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マルコフ国家モデル:芸術から科学へ

Brooke E Husic¹, Vijay S Pande¹

¹Department of Chemistry, Stanford University , Stanford, California 94305, United States.

Journal of the American Chemical Society

|January 12, 2018

まとめ

マルコフ状態モデル (MSM) は,複雑な分子動力学 (MD) シミュレーションを分析するための堅牢な枠組みを提供します. タンパク質の折りたたみや薬剤の発見などの様々な用途のために MSMの構築を簡素化しました

科学分野:

コンピュータ化学
バイオ物理学
統計的メカニズム

背景:

マルコフ状態モデル (MSM) は,分子動力学 (MD) シミュレーションを分析するために広く使用されています.
この分野は数十年で大きく進化し,方法論とソフトウェアの重要な進展がありました.
初期の研究は基礎概念に焦点を当て,後の研究はMD分析のためのMSMを確立した.

研究の目的:

マルコフ状態モデル (MSM) の歴史的概要を一般の聴衆に提供する.
MSMの方法論と応用における重要な進展と転換点を強調する.
生物学的過程を理解し,薬の発見を促進するMSMの影響を示します.

主な方法:

MSMにおける基礎論文と方法論的進歩を年代順にまとめました
客観的なMSM構築のためのバリエーション原則の開発を強調する.
モデル選択とオープンソースソフトウェアの活用におけるベストプラクティスの統合

主要な成果:

2013年のバリエーション原則の推移は,MSMを体系的かつ客観的に構築する方向に変化した.
MSMの進歩により,タンパク質の折りたたみ,アロステリー,およびリガンド結合などの分野で広範な応用が可能になった.
オープンソースソフトウェアはMSMの分析を民主化しより広い研究コミュニティにアクセスできるようにしました

結論:

MSMは複雑な動的システムを分析するための強力で,ますますアクセシブルなツールです.
現在の研究領域は,さらなる方法論的改善と新しい応用に焦点を当てています.
MSMは実験設計と薬剤発見の努力を加速する上で重要な役割を果たす準備ができています.

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