Computational Prediction of Protein Secondary Structure from Sequence

Fanchi Meng1, Lukasz Kurgan2

1 Department of Electrical and Computer Engineering, University of Alberta, Edmonton, 2 Department of Computer Science, Virginia Commonwealth University, Richmond, Virginia
Publication Name:  Current Protocols in Protein Science
Unit Number:  Unit 2.3
DOI:  10.1002/cpps.19
Online Posting Date:  November, 2016
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Secondary structure of proteins refers to local and repetitive conformations, such as α‐helices and β‐strands, which occur in protein structures. Computational prediction of secondary structure from protein sequences has a long history with three generations of predictive methods. This unit summarizes several recent third‐generation predictors. We discuss their inputs and outputs, availability, and predictive performance and explain how to perform and interpret their predictions. We cover methods for the prediction of the 3‐class secondary structure states (helix, strand, and coil) as well as the 8‐class secondary structure states. Recent empirical assessments and our small‐scale analysis reveal that these predictions are characterized by high levels of accuracy, between 70% and 80%. We emphasize that modern predictors are available to end users in the form of convenient‐to‐use Web servers and stand‐alone software. © 2016 by John Wiley & Sons, Inc.

Keywords: coil; DSSP; helix; secondary structure of proteins; strand; prediction

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Table of Contents

  • Introduction
  • Prediction of Secondary Structure from Sequence
  • Summary
  • Acknowledgements
  • Literature Cited
  • Figures
  • Tables
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Key References
  Chen and Kurgan, 2013. See above.
  Provides description and detailed discussion of key architectural details of a large number of modern predictors of secondary structure.
  Jones, 1999. See above.
  A classic reading that describes the most commonly used PSIPRED method for the prediction of the 3‐class SS.
  Kabsch and Sander, 1983. See above.
  Describes the most commonly used method for the assignment of secondary structure from the tertiary protein structure.
  Magnan and Baldi, 2014. See above.
  Describes SSpro, one of the most popular and accurate methods for the prediction of the 8‐class SS.
  Zhang et al., 2011. See above.
  Provides comprehensive empirical assessment of predictive performance of modern methods for the prediction of secondary structure.
Internet Resources
  PSIPRED Web server.
  SSpro Web server.
  PSSpred Web server.
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