I-TASSER Suite 5.2
I-TASSER Suite is a package of standalone computer programs,
developed for high-resolution protein structure prediction, refinement,
and structure-based function annotations.
A detailed instruction on how to download and install the Suite
can be found at
Please report bugs and questions at
I-TASSER message board and some members will study the
problems and answer them asap.
The I-TASSER Suite is free for academic and non-profit
Through the I-TASSER License, the researchers
have the access to the following standalone programs:
- I-TASSER: A standalone I-TASSER package for protein 3D structure
prediction and refinement.
- 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
- EDTSurf: A program to construct triangulated surfaces of protein
- 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.
- ResQ: An algorithm to estimate B-factor and
residue-level error of structural models.
The I-TASSER structural and functional template library
updated and freelly accessible to the I-TASSER users.
For academic users, please go to
I-TASSER download webpage
to download the I-TASSER Suite.
If you need I-TASSER Suite for a commercial use, please contact us through email@example.com.
J Yang, R Yan, A Roy, D Xu, J Poisson, Y Zhang.
The I-TASSER Suite: Protein structure and function prediction.
Nature Methods, 2015, 12: 7-8 (Download the PDF