Protein structure generation via folding diffusion
Stanford University · Microsoft (United States) · +2 more institutions
Abstract
The ability to computationally generate novel yet physically foldable protein structures could lead to new biological discoveries and new treatments targeting yet incurable diseases. Despite recent advances in protein structure prediction, directly generating diverse, novel protein structures from neural networks remains difficult. In this work, we present a diffusion-based generative model that generates protein backbone structures via a procedure inspired by the natural folding process. We describe a protein backbone structure as a sequence of angles capturing the relative orientation of the constituent backbone atoms, and generate structures by denoising from a random, unfolded state towards a stable folded…
Citation impact
- FWCI
- 28.49
- Percentile
- 100%
- References
- 74
Authors
7Topics & keywords
- Computer science
- Protein folding
- Threading (protein sequence)
- Protein structure
- Biological system
- Protein structure prediction
- Protein design
- Physics