5/6 We introduce a framework in which we generate candidate protein structures conditioned on flexibility with FliPS and use BackFlip to select the candidates whose predicted flexibility profile best matches the target before running expensive MD simulations.

4/6 We also introduce BackFlip - an equivariant network that can accurately predict backbone flexibility as derived from MD simulations. Crucially, BackFlip infers flexibility solely from the backbone geometry without requiring evolutionary information, making it useful for de novo protein design.

3/6 In a series of experiments, we demonstrate that FliPS samples novel, realistic proteins with diverse secondary structure composition and a remarkable resemblance to custom target flexibility profiles, as verified in 300ns Molecular Dynamics (MD) simulations of the designed samples.

2/6 Our model FliPS is a conditional flow matching model for protein structure generation. FliPS receives a flexibility profile as conditional input feature and learns how to generate realistic protein structures while respecting target flexibilities.

1/6 One of the key features of functional proteins is their inherent structural flexibility. In our recent work at #ICML, we introduce flexibility to protein structure design! More in a thread below.

Code / Tutorial: github.com/graeter-grou...
Poster: W-109, Thu 17 Jul 11 a.m. PDT — 1:30 p.m. PDT

First time transatlantic and such a view over Greenland 🤯 Wish there were more glaciers :/

Attending conferences in Italy seems to be a great idea 🥸

I finally won a lottery and got the CA visa?! Something must be wrong.. Guess that means me + ICML 2025! 😀

Enjoyed a lot meeting all my old friends and listening to their great talks at Mosbacher Kolloquium this week!

@leif-seute.bsky.social @maxfus.bsky.social

Mounted a co-author 😎