I-TASSER (Iterative Threading ASSEmbly Refinement) is a

bioinformatics Bioinformatics () is an interdisciplinary field of science that develops methods and Bioinformatics software, software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, ...

method for predicting

three-dimensional In geometry, a three-dimensional space (3D space, 3-space or, rarely, tri-dimensional space) is a mathematical space in which three values (''coordinates'') are required to determine the position (geometry), position of a point (geometry), poi ...

structure model of protein molecules from amino acid sequences. It detects structure templates from the

Protein Data Bank The Protein Data Bank (PDB) is a database for the three-dimensional structural data of large biological molecules such as proteins and nucleic acids, which is overseen by the Worldwide Protein Data Bank (wwPDB). This structural data is obtained a ...

by a technique called fold recognition (or threading). The full-length structure models are constructed by reassembling structural fragments from threading templates using replica exchange Monte Carlo simulations. I-TASSER is one of the most successful

protein structure prediction Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its Protein secondary structure, secondary and Protein tertiary structure, tertiary structure ...

methods in the community-wide CASP experiments. Following the structure prediction, I-TASSER has a component for structure-based protein function prediction, which provides annotations on

ligand In coordination chemistry, a ligand is an ion or molecule with a functional group that binds to a central metal atom to form a coordination complex. The bonding with the metal generally involves formal donation of one or more of the ligand's el ...

binding site In biochemistry and molecular biology, a binding site is a region on a macromolecule such as a protein that binds to another molecule with specificity. The binding partner of the macromolecule is often referred to as a ligand. Ligands may includ ...

, gene ontology and enzyme commission by structurally matching structural models of the target protein to the known proteins in protein function databases. It has an on-line server built in th
Yang Zhang Lab
at the

National University of Singapore The National University of Singapore (NUS) is a national university, national Public university, public research university in Singapore. It was officially established in 1980 by the merging of the University of Singapore and Nanyang University ...

, allowing users to submit sequences and obtain structure and function predictions. A standalone package of I-TASSER is available for download at th
I-TASSER website
A new version D-I-TASSER, extended from I-TASSER, was recently released. D-I-TASSER combines deep learning restraints with I-TASSER structural assembly simulations and generates models with substantially higher accuracy.

Ranking in CASP

I-TASSER (as 'Zhang-Server') has been consistently ranked as the top method in CASP, a community-wide experiment to benchmark the best structure prediction methods in the field of

protein folding Protein folding is the physical process by which a protein, after Protein biosynthesis, synthesis by a ribosome as a linear chain of Amino acid, amino acids, changes from an unstable random coil into a more ordered protein tertiary structure, t ...

and

. CASP takes place every two years since 1994. * No 1 in CASP7 (2006) * No 1 in CASP8 (2008)
Official ranking of CASP8 (164 targets)
* No 2 in CASP9 (2010)

* No 1 in CASP10 (2012)
Official ranking of CASP10 (127 targets)
* No 1 in CASP11 (2014)
Official ranking of CASP11 (126 targets)
* No 1 in CASP12 (2016)
Official ranking of CASP12 (96 targets)
* No 1 in CASP13 (2018)
Official ranking of CASP13 (112 targets)
* No 1 in CASP14 (2020)
Official ranking of CASP14 (96 targets)

Method and pipeline

I-TASSER is a template-based method for protein structure and function prediction. The pipeline consists of six consecutive steps: *1, Secondary structure prediction b
PSSpred
*2, Template detection by LOMETS *3, Fragment structure assembly using replica-exchange Monte Carlo simulation *4, Model selection by clustering structure decoys using SPICKER *5, Atomic-level structure refinement by fragment-guided molecular dynamics simulation (FG-MD) or ModRefiner *6, Structure-based biology function annotation by COACH

On-line Server

The I-TASSER server allows users to generate automatically protein structure and function predictions. *Input **Mandatory: ***Amino acid sequence with length from 10 to 1,500 residues **Optional (user can provide optionally restraints and templates to assist I-TASSER modeling): ***Contact restraints ***Distance maps ***Inclusion of special templates ***Exclusion of special templates ***Secondary structures *Output **Structure prediction: ***Secondary structure prediction ***Solvent accessibility prediction ***Top 10 threading alignment from LOMETS ***Top 5 full-length atomic models (ranked based on cluster density) ***Top 10 proteins in PDB which are structurally closest to the predicted models ***Estimated accuracy of the predicted models (including a confidence score of all models, predicted TM-score and RMSD for the first model, and per-residue error of all models) ***B-factor estimation **Function prediction: ***Enzyme Classification (EC) and the confidence score ***Gene Ontology (GO) terms and the confidence score ***Ligand-binding sites and the confidence score ***An image of the predicted ligand-binding sites

Standalone Suite

The I-TASSER Suite is a downloadable package of standalone computer programs, developed by the Yang Zhang Lab for protein structure prediction and refinement, and structure-based protein function annotations. Through the I-TASSER License, researchers have access to the following standalone programs: *I-TASSER: A standalone I-TASSER package for protein 3D structure prediction and refinement. *COACH: A function annotation program based on COFACTOR, TM-SITE and S-SITE. *COFACTOR: A program for ligand-binding site, EC number & GO term prediction. *TM-SITE: A structure-based approach for ligand-binding site prediction. *S-SITE: A sequence-based approach for ligand-binding site prediction. *LOMETS: A set of locally installed threading programs for meta-server protein fold-recognition. *MUSTER: A threading program to identify templates from a non-redundant protein structure library. *SPICKER: A clustering program to identify near-native protein model from structure decoys. *HAAD: A program for quickly adding hydrogen atoms to protein heavy-atom structures. *EDTSurf: A program to construct triangulated surfaces of protein molecules. *ModRefiner: A program to construct and refine atomic-level protein models from C-alpha traces. *NW-align: A robust program for protein sequence-to-sequence alignments by Needleman-Wunsch algorithm. *PSSpred: A highly accurate program for protein secondary structure prediction. *Library: I-TASSER structural and functional template library weekly updated and freely accessible to the I-TASSER users. Help documents *Instruction on how to download and install the I-TASSER Suite can be found a
README.txt

References

{{reflist, refs= {{cite journal , vauthors=Roy A, Kucukural A, Zhang Y , year=2010 , title=I-TASSER: a unified platform for automated protein structure and function prediction , journal=Nature Protocols , volume=5 , issue=4 , pages=725–738 , doi=10.1038/nprot.2010.5 , pmid=20360767 , pmc=2849174 {{cite journal , vauthors=Roy A, Yang J, Zhang Y , year=2012 , title=COFACTOR: An accurate comparative algorithm for structure-based protein function annotation , journal=Nucleic Acids Research , volume=40 , issue=Web Server issue , pages=W471–W477 , doi=10.1093/nar/gks372 , pmid=22570420 , pmc=3394312 {{cite journal , vauthors=Zhang C, Freddolino PL, Zhang Y , year=2017 , title=COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information , journal=Nucleic Acids Research , volume=45 , issue=W1 , pages=W291–W299 , doi=10.1093/nar/gkx366 , pmid= 28472402, pmc=5793808 {{cite journal , vauthors=Zheng W, Wuyun Q, Li Y, Liu Q, Zhou X, Peng C, Zhu Y, Freddolino L, Zhang Y , year=2025 , title=Deep-learning-based single-domain and multidomain protein structure prediction with D-I-TASSER , journal=Nature Biotechnology , doi=10.1038/s41587-025-02654-4 , doi-access=free {{cite journal , author=Moult, J, year=1995 , title=A large-scale experiment to assess protein structure prediction methods , journal=Proteins , volume=23 , issue=3 , pages=ii–iv , doi=10.1002/prot.340230303, display-authors=etal , pmid=8710822, url=https://zenodo.org/record/1229334 {{cite journal , author=Battey, JN, year=2007 , title=Automated server predictions in CASP7 , journal=Proteins , volume=69 , issue=Suppl 8 , pages=68–82 , pmid=17894354 , doi=10.1002/prot.21761, display-authors=etal, doi-access=free {{cite journal , vauthors=Wu S, Zhang Y , year=2007 , title=LOMETS: A local meta-threading-server for protein structure prediction , journal=Nucleic Acids Research , volume=35 , issue=10 , pages=3375–3382 , pmid=17478507 , pmc=1904280 , doi=10.1093/nar/gkm251 {{cite journal , vauthors=Swendsen RH, Wang JS , year=1986 , title=Replica Monte Carlo simulation of spin glasses , journal=Physical Review Letters , volume=57 , issue=21 , pages=2607–2609 , pmid=10033814 , doi=10.1103/physrevlett.57.2607, bibcode=1986PhRvL..57.2607S {{cite journal , vauthors=Zhang Y, Skolnick J , year=2004 , title=SPICKER: A Clustering Approach to Identify Near-Native Protein Folds , journal=Journal of Computational Chemistry , volume=25 , pages=865–871 , pmid=15011258 , doi=10.1002/jcc.20011 , issue=6 {{cite journal , vauthors=Zhang J, Liang Y, Zhang Y , year=2011 , title=Atomic-Level Protein Structure Refinement Using Fragment-Guided Molecular Dynamics Conformation Sampling , journal=Structure , volume=19 , issue=12 , pages=1784–1795 , pmid=22153501 , pmc=3240822 , doi=10.1016/j.str.2011.09.022 {{cite journal , vauthors=Xu D, Zhang Y , year=2011 , title=Improving the Physical Realism and Structural Accuracy of Protein Models by a Two-step Atomic-level Energy Minimization , journal=Biophysical Journal , volume=101 , issue=10 , pages=2525–2534 , pmid=22098752 , pmc=3218324 , doi=10.1016/j.bpj.2011.10.024, bibcode=2011BpJ...101.2525X {{cite journal , vauthors=Yang J, Roy A, Zhang Y , year=2013 , title=Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment , journal=Bioinformatics , volume=29 , issue=20 , pages=2588–2595 , pmid=23975762 , pmc=3789548 , doi=10.1093/bioinformatics/btt447 {{cite journal , vauthors=Yang J, Roy A, Zhang Y , year=2015 , title=The I-TASSER Suite: Protein structure and function prediction , journal=Nature Methods , volume=12 , issue=1 , pages=7–8 , pmid=25549265 , pmc=4428668 , doi=10.1038/nmeth.3213

External links

I-TASSER server homepageThe Yang Zhang LabCASP homepageHow to use on-line I-TASSER server for protein structure and function prediction
Structural bioinformatics software