Modeling Differential Binding of α4β2 Nicotinic Acetyicholine Receptor with Agonists and Antagonists.

Three-dimensional structures of both the open- and closed-channel states of α4β2 receptor have been modeled and used to study their binding with representative agonists and antagonists. The obtained binding structures and free energies consistently reveal that antagonists bind more favorably with th...

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Publicado en:Journal of the American Chemical Society Vol. 130; no. 49; pp. 16691 - 16697
Autores principales: Xiaoqin Huang, Fang Zheng, Chang-Guo Zhan
Formato: Artículo
Publicado: American Chemical Society 12/10/2008
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 12/10/2008
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        10.1021/ja8055326
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        atl: Modeling Differential Binding of α4β2 Nicotinic Acetyicholine Receptor with Agonists and Antagonists.
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        au:
          Xiaoqin Huang
          Fang Zheng
          Chang-Guo Zhan
        affil: Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky, 725 Rose Street, Lexington, Kentucky 40536
      su:
        Computer network protocols
        Ligand binding (Biochemistry)
        Nicotinic receptors
        Chemical inhibitors
        Chemical agonists
        Biochemistry
        Therapeutics
      sug:
        subj:
          Computer network protocols
          Ligand binding (Biochemistry)
          Nicotinic receptors
          Chemical inhibitors
          Chemical agonists
          Biochemistry
          Therapeutics
      ab: Three-dimensional structures of both the open- and closed-channel states of α4β2 receptor have been modeled and used to study their binding with representative agonists and antagonists. The obtained binding structures and free energies consistently reveal that antagonists bind more favorably with the closed- channel state and agonists bind more favorably with the open-channel state. The computational insights have led us to propose a computational strategy and protocol predicting whether a receptor ligand is an agonist or antagonist. Using the computational protocol, one only needs to calculate the relative binding free energies for a ligand binding with the open- and closed-channel structures. The ligand is predicted to be an agonist if the binding free energy calculated for the ligand binding with the open-channel state is significantly lower than that for its binding with the closed-channel state. If the binding free energy of a ligand with the open-channel state is higher than that with the closed-channel, the ligand is predicted to be an antagonist. The binding free energies calculated for all of the ligands binding with their most favorable channel states of the receptor are all close to the corresponding experimentally derived binding free energies. The new computational insights obtained and novel computational strategy and protocol proposed in this study are expected to be valuable in structure-based rational design of novel agonists/antagonists of nAChRs as therapeutic agents.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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