The Next Frontier in Bioinformatics? Cracking the RNA 3D Code

Bioinformatics is fundamentally reshaping modern biology, transforming raw data into life-saving insights.

At the Institute of Biotechnology of the Czech Academy of Sciences, we're committed to pushing these frontiers, developing bespoke tools for handling complex biomolecular structures. While the recent triumph of AlphaFold demonstrated the power of AI to predict protein 3D structures—a monumental achievement built on decades of structural data (over 200,000 PDB entries)—a major challenge remains: Nucleic Acids.

As we detailed in our recent paper, "When will RNA get its AlphaFold moment?" (https://doi.org/10.1093/nar/gkad726), the prediction landscape for RNA and DNA is stalled. The scarcity of high-quality structural data for nucleic acids is the critical bottleneck, preventing the successful adaptation of protein-focused AI methods.

Our Mission: Building the Foundation for RNA's AI Future
To unlock new opportunities in biology and medicine, and to help bring about the "AlphaFold moment" for nucleic acids, we are addressing this data deficit head-on. We have developed a comprehensive platform for the rigorous quality control and refinement of existing nucleic acid structural data:

• Our DNATCO suite of tools (available at dnatco.datmos.org) provides advanced annotation and validation for RNA/DNA structures.
• By using these tools, we can create a gold-standard reference set - a high-quality training basis essential for developing the next generation of machine learning and AI methods focused on nucleic acids.
• Crucially, these tools allow us to identify and refine subtle but important structural features, such as the unusual backbone conformations found in up to a third of nucleotides, making the resulting models far more reliable for training AI.