Why is RoseTTAFold All-Atom a game changer?

Traditionally, studying macromolecules and biomolecular assemblies required scientists to perform rigorous and time-consuming wet experiments. Three years ago, AlphaFold2 (AF2), and shortly after RoseTTAFold (RF), completely changed this by achieving experimental-level accuracy of protein structure prediction.

The release of AF2 undoubtedly revolutionized structural biology, enabling improved structural hypothesis generation and providing a launching pad for new AF2-based tools. However, the capabilities of AF2 and later tools have been limited to the prediction of solely polypeptide chains.

RoseTTAFold All-Atom (RFAA) is a next-generation method that builds on the achievement of AF2 and RF to enable the prediction of biomolecular complexes. RF-AA is capable of predicting the structures of all atoms of a biological unit, including:

• proteins
• metal ions
• nucleic acids
• small molecules
• covalent modifications

The complex network of biological activities within cells is rarely limited to isolated protein function. Proteins interact extensively, forming assemblies with each other for signaling, interacting with DNA and RNA to manage gene expression, and binding to small molecules to drive metabolism and communication. Until RFAA, accurately modeling these intricate interactions had remained a significant hurdle despite the impressive successes in predicting protein-only structures.

RFAA, alongside its companion model RFdiffusion All-Atom (RFdiffusionAA), unlocks the ability to model and design these complex biomolecular assemblies with remarkable accuracy. This has far-reaching implications, including:

• Breakthrough in Structural Biology: Enabling the modeling of biomolecular complexes beyond protein-only prediction.
• Impact on Drug Discovery: Providing detailed models that allow for precise prediction of complex prediction at the atomic level, facilitating the design of more effective and specific drugs with potentially fewer side effects.
• Advancements in Synthetic Biology: Enabling the (re-)design of proteins with engineered functions and interactions with non-protein partners.
• Democratizing Molecular Biology: The open-source RFAA code makes molecular biology tools accessible worldwide, particularly benefiting researchers in under-resourced regions and fostering global scientific collaboration and innovation.
• Future Prospects: Expected to integrate into more complex biological systems, improve in accuracy and efficiency with ongoing advancements in technology, providing a basis for future developments, increasing its applications and impact on larger scale biological and medical questions.

Paper: Generalized biomolecular modeling and design with RoseTTAFold All-Atom

GitHub: https://github.com/baker-laboratory/RoseTTAFold-All-Atom

Integration with Genophore and Stand-Alone Version

We are excited to announce that RoseTTAFold All-Atom (RFAA) is now seamlessly integrated into the Genophore Platform, enhancing protein design and biologics discovery workflows. This integration allows researchers to leverage the powerful AI-driven capabilities of RFAA directly within their existing Genophore pipelines, streamlining the process of designing and analyzing complex biomolecular assemblies.

Key Features of the Integration:

• Enhanced Workflow Efficiency: Integrate RFAA's all-atom prediction capabilities without leaving the Genophore environment, reducing the need for manual data transfers and improving overall workflow speed.
• Comprehensive Biomolecular Modeling: Utilize RFAA to predict and design not just proteins, but also their interactions with metal ions, nucleic acids, small molecules, and covalent modifications within the Genophore platform.
• User-Friendly Interface: Benefit from a cohesive and intuitive interface that combines Genophore's robust tools with RFAA's advanced modeling features, making complex biomolecular design accessible to both novice and experienced researchers.

In addition to the integrated solution within Genophore, we are pleased to offer a stand-alone version of RFAA for those who prefer or require a separate deployment. This version provides the full suite of RFAA's capabilities, ensuring flexibility and adaptability to diverse research needs.

Get Started Today:

• Integrated with Genophore: Explore the RFAA Integration. 
• Stand-Alone Version: Explore RFAA Stand-Alone with multi-chain, ligands and nucleic acids co-folding capabilities.

By integrating RFAA with Genophore and offering a stand-alone version, we aim to empower the scientific community and therapeutics discovery scientists with versatile tools to advance research in structural biology, drug discovery, synthetic biology, and beyond. Visit our AI-powered capabilities page for more information, documentation, and support.