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<p>Engineering proteins with desired functions remains challenging and usually requires multiple rounds of screening and selection. Here, we present Sequence Display, a platform that generates large-scale protein sequence–activity datasets in a single round. Sequence Display enables multiplexed assessment of individual variant activity within a single experiment, offering a robust approach to mapping detailed sequence–function relationships. We demonstrate the platform’s broad applicability by generating datasets for cytosine deaminase, uracil glycosylase inhibitor, aminoacyl-tRNA synthetase and a compact Cas9 nuclease. Integrating these datasets obtained from Sequence Display with pretrained protein language models, fine-grained, variant-specific activity landscapes can be constructed. We discovered several Cas9 variants with expanded protospacer-adjacent motif recognition and evolved aminoacyl-tRNA synthetase variants capable of recognizing different noncanonical amino acids. Together, this study establishes Sequence Display as a powerful tool for mapping protein activity landscapes and accelerating the discovery of optimized proteins for biological and medical applications.</p>

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Sequence Display enables large-scale sequence–activity datasets for rapid protein evolution

  • 期刊论文

  • 发表日期：

    2026年4月8日

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  • Linqi Cheng,
  • Xinzhe Zheng,
  • Shiyu Jason Jiang,
  • Yu Hu,
  • Yijie Liu,
  • Kaiqiang Yang,
  • Jinyan Rui,
  • Haoxue Ding,
  • Mengxi Zhang,
  • Teng Yuan,
  • Qianglan Lu,
  • Haoxin Ye,
  • Chen-Long Li,
  • Yiming Guo,
  • Zuotong Tian,
  • Anna Qin,
  • Boyang Zhou,
  • Kevin K. Yang,
  • Xiongyi Huang,
  • Han Xiao

摘要

Engineering proteins with desired functions remains challenging and usually requires multiple rounds of screening and selection. Here, we present Sequence Display, a platform that generates large-scale protein sequence–activity datasets in a single round. Sequence Display enables multiplexed assessment of individual variant activity within a single experiment, offering a robust approach to mapping detailed sequence–function relationships. We demonstrate the platform’s broad applicability by generating datasets for cytosine deaminase, uracil glycosylase inhibitor, aminoacyl-tRNA synthetase and a compact Cas9 nuclease. Integrating these datasets obtained from Sequence Display with pretrained protein language models, fine-grained, variant-specific activity landscapes can be constructed. We discovered several Cas9 variants with expanded protospacer-adjacent motif recognition and evolved aminoacyl-tRNA synthetase variants capable of recognizing different noncanonical amino acids. Together, this study establishes Sequence Display as a powerful tool for mapping protein activity landscapes and accelerating the discovery of optimized proteins for biological and medical applications.