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Prediction of Protein Tertiary Structures Using MUFOLD

  • Jingfen Zhang
  • Zhiquan He
  • Qingguo Wang
  • Bogdan Barz
  • Ioan Kosztin
  • Yi Shang
  • Dong Xu
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 815)

Abstract

There have been steady improvements in protein structure prediction during the past two decades. However, current methods are still far from consistently predicting structural models accurately with computing power accessible to common users. To address this challenge, we developed MUFOLD, a hybrid method of using whole and partial template information along with new computational techniques for protein tertiary structure prediction. MUFOLD covers both template-based and ab initio predictions using the same framework and aims to achieve high accuracy and fast computing. Two major novel contributions of MUFOLD are graph-based model generation and molecular dynamics ranking (MDR). By formulating a prediction as a graph realization problem, we apply an efficient optimization approach of Multidimensional Scaling (MDS) to speed up the prediction dramatically. In addition, under this framework, we enhance the predictions consistently by iteratively using the information from generated models. MDR, in contrast to widely used static scoring functions, exploits dynamics properties of structures to evaluate their qualities, which can often identify best structures from a pool more effectively.

Key words

Protein structure prediction Multidimensional scaling Molecular dynamics simulation 

Notes

Acknowledgments

This work has been supported by National Institutes of Health Grant R21/R33-GM078601. Major computing resource was provided by the University of Missouri Bioinformatics Consortium. We like to thank Jianlin Cheng, Yang Zhang, and Joel L. Sussman for helpful discussions.

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Jingfen Zhang
    • 1
  • Zhiquan He
    • 1
  • Qingguo Wang
    • 1
  • Bogdan Barz
    • 2
  • Ioan Kosztin
    • 2
  • Yi Shang
    • 1
  • Dong Xu
    • 3
  1. 1.Department of Computer ScienceUniversity of MissouriColumbiaUSA
  2. 2.Department of Physics and AstronomyUniversity of MissouriColumbiaUSA
  3. 3.Department of Computer ScienceUniversity of Missouri-ColumbiaColumbiaUSA

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