I-TASSER server for protein 3D structure prediction

By Yang Zhang. 2008

1,041 citations recorded by the source corpus.

BackgroundPrediction 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.ResultsAn 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 Å for RMSD.ConclusionThe I-TASSER server has been developed to generate automated full-length 3D protein structural predictions where the benchmarked scoring system helps users to obtain quantitative assessments of the I-TASSER models. The output of the I-TASSER server for each query includes up to five full-length models, the confidence score, the estimated TM-score and RMSD, and the standard deviation of the estimations. The I-TASSER server is freely available to the academic community at http://zhang.bioinformatics.ku.edu/I-TASSER.

Subfields: Molecular Biology

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Citations in the corpus

GPCR-I-TASSER: A hybrid approach to G protein-coupled receptor structure modeling and the application to the human genome (2015, methodology): “91) to the actual TM-score of the predicted models based on large-scale benchmark tests (Zhang, 2008).”
Recognizing protein-ligand binding sites by global structural alignment and local geometry refinement (2012, positive): “Starting from the query sequence, the 3D structure model is first generated using the I-TASSER fragment assembly simulations (Roy et al., 2010; Zhang, 2008).”
Protein model discrimination using mutational sensitivity derived from deep sequencing. (2012, methodology): “For these four proteins (70–90 residues length), 2 3 104 decoys were generated individually using I-TASSER.”
Fast and accurate automatic structure prediction with HHpred (2009, methodology): “To keep it fast, no alternative alignments are explored [4, 5, 6, 7, 15], no side chain optimization performed [4, 5, 6, 7], no contacts predicted [4, 5, 6, 7], no loops modeled [ 4 , 5, 6, 7], and no model quality assessment or structural clustering employed to pick the best of several models [4, 5”
An Integrated Framework Advancing Membrane Protein Modeling and Design (2015, methodology): “MPrelax can also be used in combination with a contact prediction method to predict structures with low sequence similarities to their template (similar to I-TASSER [68,69]).”
Evaluating the absolute quality of a single protein model using structural features and support vector machines (2009, background): “1,5–23 Most of these methods are relative scoring methods designed to discriminate near-native structures from decoys.”
Protein Structure Prediction: Is It Useful? (2009, methodology): “The actual supply and demand are partly reflected by the popularity of online structure prediction servers [31], for example, the ITASSER server [19 ] alone has generated full-length structure predictions for more than 20 000 unknown proteins submitted by about 2000 registered scientists during the ”
I-TASSER: a unified platform for automated protein structure and function prediction (2010, methodology): “The C -score scheme has been extensively tested in large-scale benchmarking test”
Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement (2011, background): “20,21 For I-TASSER,22– 24 although the reassembly of structural fragments excised from the threading alignments often results in significantly improved models, the quality of final models is still essentially dependent on that of threading templates identified in the PDB library.”