Computational Solutions to the Protein Folding Problem,

Abstract

The protein folding problem attempts to predict the native, or folded, state of a protein in three-dimensional space, given its primary sequence of amino acids. One common approach for a solution is to treat each complex amino acid as a single sphere, or united atom, and to model each peptide linkage between residues by a virtual bond between spheres. Computational efforts being examined rely on two major assumptions: for any specific molecular conformation, a corresponding potential energy function can be computed, and the three-dimensional, folded state corresponds to the global minimum of this energy function. The optimization method being used to minimize the potential energy involves collecting a large number of conformers, each attained by finding a local minimum of the potential energy function from a random starting point. The information from these conformers is then used to form a convex quadratic global underestimating function for the potential energy of the known conformers. The minimum of this underestimator is used to predict the global minimum for the function, allowing a localized conformer search to be performed based on the predicted minimum. The new set of conformers generated by the localized search can serve as the basis for another quadratic underestimation. After several repetitions, the global minimum can be found with reasonable assurance. The conformer which lies at the global minimum represents the three-dimensional folded state of the molecule. Protein folding problem, Global underestimator, Conformer, Mathematical models

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Document Details

Document Type
Technical Report
Publication Date
May 19, 1994
Accession Number
ADA284911

Entities

People

  • Vann H. Walke

Organizations

  • United States Naval Academy

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Amino Acids
  • Cartesian Coordinates
  • Computational Fluid Dynamics
  • Computational Science
  • Computer Science
  • Computer Simulations
  • Energy
  • Geometry
  • Linear Programming
  • Mathematical Models
  • Molecules
  • Optimization
  • Potential Energy
  • Sequences
  • Three Dimensional
  • United States Naval Academy

Readers

  • Computational Modeling and Simulation
  • Molecular Genetics
  • Statistical inference.

Technology Areas

  • Space