Columbia predicts RNA activity from sequence
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- Cell published the study "Thermodynamic Prediction of RNA Cellular Activity from Sequence via Conformational Ensembles" (2026) by Al‑Hashimi’s lab.
- Al‑Hashimi’s lab experimentally measured the conformational ensembles of HIV TAR RNA and 27 single‑point mutants, and quantified each mutant’s cellular activity.
- Biophysical secondary‑structure models successfully predicted the activity of thousands of TAR sequences directly from their nucleotide sequence, without using AI.
- The same predictive framework accurately forecasted activity for another HIV regulatory RNA, RRE, indicating broader applicability.
- Conserved nucleotides in TAR were shown to be essential because mutations disrupt the ensemble balance, altering activity rather than just molecular contacts.
- Future work aims to extend the models to larger, more complex RNAs and improve predictions of activity inside cells, potentially aiding drug design and genetic disease mechanistic modeling.
Why it matters: Biologists and pharmaceutical developers gain a quantitative tool to anticipate how RNA mutations affect cellular function, reducing reliance on costly trial‑and‑error experiments. This shifts drug design from static lock‑and‑key models toward ensemble‑based strategies, potentially accelerating therapies in RNA‑linked diseases globally.
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