 3.Faculty of Physics, Astronomy and Applied Computer ScienceJagiellonian UniversityKrakówPoland
  4. 4.Faculty of Physics AGHUniversity of Science and TechnologyKrakówPoland
  5. 5.Academic Computer CenterAGHKrakówPoland

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