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Exploring proteins multi-funnel energy landscape

Leonor Cruzeiro-Hansson

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Abstract

An all-atom model of proteins is used to show that the same sequence of amino acids can have many alternative structures, that are very distant from, and that can be as stable as, the corresponding native structure. Such alternative structures are not easily rationalized as belonging to the native basin and indicate instead that the free energy landscape of proteins is multi-funnel-shaped and that Anfinsen's thermodynamic hypothesis alone cannot explain protein folding. An alternative two-step process for folding is proposed and its consistency with the experimental evidence available is discussed.

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An all-atom model of proteins is used to show that the same sequence of amino acids can have many alternative structures, that are very distant from, and that can be as stable as, the corresponding native structure. Such alternative structures are not easily rationalized as belonging to the native basin and indicate instead that the free energy landscape of proteins is multi-funnel-shaped and that Anfinsen's thermodynamic hypothesis alone cannot explain protein folding. An alternative two-step process for folding is proposed and its consistency with the experimental evidence available is discussed.

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Available abstract

An all-atom model of proteins is used to show that the same sequence of amino acids can have many alternative structures, that are very distant from, and that can be as stable as, the corresponding native structure. Such alternative structures are not easily rationalized as belonging to the native basin and indicate instead that the free energy landscape of proteins is multi-funnel-shaped and that Anfinsen's thermodynamic hypothesis alone cannot explain protein folding. An alternative two-step process for folding is proposed and its consistency with the experimental evidence available is discussed.

Key concepts: Funnel, Energy landscape, Folding (DSP implementation), Consistency (knowledge bases), Protein folding, Folding funnel, Computational biology, Physics

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