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Methods for the Refinement of Protein Structure 3D Models.

Recep Adiyaman1, Liam James McGuffin2

  • 1School of Biological Sciences, University of Reading, Reading RG6 6AS, UK. r.adiyaman@pgr.reading.ac.uk.

International Journal of Molecular Sciences
|May 12, 2019
PubMed
Summary

Refining predicted 3D protein models is essential for computational studies. Current methods face challenges in accurately selecting the most native-like conformations from generated models.

Keywords:
Critical Assessment of techniques for Structure Prediction (CASP)energy functionsmodel quality estimatesmolecular dynamics simulationsprotein model refinementtertiary structure prediction

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Biophysics

Background:

  • Accurate 3D protein models are vital for downstream computational analyses.
  • Current refinement strategies struggle to consistently improve initial model accuracy.
  • Deviations from native structures can occur due to force-field limitations.

Purpose of the Study:

  • To enhance the accuracy of predicted 3D protein models.
  • To address challenges in distinguishing near-native conformations during refinement.
  • To improve the selection of the most biologically relevant protein structures.

Main Methods:

  • Utilizing Molecular Dynamics (MD)-based protocols for sampling improved 3D models.
  • Employing physics-based force fields and targeted restraint strategies to guide refinement.
  • Integrating energy functions and Model Quality Assessment Programs (MQAPs) for scoring and discrimination.

Main Results:

  • MD-based protocols with smart restraints show progress in consistent 3D model refinement.
  • Physics-based force fields aid in generating more accurate protein structures.
  • MQAPs assist in differentiating near-native from non-native conformations.

Conclusions:

  • Refining 3D protein models remains challenging due to subtle differences between conformations.
  • Accurate prediction of local errors and contacts can guide effective restraint strategies.
  • Identifying the most native-like conformations is a critical ongoing challenge in structural bioinformatics.