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A Protocol for Computer-Based Protein Structure and Function Prediction
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PROTHON: A Local Order Parameter-Based Method for Efficient Comparison of Protein Ensembles.

Adekunle Aina1, Shawn C C Hsueh1, Steven S Plotkin1,2

  • 1Department of Physics and Astronomy, The University of British Columbia, Vancouver, BC V6T 1Z1, Canada.

Journal of Chemical Information and Modeling
|May 13, 2023
PubMed
Summary

A new computational method, PROTHON, efficiently compares protein conformational ensembles using probability distribution functions. This approach is significantly faster and requires fewer computing resources than existing methods, aiding structural biology research.

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Biophysics

Background:

  • Comparing protein conformational ensembles is crucial in structural biology.
  • Existing computational methods like ENCORE are often too slow and resource-intensive for large datasets.

Purpose of the Study:

  • To develop an efficient computational method for representing and comparing protein conformational ensembles.
  • To address the limitations of existing computationally expensive methods.

Main Methods:

  • Representing protein ensembles as vectors of probability distribution functions (pdfs) for local structural properties.
  • Quantifying dissimilarity using the Jensen-Shannon distance between pdf sets.
  • Validating the method with molecular dynamics simulations of ubiquitin and experimental data for human tau protein.

Main Results:

  • The new method, PROTHON, demonstrated significant speed improvements, up to 88 times faster than ENCORE.
  • PROTHON utilized substantially fewer computing cores (48 times fewer) compared to ENCORE.
  • The method proved effective for both simulated and experimentally derived conformational ensembles.

Conclusions:

  • PROTHON offers a computationally efficient and effective approach for protein conformational ensemble comparison.
  • This method can accelerate research in structural biology by overcoming the limitations of current tools.
  • PROTHON is available as an open-source Python package.