Predicting RNA activity expands therapeutic possibilities
Why it matters: Predicting RNA activity unlocks new therapies and deepens our understanding of genetic diseases.
- Hashim Al-Hashimi argues that the ultimate goal isn't just solving structures, but understanding how molecules function and perform their biological jobs inside cells.
- New research from Al-Hashimi's lab shows that predicting RNA activity is possible by considering the "ensemble" of shapes an RNA can adopt, rather than a single structure.
- The team successfully predicted the activity of HIV's TAR RNA using existing biophysical models, revealing that mutations impact activity by altering the RNA's conformational ensemble, not just its contacts with other molecules.
- This breakthrough could lead to new drug discoveries, solve genetic disease mysteries, and improve in silico cell modeling.
While AI excels at predicting protein structures, Columbia biophysicist Hashim Al-Hashimi highlights a critical gap: predicting the actual cellular activity of RNA and DNA. His lab's new research, published in Cell, demonstrates that RNA activity can be predicted from biophysical principles, specifically by understanding how sequence changes the ensemble of structures an RNA can adopt.
