Out of Many, One: Designing and Scaffolding Proteins at the Scale of the Structural Universe with Genie 2
<|reference_start|>Out of Many, One: Designing and Scaffolding Proteins at the Scale of the Structural Universe with Genie 2: Protein diffusion models have emerged as a promising approach for protein design. One such pioneering model is Genie, a method that asymmetrically represents protein structures during the forward and backward processes, using simple Gaussian noising for the former and expressive SE(3)-equivariant attention for the latter. In this work we introduce Genie 2, extending Genie to capture a larger and more diverse protein structure space through architectural innovations and massive data augmentation. Genie 2 adds motif scaffolding capabilities via a novel multi-motif framework that designs co-occurring motifs with unspecified inter-motif positions and orientations. This makes possible complex protein designs that engage multiple interaction partners and perform multiple functions. On both unconditional and conditional generation, Genie 2 achieves state-of-the-art performance, outperforming all known methods on key design metrics including designability, diversity, and novelty. Genie 2 also solves more motif scaffolding problems than other methods and does so with more unique and varied solutions. Taken together, these advances set a new standard for structure-based protein design. Genie 2 inference and training code, as well as model weights, are freely available at: https://github.com/aqlaboratory/genie2.<|reference_end|>
@article{lin2024out,
    title={Out of Many, One: Designing and Scaffolding Proteins at the Scale of the
  Structural Universe with Genie 2},
    author={Yeqing Lin, Minji Lee, Zhao Zhang, Mohammed AlQuraishi},
    journal={arXiv preprint arXiv:2405.15489},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.15489},
    primaryClass={q-bio.BM cs.LG}
}