Related Experiment Video
Updated: Jan 20, 2026

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
Published on: July 8, 2025
I-TASSER gateway: A protein structure and function prediction server powered by XSEDE
Wei Zheng1, Chengxin Zhang1, Eric W Bell1
1Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109-2218, United States.
The I-TASSER gateway offers automated protein structure and function prediction, bridging the gap between sequence data and experimental characterization. This computational tool aids researchers by providing reliable structural models and functional insights from protein sequences.
Area of Science:
- * Bioinformatics
- * Computational Biology
- * Structural Biology
Background:
- * Growing disparity between known protein sequences and experimentally determined structures/functions.
- * Need for efficient, automated methods to predict protein attributes.
Purpose of the Study:
- * Introduce the I-TASSER gateway for automated protein structure and function prediction.
- * Detail the integration of the I-TASSER pipeline with the XSEDE Gateway system and XSEDE-Comet supercomputer.
- * Provide an overview of the I-TASSER methodology and its developmental progress.
Main Methods:
- * Template recognition using known structure libraries.
- * Full-length atomic model construction via iterative assembly simulations of structural fragments.
- * Functional prediction through comparative analysis with known protein functions.
Main Results:
- * Development of the I-TASSER gateway for reliable protein structure and function prediction.
- * Integration with XSEDE Gateway and XSEDE-Comet to enhance computational capacity and user accessibility.
- * Demonstrated utility in addressing the challenge of predicting protein attributes from sequences.
Conclusions:
- * The I-TASSER gateway provides a robust solution for automated protein structure and function prediction.
- * Integration with high-performance computing resources like XSEDE-Comet improves scalability and accessibility.
- * The tool aids in alleviating the bottleneck in structural and functional annotation of the proteome.
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