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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Balance between alpha and beta structures in ab initio protein folding.

Robert B Best1, Jeetain Mittal

  • 1Department of Chemistry, Cambridge University, Lensfield Road, Cambridge CB2 1EW, UK. rbb24@cam.ac.uk

The Journal of Physical Chemistry. B
|June 12, 2010
PubMed
Summary

This study optimized a protein force field to accurately predict peptide folding structures. The modified force field shows promise for simulating diverse protein classes, despite some limitations in modeling unfolded states.

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Area of Science:

  • Computational chemistry
  • Biophysics
  • Molecular dynamics

Background:

  • Current protein force fields often exhibit bias towards specific secondary structures (alpha-helices or beta-sheets).
  • This structural bias necessitates careful selection of force fields based on the target protein's class.
  • Developing a transferable force field is crucial for accurate protein folding simulations.

Purpose of the Study:

  • To evaluate a modified Amber ff03 force field, optimized for helical propensity, in simulating peptide folding.
  • To assess the force field's ability to accurately reproduce native structures and equilibrium folding distributions for peptides with distinct secondary structure preferences.
  • To investigate the transferability of the modified force field across different protein structural classes.

Main Methods:

  • Extensive replica exchange molecular dynamics (REMD) simulations were performed.
  • Simulations started from completely unfolded peptide configurations.
  • The modified Amber ff03 force field was employed, incorporating backbone corrections.
  • Structural analysis included root-mean-square deviation (RMSD) calculations and comparison with experimental data.

Main Results:

  • The modified force field successfully predicted the native folded structures for both alpha-helical (Trp cage) and beta-hairpin (GB1 hairpin) peptides with high accuracy (<1.5 Å all-atom RMSD).
  • Converged equilibrium folding distributions were obtained, showing good agreement with experimental folded state populations at ~300 K.
  • Experimental data (NMR, FRET) indicated that while folded structures were well-reproduced, the unfolded states were slightly too compact and structured.

Conclusions:

  • The backbone correction in the modified Amber ff03 force field enhances its accuracy for peptide folding simulations.
  • The optimized force field demonstrates improved transferability, enabling accurate simulation of proteins with diverse secondary structure compositions.
  • Further refinement may be needed to fully capture the dynamics and conformational ensemble of unfolded protein states.