Computational Modeling Toward Understanding Agonist Binding on Dopamine 3

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• 作者：Yaxue Zhao ; Xuefeng Lu ; Chao-yie Yang ; Zhimin Huang ; Wei Fu ; Tingjun Hou ; Jian Zhang
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2010
• 出版时间：September 27, 2010
• 年：2010
• 卷：50
• 期：9
• 页码：1633-1643
• 全文大小：568K
• 年卷期：v.50,no.9(September 27, 2010)
• ISSN：1549-960X

文摘

The dopamine 3 (D3) receptor is a promising therapeutic target for the treatment of nervous system disorders, such as Parkinson’s disease, and current research interests primarily focus on the discovery/design of potent D3 agonists. Herein, a well-designed computational protocol, which combines pharmacophore identification, homology modeling, molecular docking, and molecular dynamics (MD) simulations, was employed to understand the agonist binding on D3 aiming to provide insights into the development of novel potent D3 agonists. We (1) identified the chemical features required in effective D3 agonists by pharmacophore modeling based upon 18 known diverse D3 agonists; (2) constructed the three-dimensional (3D) structure of D3 based on homology modeling and the pharmacophore hypothesis; (3) identified the binding modes of the agonists to D3 by the correlation between the predicted binding free energies and the experimental values; and (4) investigated the induced fit of D3 upon agonist binding through MD simulations. The pharmacophore models of the D3 agonists and the 3D structure of D3 can be used for either ligand- or receptor-based drug design. Furthermore, the MD simulations further give the insight that the long and flexible EL2 acts as a “door” for agonist binding, and the “ionic lock” at the bottom of TM3 and TM6 is essential to transduce the activation signal.