Deep Learning’s Impact on de novo Protein Design

Key Takeaways: With advancements in AI, the field of protein engineering has shifted from template-based approaches to de novo designs with approaches including seed-based design, deep generative models, and binder hallucination. Design towards specific protein functions is the current frontier factoring in parameters including neosurfaces, conditional binding with biological stimuli, and dynamic modeling, linking deep…

Read More

Next Generation Generative Model Unlocks de novo Designs at Scale

Key Takeaways: NVIDIA’s new Proteina-Complexa model combines generative AI with inference-time search algorithms to operate 30-60x faster than RFdiffusion when designing custom proteins that target specific diseases. In a test to find binders for 127 different targets from over 1 million protein designs, the model successfully found binders for 68% of the targets. The model…

Read More

Rosetta Commons Run (rc-run) Now Available

We are pleased to announce a new Rosetta Commons workflow optimization tool: rc-run. rc-run (invoked as rc) is a command-line utility tool for running containerized and native biomolecular software. It simplifies common tasks, such as mounting local directories, building HPC containers, running containerized applications, and logging executed commands, to make complex workflows easier to reliably…

Read More

CyclicMPNN adapts sequence design to cyclic backbones

Why this work matters Cyclic peptides are attractive scaffolds because their closed backbone can promote structural rigidity and proteolytic stability. Yet assigning sequences that reliably fold into a given cyclic backbone remains a key challenge. In this study, the authors introduce CyclicMPNN, a fine-tuned version of ProteinMPNN designed specifically to improve sequence design for short…

Read More

Foundry Docker Image Now Available

Rosetta Commons now offers an official Foundry Docker image designed to make it dramatically easier to run cutting-edge biomolecular machine learning models without complex setup. Foundry is the central repository for a suite of ML models used in protein science—including RF3 (a next-generation biomolecular structure prediction network), ProteinMPNN inverse-folding models, and the newest RFdiffusion3 (RFD3)…

Read More

Engineering a protein biosensor to detect common NSAIDs in wastewater

Why this research matters Pharmaceuticals often end up in wastewater after use, and monitoring them can be technically demanding. Traditional analytical methods are powerful but typically require specialized equipment and off-site processing, which can limit how frequently water is tested. This study describes a protein-based biosensor designed to detect two widely used “profen” non-steroidal anti-inflammatory…

Read More

Ultra-large virtual screening using a motif-guided Rosetta pipeline validated in zebrafish

Broader significance: a screenable path from computation to in vivo Virtual screening can now evaluate billions of molecules. But that scale creates a practical problem. Docking pipelines often return thousands of candidates that pass computational filters, and predicted binding energies do not reliably predict what will work in living systems. This study introduces a workflow…

Read More

Using protein design experiments to guide energy-function development

Why this matters When a protein is designed on a computer, tiny “impossible overlaps” between atoms can slip into the model. Those clashes may look small on-screen, but they can push a real protein to adopt a different shape than intended. In a December 2025 bioRxiv preprint, the authors show that steric clashing is a…

Read More

Optimizing Stability in Dynamic Small-Molecule Binding Proteins

Why this research matters Many proteins must change shape to function. For proteins that bind small molecules, this motion is essential for activity but often makes them difficult to stabilize. Efforts to increase stability can unintentionally disrupt binding by shifting how the protein moves. This study examines how explicitly accounting for protein motion during design…

Read More

Quarterly PyRosetta builds now available

We are happy to announce the availability of quarterly PyRosetta builds. These builds provide persistent wheel packages that are retained long-term (potentially indefinitely), making it straightforward to create reproducible PyRosetta environments across all supported build flavors and Python versions. This is now the recommended installation path for users who need stability and reproducibility.   Below…

Read More