Introduction

Accurate prediction of protein secondary structure is essential for accurate sequence alignment, three-dimensional structure modeling, and function prediction. The accuracy of ab initio secondary structure prediction from sequence, however, has only increased from around 77 to 80% over the past decade. Here, we developed a multistep neural-network algorithm by coupling secondary structure prediction with prediction of solvent accessibility and backbone torsion angles in an iterative manner. Our method called SPINE X was applied to a dataset of 2640 proteins (25% sequence identity cutoff) previously built for the first version of SPINE and achieved a 82.0% accuracy based on 10-fold cross validation (Q(3)). Surpassing 81% accuracy by SPINE X is further confirmed by employing an independently built test dataset of 1833 protein chains, a recently built dataset of 1975 proteins and 117 CASP 9 targets (critical assessment of structure prediction techniques) with an accuracy of 81.3%, 82.3% and 81.8%, respectively. The prediction accuracy is further improved to 83.8% for the dataset of 2640 proteins if the DSSP assignment used above is replaced by a more consistent consensus secondary structure assignment method. Comparison to the popular PSIPRED and CASP-winning structure-prediction techniques is made. SPINE X predicts number of helices and sheets correctly for 21.0% of 1833 proteins, compared to 17.6% by PSIPRED. It further shows that SPINE X consistently makes more accurate prediction in helical residues (6%) without over prediction while PSIPRED makes more accurate prediction in coil residues (3-5%) and over predicts them by 7%. SPINE X Server and its training/test datasets are available at http://sparks.informatics.iupui.edu/

Publications

  1. SPINE X: improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles.
    Cite this
    Faraggi E, Zhang T, Yang Y, Kurgan L, Zhou Y, 2012-01-01 - Journal of computational chemistry
  2. Fluctuations of backbone torsion angles obtained from NMR-determined structures and their prediction.
    Cite this
    Zhang T, Faraggi E, Zhou Y, 2010-12-01 - Proteins
  3. Predicting continuous local structure and the effect of its substitution for secondary structure in fragment-free protein structure prediction.
    Cite this
    Faraggi E, Yang Y, Zhang S, Zhou Y, 2009-11-01 - Structure (London, England : 1993)

Credits

  1. Eshel Faraggi
    Developer

    School of Informatics, Indiana University Purdue University, United States of America

  2. Tuo Zhang
    Developer

  3. Yuedong Yang
    Developer

  4. Lukasz Kurgan
    Developer

  5. Yaoqi Zhou
    Investigator

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Summary
AccessionBT000281
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Submitted ByYaoqi Zhou