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  3. Raptscore: A Large Language Model-based Algorithm For Versatile Aptamer Evaluation.
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  3. Raptscore: A Large Language Model-based Algorithm For Versatile Aptamer Evaluation.

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RaptScore: a large language model-based algorithm for versatile aptamer evaluation.

Akira Kimura-Yamazaki1, Tatsuo Adachi2, Shigetaka Nakamura2

  • 1Graduate School of Advanced Science and Engineering, Waseda University, Shinjuku-ku Okubo 3-4-1, 169-0072 Tokyo, Japan.

Nucleic Acids Research
|January 14, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Researchers developed RaptScore, a new metric using large language models to evaluate RNA aptamer binding activity. This tool identifies shorter, effective aptamers and improves discovery efficiency, reducing experimental work.

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Area of Science:

  • Biotechnology
  • Computational Biology
  • Drug Discovery

Background:

  • RNA aptamers are valuable tools in life sciences, particularly for drug discovery.
  • Systematic Evolution of Ligands by Exponential Enrichment (SELEX) is a common method for aptamer generation but has limitations.
  • Existing evaluation metrics for aptamers are restricted to sequences found in SELEX and cannot assess varying lengths.

Purpose of the Study:

  • To develop a novel binding activity evaluation metric for RNA aptamers that overcomes SELEX limitations.
  • To enable assessment of arbitrary sequences, including those not identified by SELEX, and accommodate sequence length variations.
  • To enhance aptamer design optimization and discovery efficiency.

Main Methods:

  • Development of RaptScore, a new metric leveraging large language models for RNA aptamer binding activity evaluation.
  • Integration of RaptScore with in silico maturation for aptamer sequence optimization.
  • Combination of RaptScore with RaptGen, a variational autoencoder-based aptamer discovery tool.

    • Main Results:

    • RaptScore demonstrated a strong correlation with actual binding activity.
    • Identification of shorter RNA aptamers with maintained or enhanced binding properties.
    • Achieved a 10-nucleotide sequence truncation while preserving binding efficiency through RaptScore and in silico maturation.
    • Improved aptamer discovery efficiency when RaptScore was combined with RaptGen.

    Conclusions:

    • RaptScore is a powerful tool for evaluating and optimizing RNA aptamer sequences.
    • The metric facilitates the discovery of high-activity aptamers, including shorter variants.
    • RaptScore significantly reduces experimental effort in aptamer research and development.