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Miniaturizing and modifying natural proteins with Raygun

Research Bioinformatics AI

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TL;DR - Raygun is a generative AI framework that uses probabilistic sequence encodings derived from language-model embeddings to redesign natural proteins. It enables protein miniaturization, modification, and augmentation while preserving native structure and function.

  • Applies language-model embeddings to probabilistic protein sequence generation.
  • Supports multiple redesign operations, including shrinking and augmenting proteins.
  • Prioritizes retention of native architecture and functional integrity.
  • The provided abstract does not include quantitative performance results.

Sources (1)

Miniaturizing and modifying natural proteins with Raygun

Nature Kapil Devkota, Daichi Shonai, Joey Mao, Young Su Ko, Wei Wang, Scott Soderling, Rohit Singh 2026-07-29 doi:10.1038/s41586-026-10842-8
Public signals OpenAlex citations 1
Providers: Hugging Face · N/A OpenAlex · Citations 1 Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-08-26 14:41:28.393200 UTC

TL;DR - Raygun is a generative AI framework that uses probabilistic sequence encodings derived from language-model embeddings to redesign natural proteins. It enables protein miniaturization, modification, and augmentation while preserving native structure and function.

  • Applies language-model embeddings to probabilistic protein sequence generation.
  • Supports multiple redesign operations, including shrinking and augmenting proteins.
  • Prioritizes retention of native architecture and functional integrity.
  • The provided abstract does not include quantitative performance results.
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