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Divya Nori: Introducing RNAFlow
Jul 8, 2024, 11:15

Divya Nori: Introducing RNAFlow

Divya Nori, Undergraduate Researcher at Eric and Wendy Schmidt Center at Broad Institute of MIT and Harvard, made the following post on X:

“Introducing RNAFlow, a protein-conditioned RNA generative model for structure and sequence design. Excited to present this work, mentored by Wengong Jin, ICML Conference in a few weeks!
Paper.

Divya Nori: Introducing RNAFlow

RNAs can be engineered to perform versatile functions, particularly through their interactions with specific protein binding partners.

Divya Nori: Introducing RNAFlow

In the protein design field, diffusion and flow matching models that fine-tune pre-trained structure prediction networks have excelled at conditional binder design. But this is computationally expensive and necessitates a separate sequence design step.

RNAFlow uses inverse folding as a bridge to unlock the generative capability of pre-trained structure prediction models, without fine-tuning. We predict a denoised sequence from a noisy backbone, with protein conditioning (using a modified version of gRNAde from Chaitanya K. Joshi!)

Divya Nori: Introducing RNAFlow

A frozen RosettaFold2NA network folds the sequence into a denoised structure to perform flow matching in structural space. RNAFlow can design RNAs with modest sequence and structure accuracy while maintaining novelty! See the paper for details.

Divya Nori: Introducing RNAFlow

Further, we model the dynamic nature of RNA. Over the course of flow matching inference, RNAFlow generates a trajectory of structures. The final RNA sequence design is conditioned on the last few inference outputs which approximate a conformational ensemble.

Divya Nori: Introducing RNAFlow

We evaluate whether RNAFlow can design the sequence and structure of an aptamer that binds to GRK2, a target of interest for chronic heart failure. We provide a known binding motif of 4-nucleotides. RNAFlow’s predictions resemble the true aptamer’s sequence and structure!

Divya Nori: Introducing RNAFlow

If you’d like to chat about RNAFlow, or ML for biology in general, please reach out! Excited to connect ICML Conference.”

Source: Divya Nori/X