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Updated: Sep 9, 2025

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ARCADE: ファンデーションモデルからアクティベーションエンジニアリングによる制御可能なコドン設計

Jiayi Li¹, Litian Liang¹, Shiyi Du¹

¹Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 15217, US.

bioRxiv : the preprint server for biology

|September 2, 2025

まとめ

ARCADEは,アクティベーションエンジニアリングと事前に訓練されたゲノムモデルを使用して,mRNAコドン配列設計に対する柔軟な制御を提供します. このアプローチは,mRNAワクチンや遺伝子編集療法などの応用のためにプログラム可能な生物学的配列設計を強化します.

科学分野:

バイオ情報学
コンピュータ生物学
合成生物学

背景:

コドン配列の設計はmRNA療法と遺伝子編集に不可欠です.
現在の方法は,多様な設計目的のために必要な柔軟性と制御が欠けている.

研究の目的:

柔軟で制御可能なコドン配列生成のための新しい枠組みであるARCADEを導入する.
強化された配列設計のための連続生物学的メトリックにアクティベーションエンジニアリングを拡張する.

主な方法:

ARCADEは,事前に訓練されたゲノム基盤モデルのアクティベーションエンジニアリングを使用しています.
モデルのアクティベーションスペースに生物学的に有意義な意味学的な方向ベクトルを使用します.
フレームワークはコドン適応指数,最小自由エネルギー,再訓練なしにGC含有量などの連続的な性質を調節します.

主要な成果:

ARCADEは,既存の方法と比較して優れた性能と著しく高い柔軟性を示しています.
このアプローチにより,複数の連続した生物学的メトリックを正確に制御できます.

結論:

ARCADEはプログラム可能な生物学的配列設計における重要な進歩を表しています
この枠組みは,新しいmRNAワクチンや遺伝子編集療法の開発を加速させる可能性を秘めています.

キーワード:

アクティベーションエンジニアリング制御可能なシーケンス生成ゲノミクスの基礎モデル基礎モデルの研修後 mRNAデザイン

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