RoseTTAFold
Level 22: Biology, Chemistry & Drug Discovery
Science · Level 22
In short
RoseTTAFold is an AI tool in the Biology & Medicine category from University of Washington (Baker Lab / RosettaCommons) in Seattle, United States. The pricing model is open source. It is available in English only.
What is RoseTTAFold?
RoseTTAFold is an AI-powered protein structure prediction system developed by the Baker Lab at the University of Washington. The software employs deep neural networks to generate highly accurate 3D models of proteins directly from primary amino acid sequences. It utilizes a novel three-track architecture that concurrently processes sequence, residue-pair distance, and 3D coordinate information.
Compared to traditional experimental approaches like X-ray crystallography or cryo-electron microscopy, RoseTTAFold computes structural predictions in minutes or hours rather than months. Beyond individual protein monomers, the system excels at predicting complex protein-protein assemblies and nucleic acid interactions. This significantly accelerates the analysis of biological mechanisms in basic and applied research.
RoseTTAFold is accessible to the scientific community via the free Robetta web server and as open-source code for local deployment. Alongside DeepMind's AlphaFold, it represents a landmark achievement in computational biology. It serves as a core tool in modern drug discovery, bioengineering, and molecular research workflows.
Core features & strengths
- Three-Track Neural Architecture — Simultaneously integrates 1D sequence data, 2D distance maps, and 3D atomic coordinates for precise structural predictions.
- Multi-Protein Complex Prediction — Capable of accurately modeling complex multi-chain protein assemblies and intermolecular interaction interfaces.
- Open-Source & Web Accessibility — Can be accessed through the web-based Robetta submission server or installed locally for custom HPC integration.
Who is this tool for?
Structural biologists, bioinformaticians, academic researchers, and biotech professionals working on protein engineering and molecular modeling.
Typical use case
A structural biologist is investigating a novel bacterial surface protein with no known experimental structure. By submitting the amino acid sequence to RoseTTAFold, the researcher receives a detailed 3D structural prediction within hours. This model helps identify potential active sites and guides the rational design of small-molecule inhibitors for drug discovery.
What is RoseTTAFold good for?
- Structural biologists, bioinformaticians, academic researchers, and biotech professionals working on protein engineering and molecular modeling.
- A structural biologist is investigating a novel bacterial surface protein with no known experimental structure.
- Three-Track Neural Architecture: Simultaneously integrates 1D sequence data, 2D distance maps, and 3D atomic coordinates for precise structural predictions.
- Multi-Protein Complex Prediction: Capable of accurately modeling complex multi-chain protein assemblies and intermolecular interaction interfaces.
- Open-Source & Web Accessibility: Can be accessed through the web-based Robetta submission server or installed locally for custom HPC integration.
When a different tool fits better
Not suitable for non-specialists lacking domain knowledge in biochemistry, or for commercial entities evaluating confidential IP using the public web server.
Pricing & plans
Plans in detail
- Academic/Research Access00free
- Access to protein structure prediction models
- No subscription fees for academic users
Good to know
- Computational resources on the Robetta server are limited; queues may occur during periods of high demand.
- The software is available under open-source licenses and can be hosted on local infrastructure.
Prices checked on 15/08/2026. Prices based on public provider information, without warranty. Euro amounts are approximations; the provider's pricing page prevails.
Supported languages
User interface, documentation, and server tools are available exclusively in English.
Interface = the tool's menu language, content = the language you can work in. Without guarantee — vendors keep expanding their language coverage.
Privacy & GDPR
Data flow: When using the Robetta web server, submitted protein sequences are transmitted to and processed on servers at the University of Washington in the USA.
Training on your inputs: Data submitted to public web servers may be evaluated for scientific research pipelines; running the local open-source code avoids any external data transfer.
For companies: There is no standard GDPR DPA for the public academic web server; commercial entities must acquire a license and host the code internally.
Practical advice: Do not submit highly confidential corporate sequences or proprietary IP to the public web server; host the open-source model locally instead.
- GDPR:
- EU data protection regulation: defines how personal data may be processed and what rights you have (access, deletion, objection).
- DPA:
- Data Processing Agreement: contractually binds the provider to process your data only on your instructions. Usually mandatory for companies.
Privacy data checked on 02/08/2026. Editorial summary based on public provider information — not legal advice. When in doubt, check the provider's current privacy terms.
Fact sheet
| Vendor | University of Washington (Baker Lab / RosettaCommons) |
|---|---|
| Headquarters | Seattle, United States |
| Category | Biology & Medicine |
| Pyramid level | Level 22 – Biology, Chemistry & Drug Discovery |
| Pricing model | Open Source |
| Free forever option | Yes |
| Open Source | Yes |
| Entry plan | Academic/Research Access: 0 (0) |
| German | not supported |
| English | interface and content |
| Privacy classification | US Cloud |
| Data processing agreement | There is no standard GDPR DPA for the public academic web server; commercial entities must acquire a license and host the code internally. |
Alternatives to RoseTTAFold
- AlphaFold — Open Source · HQ: London, United Kingdom · GDPR / EU
- Cradle — Paid · HQ: Amsterdam, Netherlands · GDPR / EU
- ESMFold — Open Source · HQ: Menlo Park, United States · GDPR / EU
- Owkin — Paid · HQ: Paris, France · Unclear
- Schrödinger Maestro — Paid · HQ: New York, United States · Unclear
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