Protein Design with Guided Discrete Diffusion

05/31/2023
by   Nate Gruver, et al.
3

A popular approach to protein design is to combine a generative model with a discriminative model for conditional sampling. The generative model samples plausible sequences while the discriminative model guides a search for sequences with high fitness. Given its broad success in conditional sampling, classifier-guided diffusion modeling is a promising foundation for protein design, leading many to develop guided diffusion models for structure with inverse folding to recover sequences. In this work, we propose diffusioN Optimized Sampling (NOS), a guidance method for discrete diffusion models that follows gradients in the hidden states of the denoising network. NOS makes it possible to perform design directly in sequence space, circumventing significant limitations of structure-based methods, including scarce data and challenging inverse design. Moreover, we use NOS to generalize LaMBO, a Bayesian optimization procedure for sequence design that facilitates multiple objectives and edit-based constraints. The resulting method, LaMBO-2, enables discrete diffusions and stronger performance with limited edits through a novel application of saliency maps. We apply LaMBO-2 to a real-world protein design task, optimizing antibodies for higher expression yield and binding affinity to a therapeutic target under locality and liability constraints, with 97 expression rate and 25

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/29/2023

Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds

Proteins power a vast array of functional processes in living cells. The...
research
05/18/2023

Dirichlet Diffusion Score Model for Biological Sequence Generation

Designing biological sequences is an important challenge that requires s...
research
07/02/2023

Optimizing protein fitness using Gibbs sampling with Graph-based Smoothing

The ability to design novel proteins with higher fitness on a given task...
research
01/29/2019

Conditioning by adaptive sampling for robust design

We present a new method for design problems wherein the goal is to maxim...
research
05/26/2022

Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models

Proteins are macromolecules that mediate a significant fraction of the c...
research
05/31/2023

AbODE: Ab Initio Antibody Design using Conjoined ODEs

Antibodies are Y-shaped proteins that neutralize pathogens and constitut...
research
05/09/2022

Multi-segment preserving sampling for deep manifold sampler

Deep generative modeling for biological sequences presents a unique chal...

Please sign up or login with your details

Forgot password? Click here to reset