I-TASSER-MTD is a hierarchical protocol to predict structures and functions of
It first predicts the domain boundaries by
based on the deep-learning contact-map prediction and multiple threading alignments.
Next, the structure model of each individual domain is constructed independently
guided by the deep learning predicted spatial restraints.
Finally, the individual domain models are assembled into full-length structure by
under guidance of quaternary structural templates and deep-learning distance profiles.
Meanwhile, the protein functions at both domain level and full-chain level are annotated by
based on structures, sequences, and protein-protein interaction networks.
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I-TASSER-MTD On-line Server
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- Xiaogen Zhou, Wei Zheng, Yang Li, Robin Pearce, Chengxin Zhang, Eric W. Bell, Guijun Zhang, and Yang Zhang.
I-TASSER-MTD: A deep-learning based platform for multi-domain protein structure and function prediction,
Nature Protocols, 17: 2326–2353 (2022).
- Xiaogen Zhou, Jun Hu, Chengxin Zhang, Guijun Zhang, Yang Zhang.
Assembling multidomain protein structures through analogous global structural alignments.
Proceedings of the National Academy of Sciences, 116: 15930-15938 (2019).