Assessment of Detection and Refinement Strategies for de novo Protein Structures using Force Field and Statistical Potentials

Abstract

De novo predictions of protein structures at high resolution are challenged by the problem of detecting the native conformation from false energy minima. In this work, we provide an assessment of various detection and refinement protocols on a small subset of the second-generation all-atom Rosetta decoy set (Tsai, et al. Proteins 2003, 53, 76-87) by using an all-atom force field and a heavy-atom statistical potential. Detection schemes include minimization followed by conformational scoring and short-time molecular dynamics simulations. Refinement methods include temperature-based replica exchange molecular dynamics and a new computational unfold/refold procedure. Our results indicate that simple detection without any refinement is the best protocol for finding most native-like structures in the decoy set. The refinement techniques that we tested were generally unsuccessful in improving detection; however, they provided marginal improvements to some of the decoy structures.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2007
Accession Number
ADA468130

Entities

People

  • Mark A Olson
  • Michael S. Lee

Organizations

  • United States Army Medical Research Institute of Infectious Diseases

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Application Software
  • Biomedical Research
  • Computational Science
  • Computations
  • Computer Science
  • Demographic Cohorts
  • Dynamics
  • Free Energy
  • High Resolution
  • Information Science
  • Molecular Dynamics
  • Molecular Mechanics Methods
  • Probability
  • Sampling
  • Simulations
  • X Rays

Readers

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