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副作用の標的に対する薬物活動の大規模な予測とテスト
Eugen Lounkine1, Michael J Keiser, Steven Whitebread
1Novartis Institutes for Biomedical Research, Cambridge, Massachusetts 02139, USA.
Nature
|June 23, 2012
まとめ
薬の副作用を予測するのは難しい. 新しいコンピューティング・メソッドは,意図せぬ薬物標的を特定し,その予測の半分を確認し,より安全な薬物発見のための新しい薬物標的と有害反応のリンクを明らかにしました.
科学分野:
- 薬理学 薬理学とは
- コンピューティング・ケミストリー
- 毒理学 毒理学 毒理学
背景:
- 薬剤の有害反応 (ADRs) に関連した意図しない薬物標的 (オフターゲット) を識別することは,従来の経験的方法を使用して困難です.
- 何百ものタンパク質がADRに関与しており,薬剤は複数の標的と相互作用し,従来の指標では関係のないものもあります.
研究 の 目的:
- 73の予期せぬ"副作用"の標的に対して,販売されている656種類の薬物の活性を計算的に予測する.
- 観察された副作用を最もよく説明するオフターゲットを優先するために新しい関連メトリックを開発する.
- 薬物の標的と薬物の副作用に関する包括的なネットワークを構築する.
主な方法:
- 副作用標的の定義されたセットで薬物活動を予測するために計算戦略を使用しました.
- 独自のデータベースと新しい実験的アッセイを通じて,検証された予測.
- 関連メトリックを開発し,適用し,新たに特定された非目標値と特定のADRを関連付けました.
主要な成果:
- 計算による予測の約50%が実験的に確認され,親和度は1nMから30μMまでであった.
- クロロトリアニゼンのサイクロオキシゲナーゼ-1 (COX-1) 抑制が腹痛の原因であるなど,新たな薬物標的関連が特定されました.
- 血小板集積アッセイを通じて,特定された標的外相互作用の臨床的関連性を検証しました.
結論:
- コンピューティングによるアプローチは,意図しない薬物標的とその薬物不良反応との関連を効果的に予測します.
- この戦略は,ADRsの基礎となる新しいメカニズムを特定し,薬剤発見のリスクを軽減するために,オフターゲットの優先順位を付けることができます.
- 開発された薬物標的薬物不良反応ネットワークは,毒性学的負債を理解し軽減するための貴重なツールを提供します.
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