articleBMC BioinformaticsJan 23, 2008GOLD OA

I-TASSER server for protein 3D structure prediction

University of Kansas

PubMed
Indexed incrossrefdoajpubmed

Abstract

Background

Prediction of 3-dimensional protein structures from amino acid sequences represents one of the most important problems in computational structural biology. The community-wide Critical Assessment of Structure Prediction (CASP) experiments have been designed to obtain an objective assessment of the state-of-the-art of the field, where I-TASSER was ranked as the best method in the server section of the recent 7th CASP experiment. Our laboratory has since then received numerous requests about the public availability of the I-TASSER algorithm and the usage of the I-TASSER predictions.

Results

An on-line version of I-TASSER is developed at the KU Center for Bioinformatics which has generated protein structure predictions for thousands of modeling requests from more than 35 countries. A scoring function (C-score) based on the relative clustering structural density and the consensus significance score of multiple threading templates is introduced to estimate the accuracy of the I-TASSER predictions. A large-scale benchmark test demonstrates a strong correlation between the C-score and the TM-score (a structural similarity measurement with values in [0, 1]) of the first models with a correlation coefficient of 0.91. Using a C-score cutoff > -1.5 for the models of correct topology, both false positive and false negative rates are below 0.1. Combining C-score and protein length, the accuracy of the I-TASSER models can be predicted with an average error of 0.08 for TM-score and 2 A for RMSD.

Citation impact

5,218
total citations
FWCI
51.24
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100%
References
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Citations per year

Authors

1

Topics & keywords

Keywords
  • CASP
  • Protein structure prediction
  • Threading (protein sequence)
  • Computer science
  • Structural bioinformatics
  • Benchmark (surveying)
  • Cluster analysis
  • Protein structure
UN Sustainable Development Goals
  • Partnerships for the goals
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