I-TASSER: a unified platform for automated protein structure and function prediction

By Ambrish Roy, Alper Kucukural, Yang Zhang. Nature Protocols, 2010

494 citations recorded by the source corpus.

The iterative threading assembly refinement (I-TASSER) server is an integrated platform for automated protein structure and function prediction based on the sequence-to-structure-to-function paradigm. Starting from an amino acid sequence, I-TASSER first generates three-dimensional (3D) atomic models from multiple threading alignments and iterative structural assembly simulations. The function of the protein is then inferred by structurally matching the 3D models with other known proteins. The output from a typical server run contains full-length secondary and tertiary structure predictions, and functional annotations on ligand-binding sites, Enzyme Commission numbers and Gene Ontology terms. An estimate of accuracy of the predictions is provided based on the confidence score of the modeling. This protocol provides new insights and guidelines for designing of online server systems for the state-of-the-art protein structure and function predictions. The server is available at http://zhanglab.ccmb.med.umich.edu/I-TASSER.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/80b64b4bcc67d2d375e2914c5e4d263fd9c40365

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Citations in the corpus

rawMSA: End-to-end Deep Learning Makes Protein Sequence Profiles and Feature Extraction obsolete (2018, methodology): “…PSSM will not be as reliable and the prediction system may not be able to distinguish between a reliable and an unreliable PSSM. SS, RSA and similar properties are sometimes used as intermediate steps to constrain and help the prediction of more complex properties in a number of methods [33–35].”
The HDOCK server for integrated protein–protein docking (2020, methodology): “In those cases, users are recommended to use a specialized structure prediction method like I-TASSER 63 – 65 for structural modeling and then submit the modeled 3D structures to the HDOCK server for docking.”
Patterns of coevolving amino acids unveil structural and dynamical domains (2017, background): “…have also followed different routes: from the development of increasingly accurate force ﬁelds to be used in unbiased folding simulations (8, 9) to higher-level approaches where structural features are inferred from the sole physicochemical or statistical proﬁling of the primary sequence (32–36).”
Comprehending crystalline β-carotene accumulation by comparing engineered cell models and the natural carotenoid-rich system of citrus (2011, unknown): “The resultant plasmid has the”
SE(3)-Equivariant Energy-based Models for End-to-End Protein Folding (2021, methodology): “On the other hand, most structure prediction methods rely on traditional optimization toolkits, including Rosetta [33], I-TASSER [26], and CNS [5].”
Deep learning techniques have significantly impacted protein structure prediction and protein design. (2021, methodology): “The most successful TBM method is probably I-TASSER [8], which is an extension of TASSER and has been consistently ranked as the top automated method in the community-wide Critical Assessment of Structure Prediction (CASP) experiment, whose goal is to benchmark the state of the art in protein…”
STRUM: structure-based prediction of protein stability changes upon single-point mutation (2016, methodology): “I-TASSER is a hierarchical approach to protein structure prediction, which constructs full-length models by iteratively reassembling the structure fragments excised from the threading templates (Roy et al. , 2010; Yang et al. , 2015).”
TP53 copy number expansion is associated with the evolution of increased body size and an enhanced DNA damage response in elephants (2015, methodology): “…interface might disrupt a physical interaction between TP53RTG12 and TP53 we generated a homology model of the TP53RTG12/TP53 dimer using I-TASSER/ModRefiner (Roy et al., 2010; Xu and Zhang, 2011; Zhang, 2008) and the crystal structure of the TP53 tetramer as a template (Kitayner et al., 2006).”
Toward the solution of the protein structure prediction problem (2021, methodology): “For example, I-TASSER, which is an extension of TASSER, uses multiple templates identi ﬁ ed by LOMETS; compared with TASSER, the main difference of I-TASSER is that, following clustering of the low-energy decoys and selection of the cluster centroid, the centroid is searched through the PDB library ”
Protein Structure and Function Prediction Using I-TASSER (2015, methodology): “The details of the I-TASSER protocol have been described in several other publications (Wu et al., 2007; Zhang, 2007; Roy et al., 2010; Yang et al., 2015).”
Mechanisms and management of acaricide resistance for Tetranychus urticae in agroecosystems (2021, unknown): “urticae AChE model was generated by using the I-TASSER server (Roy et al. 2010) and the image was rendered with UCSF Chimera 1.”