A unified multi-molecular modeling system that brings together proteins, nucleic acids, ligands, and complex assemblies
Today at Microsoft Ignite 2025, we are excited to launch RosettaFold3 (RF3) on Microsoft Foundry - making a new generation of multi-molecular structure prediction models available to researchers, biotech innovators, and scientific teams worldwide.
RF3 was developed by the Baker lab and DiMaio lab from the Institute for Protein Design (IPD) at the University of Washington, in collaboration with Microsoft’s AI for Good lab and other research partners. RF3 is now available in Foundry Models, offering scalable access to a new generation of biomolecular modeling capabilities.
A new multi-molecular modeling system, now accessible in Foundry Models
RF3 represents a leap forward in biomolecular structure prediction. Unlike previous generation models focused narrowly on proteins, RF3 can jointly model:
- Proteins (enzymes, antibodies, peptides)
- Nucleic acids (DNA, RNA)
- Small molecules/ligands
- Multi-chain complexes
This unified modeling approach allows researchers to explore entire interaction systems—protein–ligand docking, protein–RNA assembly, protein–DNA binding, and more—in a single end-to-end workflow.
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Key advances in RF3
RF3 incorporates several advancements in protein and complex prediction, making it the state-of-the-art open-source model.
- Joint atom-level modeling across molecular types
RF3 can simultaneously model all atom types across proteins, nucleic acids, and ligands—enabled by innovations in multimodal transformers and generative diffusion models. -
Unprecedented control: atom-level conditioning
Users can provide the 3D structure of a ligand or compound, and RF3 will fold a protein around it. This atom-level conditioning unlocks:
- Targeted drug-design workflows
- Protein pocket and surface engineering
- Complex interaction modeling
Example showing how RF3 allows conditioning on user inputs offering greater control of the model’s predictions.
- Broad templating support for structure-guided design
RF3 allows users to guide structure prediction using:
- Distance constraints
- Geometric templates
- Experimental data (e.g., cryo-EM)
This flexibility is limited in other models and makes RF3 ideal for hybrid computation–wet-lab workflows.
- Extensible foundation for scientific and industrial research
RF3 can be adapted to diverse application areas—including enzyme engineering, materials science, agriculture, sustainability, and synthetic biology.
Use cases
RF3’s multimolecular modeling capabilities have broad applicability beyond fundamental biology. The model enables breakthroughs across medicine, materials science, sustainability, and defense—where structure-guided design directly translates into measurable innovation.
| Sector | Illustrative Use Cases |
| Medicine | Gene therapy research: RF3 enables the design of custom proteins that bind specific DNA sequences for targeted genome repair. |
| Materials Science | Inspired by natural protein fibers such as wool and silk, IPD researchers are designing synthetic fibers with tunable mechanical properties and texture—enabling sustainable textiles and advanced materials. |
| Sustainability | RF3 supports enzyme design for plastic degradation and waste recycling, contributing to circular bioeconomy initiatives. |
| Disease & Vaccine Development | RF3-powered workflows will contribute to structure-guided vaccine design, building on IPD’s prior success with the SKYCovione COVID-19 nanoparticle vaccine developed with SK Bioscience and GSK. |
| Crop Science and Food security | Support for gene-editing technology (due to protein-DNA binding prediction capabilities) for agricultural research, design of small proteins called Anti-Microbial Peptides or Anti-Fungal peptides to fight crop diseases and tree diseases such as citrus greening. |
| Defense & Biosecurity | Enables detection and rapid countermeasure design against toxins or novel pathogens; models of this class are being studied for biosafety applications (Horvitz et al., Science, 2025). |
| Aerospace & Extreme Environments | Supports design of lightweight, self-healing, and radiation-resistant biomaterials capable of functioning under non-terrestrial conditions (e.g., high temperature, pressure, or radiation exposure). |
RF3 has the potential to lower the cost of exploratory modeling, raise success rates in structure-guided discovery, and expand biomolecular AI into domains that were previously limited by sparse experimental structures or difficult multimolecular interactions. Because the model and training framework are open and extensible, partners can also adapt RF3 for their own research, making it a foundation for the next generation of biomolecular AI on Microsoft Foundry.
Get started today
RosettaFold3 (RF3) brings advanced multimolecular modeling capabilities into Foundry Models, enabling researchers and biotech teams to run structure-guided workflows with greater flexibility and speed. Within Microsoft Foundry, you can integrate RF3 into your existing scientific processes—combining your data, templates, and downstream analysis tools in one connected environment.
Start exploring the next frontier of biomolecular modeling with RosettaFold3 in the Foundry Models. You can also discover other early-stage AI innovations in Foundry Labs.
If you’re attending Microsoft Ignite 2025, or watching on demand, be sure to check out our session:
Session: AI Frontier in Foundry Labs: Experiment Today, Lead Tomorrow
About the session:
“Curious about the next wave of AI breakthroughs? Get a sneak peek into the future of AI with Azure AI Foundry Labs—your front door to experimental models, multi-agent orchestration prototypes, Agent Factory blueprints, and edge innovations. If you’re a researcher eager to test, validate, and influence what’s next in enterprise AI, this session is your launchpad. See how Labs lets you experiment fast, collaborate with innovators, and turn new ideas into real impact.”
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