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A protein structure prediction service using deep learning and comparative modeling.

Robetta is a protein structure prediction service leveraging both deep learning and comparative modeling techniques. At its core is RoseTTAFold, a deep learning-based method renowned for its speed and accuracy in predicting protein structures from sequence. The service offers an interactive submission interface that accommodates custom sequence alignments, homology modeling constraints, and local fragments. Robetta can model multi-chain complexes using either RoseTTAFold (requiring paired MSA) or comparative modeling (CM) approaches. The CM method utilizes the PDB100 template database, a co-evolution based model database (MDB), and allows for custom templates. Computing resources are provided by the Baker lab and Rosetta@home, a distributed computing project. The service facilitates large-scale sampling, making it valuable for research into protein function, drug discovery, and understanding biological mechanisms. Its architecture is designed to incorporate community contributions and leverage volunteer computing power.
Robetta is a protein structure prediction service leveraging both deep learning and comparative modeling techniques.
Explore all tools that specialize in homology modeling. This domain focus ensures Robetta delivers optimized results for this specific requirement.
Deep learning-based method for fast and accurate protein structure prediction, leveraging end-to-end differentiable learning.
Utilizes the PDB100 template database and co-evolution based model database (MDB) for homology modeling.
Capable of modeling protein complexes using RoseTTAFold (with paired MSA) or comparative modeling.
Allows users to supply their own templates for comparative modeling, enhancing accuracy in specific cases.
Provides options for extensive sampling, generating multiple models to explore conformational space.
1. Visit the Robetta website.
2. Create an account or use the service as a guest.
3. Prepare your input protein sequence in FASTA format.
4. Select the appropriate modeling method (RoseTTAFold or Comparative Modeling).
5. Submit your job with any custom constraints or templates.
6. Monitor the job status on the Robetta interface.
7. Download the predicted protein structure in PDB format.
8. Analyze the model statistics and assess the quality of the prediction.
All Set
Ready to go
Verified feedback from other users.
"Robetta provides accurate and reliable protein structure predictions, especially with RoseTTAFold, though turnaround times can vary."
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