Ligand Binding Mode Prediction by Docking: Mdm2/Mdmx Inhibitors as a Case Study
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- 作者：Nagakumar Bharatham ; Kavitha Bharatham ; Anang A. Shelat ; Donald Bashford
- 刊名：Journal of Chemical Information and Modeling
- 出版年：2014
- 出版时间：February 24, 2014
- 年：2014
- 卷：54
- 期：2
- 页码：648-659
- 全文大小：662K
- 年卷期：v.54,no.2(February 24, 2014)
- ISSN：1549-960X
文摘
The p53-binding domains of Mdm2 and Mdmx, two negative regulators of the tumor suppressor p53, are validated targets for cancer therapeutics, but correct binding poses of some proven inhibitors, particularly the nutlins, have been difficult to obtain with standard docking procedures. Virtual screening pipelines typically draw from a database of compounds represented with 1D or 2D structural information from which one or more 3D conformations must be generated. These conformations are then passed to a docking algorithm that searches for optimal binding poses on the target protein. This work tests alternative pipelines using several commonly used conformation generation programs (LigPrep, ConfGen, MacroModel, and Corina/Rotate) and docking programs (GOLD, Glide, MOE-dock, and AutoDock Vina) for their ability to reproduce known poses for a series of Mdmx and/or Mdm2 inhibitors, including several nutlins. Most combinations of these programs using default settings fail to find correct poses for the nutlins but succeed for all other compounds. Docking success for the nutlin class requires either computationally intensive conformational exploration or an 鈥渁nchoring鈥?procedure that incorporates knowledge of the orientation of the central imidazoline ring.