NMA-tune: Generating Highly Designable and Dynamics Aware Protein Backbones
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ACM
Department of Computer Science and Technology
https://proceedings.mlr.press/v267/
Department of Computer Science and Technology
https://proceedings.mlr.press/v267/
Abstract
Description
Protein’s backbone flexibility is a crucial property
that heavily influences its functionality. Recent
work in the field of protein diffusion probabilistic
modelling has leveraged Normal Mode Analysis
(NMA) and, for the first time, introduced informa-
tion about large scale protein motion into the gen-
erative process. However, obtaining molecules
with both the desired dynamics and designable
quality has proven challenging. In this work,
we present NMA-tune, a new method that intro-
duces the dynamics information to the protein
design stage. NMA-tune uses a trainable com-
ponent to condition the backbone generation on
the lowest normal mode of oscillation. We imple-
ment NMA-tune as a plug-and-play extension to
RFdiffusion, show that the proportion of samples
with high quality structure and the desired dy-
namics is improved as compared to other methods
without the trainable component, and we show the
presence of the targeted modes in the Molecular
Dynamics simulations.
Cambridge Trust
Cambridge Trust