グラフ理論を用いた超分子機械のメチル-NMRスペクトルの自動割り当て
Iva Pritišanac1, Matteo T Degiacomi1, T Reid Alderson1
1Department of Chemistry, Physical & Theoretical Chemistry Laboratory, University of Oxford , South Parks Road, Oxford, Oxfordshire OX1 3QZ, U.K.
Journal of the American Chemical Society
|July 11, 2017
まとめ
メチルグループは,NMRを用いた生物分子構造の分析に不可欠である. 新しい方法であるグラフマッチングによるメチル配分 (MAGMA) は,メチル共鳴を100%の精度で自動的に配分し,研究を加速します.
科学分野:
- 生化学と構造生物学
- 核磁共振 (NMR) スペクトロスコーピー
- コンピューター生物学
背景:
- メチルグループは,NMRによる超分子組成構造,動力学,および機能の研究に価値があります.
- メチル共鳴を特定の生物分子の位置に割り当てることは,方法論の適用を制限する重要な課題です.
研究 の 目的:
- NMRスペクトロシーにおけるメチル共振の割り当てのための自動化された方法を開発する.
- 生物分子内のスペクトル共鳴の割り当てにおける既存の制限を克服する.
主な方法:
- グラフマッチングによるメチル割り当て (MAGMA) の導入,自動化されたプロトコル.
- グラフマッチングを使用して,各共鳴の割り当ての可能性を調査します.
- 合成データと9つのクロス検証された溶液と固体NMRの例による検証
主要な成果:
- MAGMAは100%の精度で 信頼性の高いメチル共振配分を実現します
- タンパク質の構造を区別する能力を示した.
- HSP90の薬剤発見研究で,リガンド結合モードを効率的に区別した.
結論:
- MAGMAはメチル共振配分のための正確で堅固なソリューションを提供します.
- この方法は,メチルベースのNMRを用いた超分子機械の研究を大幅に加速します.
- 薬の発見や 構造生物学の研究を 速くできるようになります
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