How can we design protein sequences folding into the desired structures
effectively and efficiently? Structure-based protein design has attracted
increasing attention in recent years; however, few methods can simultaneously
improve the accuracy and efficiency due to the lack of expressive features and
autoregressive sequence decoder. To address these issues, we propose PiFold,
which contains a novel residue featurizer and PiGNN layers to generate protein
sequences in a one-shot way with improved recovery. Experiments show that
PiFold could achieve 51.66\% recovery on CATH 4.2, while the inference speed is
70 times faster than the autoregressive competitors. In addition, PiFold
achieves 58.72\% and 60.42\% recovery scores on TS50 and TS500, respectively.
We conduct comprehensive ablation studies to reveal the role of different types
of protein features and model designs, inspiring further simplification and
improvement.

本论文提出了 PiFold 具有改进恢复能力的新型残基特征提取器和 PiGNN 层，可一次性生成蛋白质序列。实验结果显示，PiFold 能够快速恢复结构，并且在 CATH 4.2，TS50 和 TS500 上的恢复效果也非常好，是以前方法的 70 倍快。