Skip to content

RNA & Protein Design

Note

  • Autoregressive Approach:
    • AlphaFold 2, Nature, 2021
    • RoseTTAFold2, bioRxiv, 2023
  • Diffusion Approach:
    • RFDiffusion, Nature, 2023
    • RoseTTAFold All-Atom, Science, 2024
    • AlphaFold 3 (All-Atom), Nature, 2024

0. Protein Design

  • ✅ [review] 2024 NBT - Machine learning for functional protein design
  • ✅ 2024 Science - Generalized biomolecular modeling and design with RoseTTAFold All-Atom
  • ✅ 2023 Nature - De novo design of protein structure and function with RFdiffusion
  • [benchmark] 2024 NBT - Computational scoring and experimental evaluation of enzymes generated by neural networks
  • 2023 Nature - Illuminating protein space with a programmable generative model
  • 2022 Nature Biotech. - Large language models generate functional protein sequences across diverse families

I. RNA Design

  • ✅ [RfamGen] 2024 Nature Methods - Deep generative design of RNA family sequences
  • 2024 Nature Machine Intelligence - Multi-purpose RNA language modelling with motif-aware pretraining and type-guided fine-tuning
  • ✅ 2024 Nature machine intelligence - A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions
  • 2024 Cell Genome - Revealing the grammar of small RNA secretion using interpretable machine learning
  • 2024 Nature Methods - Deep generative design of RNA family sequences
  • 2023 bioRXiv - CodonBERT- Large Language Models for mRNA Design and Optimization
  • 2023 BIB - Integrated mRNA sequence optimization using deep learning
  • 2021 NAR - Theoretical basis for stabilizing messenger RNA through secondary structure design

II. RNA Vaccine Design